clinical presentation of chronic kidney disease

Chronic Kidney Disease (CKD) Clinical Presentation

• Author: Pradeep Arora, MD; Chief Editor: Vecihi Batuman, MD, FASN  more...
• Sections Chronic Kidney Disease (CKD)
• Practice Essentials
• Pathophysiology
• Epidemiology
• Patient Education
• Physical Examination
• Approach Considerations
• Kidney Function Formulas
• Renal Ultrasonography
• Radiography
• CT, MRI, and Radionuclide Scans
• Kidney Biopsy
• Delaying or Halting Progression of Chronic Kidney Disease
• Treating Pathologic Manifestations of Chronic Kidney Disease
• Renal Replacement Therapy
• Consultations and Long-Term Monitoring
• Medication Summary
• Calcium Salts
• Vitamin D Analogues
• PO4 Scavengers
• Hematopoietic Growth Factors
• Hypoxia-Inducible Factors Inhibitors
• Iron Products
• Calcimimetics
• Sodium-Glucose Transporter-2 (SGLT2) Inhibitors
• Mineralocorticoid Receptor Antagonists
• Sodium/Hydrogen Exchanger 3 (NHE3) Inhibitors
• Questions & Answers

Patients with chronic kidney disease (CKD) stages 1-3 (glomerular filtration rate [GFR] > 30 mL/min/1.73 m²) are frequently asymptomatic; in terms of possible “negative” symptoms related simply to the reduction in GFR, they do not experience clinically evident disturbances in water or electrolyte balance or endocrine/metabolic derangements.

Generally, these disturbances become clinically manifest with CKD stages 4-5 (GFR < 30 mL/min/1.73 m²). Patients with tubulointerstitial disease, cystic diseases, nephrotic syndrome, and other conditions associated with “positive” symptoms (eg, polyuria, hematuria, edema) are more likely to develop signs of disease at earlier stages.

Uremic manifestations in patients with CKD stage 5 are believed to be primarily secondary to an accumulation of multiple toxins, the full spectrum and identity of which is generally not known. Metabolic acidosis in stage 5 may manifest as protein-energy malnutrition, loss of lean body mass, and muscle weakness. Altered salt and water handling by the kidney in CKD can cause peripheral edema and, not uncommonly, pulmonary edema and hypertension.

Anemia, which in CKD develops primarily as a result of decreased renal synthesis of erythropoietin, manifests as fatigue, reduced exercise capacity, impaired cognitive and immune function, and reduced quality of life. Anemia is also associated with the development of cardiovascular disease, the new onset of heart failure, the development of more severe heart failure, and increased cardiovascular mortality.

Other manifestations of uremia in end-stage renal disease (ESRD), many of which are more likely in patients who are inadequately dialyzed, include the following:

Pericarditis: Can be complicated by cardiac tamponade, possibly resulting in death

Encephalopathy: Can progress to coma and death

Peripheral neuropathy

Restless leg syndrome

Gastrointestinal symptoms: Anorexia, nausea, vomiting, diarrhea

Skin manifestations: Dry skin, pruritus, ecchymosis

Fatigue, increased somnolence, failure to thrive

Malnutrition

Erectile dysfunction, decreased libido, amenorrhea

Platelet dysfunction with tendency to bleed

A careful physical examination is imperative. It may reveal findings characteristic of the condition that is underlying chronic kidney disease (CKD) (eg, lupus, severe arteriosclerosis, hypertension) or its complications (eg, anemia, bleeding diathesis, pericarditis). However, the lack of findings on physical examination does not exclude kidney disease. In fact, CKD is frequently clinically silent, so screening of patients without signs or symptoms at routine health visits is important.

Screening for depression

Forty-five percent of adult patients with CKD have depressive symptoms at initiation of dialysis therapy, as assessed using self-report scales. However, these scales may emphasize somatic symptoms—specifically, sleep disturbance, fatigue, and anorexia—that can coexist with chronic disease symptoms.

Hedayati et al reported that the 16-item Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR[16]) and the Beck Depression Inventory (BDI) are effective screening tools and that scores of 10 and 11, respectively, were the best cutoff scores for identification of a major depressive episode in their study's patient population. [ 43 ] The study compared the BDI and QIDS-SR(16) with a gold-standard structured psychiatric interview in 272 patients with CKD stages 2-5 who had not been treated with dialysis.

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Ha JT, Neuen BL, Cheng LP, Jun M, Toyama T, Gallagher MP, et al. Benefits and Harms of Oral Anticoagulant Therapy in Chronic Kidney Disease: A Systematic Review and Meta-analysis. Ann Intern Med . 2019 Jul 16. [QxMD MEDLINE Link] .

Piccoli GB, Capizzi I, Vigotti FN, Leone F, D'Alessandro C, Giuffrida D, et al. Low protein diets in patients with chronic kidney disease: a bridge between mainstream and complementary-alternative medicines?. BMC Nephrol . 2016 Jul 8. 17 (1):76. [QxMD MEDLINE Link] . [Full Text] .

Suckling RJ, He FJ, Macgregor GA. Altered dietary salt intake for preventing and treating diabetic kidney disease. Cochrane Database Syst Rev . 2010 Dec 8. CD006763. [QxMD MEDLINE Link] .

Slagman MC, Waanders F, Hemmelder MH, et al. Moderate dietary sodium restriction added to angiotensin converting enzyme inhibition compared with dual blockade in lowering proteinuria and blood pressure: randomised controlled trial. BMJ . 2011 Jul 26. 343:d4366. [QxMD MEDLINE Link] . [Full Text] .

Vegter S, Perna A, Postma MJ, et al. Sodium Intake, ACE Inhibition, and Progression to ESRD. J Am Soc Nephrol . 2012 Jan. 23(1):165-73. [QxMD MEDLINE Link] .

Romanowski A. Diets for Patients With CKD: What's New, What's Best?. Medscape Medical News. Available at https://www.medscape.com/viewarticle/910884 . March 27, 2019; Accessed: May 1, 2019.

Clegg DJ, Hill Gallant KM. Plant-Based Diets in CKD. Clin J Am Soc Nephrol . 2019 Jan 7. 14 (1):141-143. [QxMD MEDLINE Link] . [Full Text] .

Goraya N, Simoni J, Jo C, Wesson DE. Dietary acid reduction with fruits and vegetables or bicarbonate attenuates kidney injury in patients with a moderately reduced glomerular filtration rate due to hypertensive nephropathy. Kidney Int . 2012 Jan. 81(1):86-93. [QxMD MEDLINE Link] .

Mallamaci F, Pisano A, Tripepi G. Physical activity in chronic kidney disease and the EXerCise Introduction To Enhance trial. Nephrol Dial Transplant . 2020 Mar 1. 35 (Suppl 2):ii18-ii22. [QxMD MEDLINE Link] . [Full Text] .

Barcellos FC, Santos IS, Umpierre D, Bohlke M, Hallal PC. Effects of exercise in the whole spectrum of chronic kidney disease: a systematic review. Clin Kidney J . 2015 Dec. 8 (6):753-65. [QxMD MEDLINE Link] .

Sakaguchi Y, Shoji T, Kawabata H, Niihata K, Suzuki A, Kaneko T, et al. High prevalence of obstructive sleep apnea and its association with renal function among nondialysis chronic kidney disease patients in Japan: a cross-sectional study. Clin J Am Soc Nephrol . 2011 May. 6(5):995-1000. [QxMD MEDLINE Link] . [Full Text] .

[Guideline] Inker LA, Astor BC, Fox CH, Isakova T, Lash JP, Peralta CA, et al. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis . 2014 May. 63 (5):713-35. [QxMD MEDLINE Link] . [Full Text] .

• Chronic kidney disease: Calciphylaxis due to secondary hyperparathyroidism.

Contributor Information and Disclosures

Pradeep Arora, MD Assistant Professor of Medicine, University of Buffalo State University of New York School of Medicine and Biomedical Sciences; Attending Nephrologist, Veterans Affairs Western New York Healthcare System Disclosure: Nothing to disclose.

Vecihi Batuman, MD, FASN Professor of Medicine, Section of Nephrology-Hypertension, Deming Department of Medicine, Tulane University School of Medicine Vecihi Batuman, MD, FASN is a member of the following medical societies: American College of Physicians , American Society of Hypertension , American Society of Nephrology , Southern Society for Clinical Investigation Disclosure: Nothing to disclose.

George R Aronoff, MD Director, Professor, Departments of Internal Medicine and Pharmacology, Section of Nephrology, Kidney Disease Program, University of Louisville School of Medicine

George R Aronoff, MD is a member of the following medical societies: American Federation for Medical Research , American Society of Nephrology , Kentucky Medical Association , and National Kidney Foundation

Disclosure: Nothing to disclose.

Laura Lyngby Mulloy, DO, FACP Professor of Medicine, Chief, Section of Nephrology, Hypertension, and Transplantation Medicine, Glover/Mealing Eminent Scholar Chair in Immunology, Medical College of Georgia

Francisco Talavera, PharmD, PhD Adjunct Assistant Professor, University of Nebraska Medical Center College of Pharmacy; Editor-in-Chief, Medscape Drug Reference

Disclosure: Medscape Salary Employment

Mauro Verrelli, MD, FRCP(C), FACP Assistant Professor, Department of Medicine, Section of Nephrology, University of Manitoba, Canada

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• Chronic Kidney Disease (CKD)
• Kidney Disease and Pregnancy
• Chronic Kidney Disease in Children
• Managing Cardiovascular Risk in Patients With Chronic Kidney Disease
• Fast Five Quiz: Chronic Kidney Disease Differential Diagnosis
• Fast Five Quiz: Chronic Kidney Disease Complications
• Early Recognition of Chronic Kidney Disease in Patients With Type 2 Diabetes
• Semaglutide Significantly Improves Chronic Kidney Disease
• A Racing Heart Signals Trouble in Chronic Kidney Disease
• Chronic Kidney Disease and Tooth Loss After Menopause
• AJKD Blog NephMadness

• Drug Interaction Checker
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• 2001/viewarticle/981891 New Consensus on Diabetes and Chronic Kidney Disease Together
• 2010/viewarticle/999124Self Assessment Self Assessment Fast Five Quiz: Chronic Kidney Disease Differential Diagnosis

Chronic Kidney Disease

(chronic renal failure; ckd).

• Pathophysiology |
• Symptoms and Signs |
• Diagnosis |
• Treatment |
• Prognosis |
• Key Points |

Chronic kidney disease (CKD) is long-standing, progressive deterioration of renal function. Symptoms develop slowly and in advanced stages include anorexia, nausea, vomiting, stomatitis, dysgeusia, nocturia, lassitude, fatigue, pruritus, decreased mental acuity, muscle twitches and cramps, water retention, undernutrition, peripheral neuropathies, and seizures. Diagnosis is based on laboratory testing of renal function, sometimes followed by renal biopsy. Treatment is primarily directed at the underlying condition but includes fluid and electrolyte management, blood pressure control, treatment of anemia, various types of dialysis, and kidney transplantation.

Prevalence of CKD (defined as estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73m 2  or urinary albumin to creatinine ratio [ACR] ≥ 30 mg/g) among adults in the United States from 2017 through March 2020 was estimated to be 14.0% ( 1 ).

General reference

1. United States Renal Data System (USRDS) : CKD in the general population. Accessed August 18, 2023.

Etiology of Chronic Kidney Disease

Chronic kidney disease may result from any cause of renal dysfunction of sufficient magnitude (see table Major Causes of Chronic Kidney Disease ).

The most common causes in the United States in order of prevalence are

Diabetic nephropathy

Hypertensive nephrosclerosis

Various primary and secondary glomerulopathies

Metabolic syndrome , in which hypertension and type 2 diabetes are present, is a large and growing cause of renal damage.

Major Causes of Chronic Kidney Disease

Pathophysiology of Chronic Kidney Disease

Chronic kidney disease (CKD) is initially described as diminished renal reserve or renal insufficiency, which may progress to renal failure (end-stage kidney disease). Initially, as renal tissue loses function, there are few noticeable abnormalities because the remaining tissue increases its performance (renal functional adaptation).

Decreased renal function interferes with the kidneys’ ability to maintain fluid and electrolyte homeostasis. The ability to concentrate urine declines early and is followed by decreases in ability to excrete excess phosphate, acid, and potassium. When renal failure is advanced (glomerular filtration rate [GFR] ≤ 15 mL/min/1.73 m 2 ), the ability to effectively dilute or concentrate urine is lost; thus, urine osmolality is usually fixed at about 300 to 320 mOsm/kg, close to that of plasma (275 to 295 mOsm/kg), and urinary volume does not respond readily to variations in water intake.

Creatinine and urea

Plasma concentrations of creatinine and urea (which are highly dependent on glomerular filtration) begin a hyperbolic rise as GFR diminishes. These changes are minimal early on. When the GFR falls below 15 mL/min/1.73 m 2 (normal > 90 mL/min/1.73 m 2 ), creatinine and urea levels are high and are usually associated with systemic manifestations (uremia). Urea and creatinine are not major contributors to the uremic symptoms; they are markers for many other substances (some not yet well-defined) that cause the symptoms.

Sodium and water

Despite a diminishing GFR, sodium and water balance is well-maintained by increased fractional excretion of sodium in urine and a normal response to thirst. Thus, the plasma sodium concentration is typically normal, and hypervolemia is infrequent unless dietary intake of sodium or water is very restricted or excessive. Heart failure can occur due to sodium and water overload, particularly in patients with decreased cardiac reserve.

For substances whose secretion is controlled mainly through distal nephron secretion (eg, potassium), renal adaptation usually maintains plasma levels at normal until renal failure is advanced or dietary potassium intake is excessive. Potassium-sparing diuretics , angiotensin-converting enzyme inhibitors , beta-blockers , nonsteroidal anti-inflammatory drugs may raise plasma potassium levels in patients with less advanced renal failure.

Calcium and phosphate

Abnormalities of calcium, phosphate, parathyroid hormone (PTH), and can occur, as can renal osteodystrophy. Decreased renal production of calcitriol (1,25(OH) 2 D, the active vitamin D hormone) contributes to hypocalcemia . Decreased renal excretion of phosphate results in hyperphosphatemia . Secondary hyperparathyroidism is common and can develop in renal failure before abnormalities in calcium or phosphate concentrations occur. For this reason, monitoring PTH in patients with moderate CKD, even before hyperphosphatemia occurs, has been recommended.

Renal osteodystrophy (abnormal bone mineralization resulting from hyperparathyroidism, calcitriol deficiency, elevated serum phosphate, or low or normal serum calcium) usually takes the form of increased bone turnover due to hyperparathyroid bone disease (osteitis fibrosa) but can also involve decreased bone turnover due to adynamic bone disease (with increased parathyroid suppression) or osteomalacia. Calcitriol deficiency may cause osteopenia or osteomalacia.

pH and bicarbonate

Moderate metabolic acidosis (plasma bicarbonate content 15 to 20 mmol/L) is characteristic. Acidosis causes muscle wasting due to protein catabolism, bone loss due to bone buffering of acid, and accelerated progression of kidney disease.

Anemia is characteristic of moderate to advanced CKD ( ≥ stage 3). The anemia of CKD is normochromic-normocytic, with a hematocrit of 20 to 30% (35 to 40% in patients with polycystic kidney disease ). It is usually caused by deficient erythropoietin production due to a reduction of functional renal mass (see page Anemias Caused by Deficient Erythropoiesis ). Other causes include deficiencies of iron , folate , and vitamin B12 .

Symptoms and Signs of Chronic Kidney Disease

Patients with mildly diminished renal reserve are asymptomatic. Even patients with mild to moderate renal insufficiency may have no symptoms despite elevated blood urea nitrogen (BUN) and creatinine. Nocturia is often noted, principally due to failure to concentrate the urine. Lassitude, fatigue, anorexia, and decreased mental acuity often are the earliest manifestations of uremia.

With more severe renal disease (eg, estimated glomerular filtration rate [eGFR] < 15 mL/min/1.73 m 2 ), neuromuscular symptoms may be present, including coarse muscular twitches, peripheral sensory and motor neuropathies , muscle cramps, hyperreflexia, restless legs syndrome , and seizures (usually the result of hypertensive or metabolic encephalopathy).

Anorexia, nausea, vomiting, weight loss, stomatitis, and an unpleasant taste in the mouth are almost uniformly present. The skin may be yellow-brown and/or dry. Occasionally, urea from sweat crystallizes on the skin (uremic frost). Pruritus may be especially uncomfortable. Undernutrition leading to generalized tissue wasting is a prominent feature of chronic uremia.

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In advanced CKD, pericarditis and gastrointestinal ulceration and bleeding may occur. Hypertension is present in > 80% of patients with advanced CKD and is usually related to hypervolemia. Heart failure caused by hypertension or coronary artery disease and renal retention of sodium and water may lead to dependent edema and/or dyspnea.

Diagnosis of Chronic Kidney Disease

Electrolytes, blood urea nitrogen (BUN), creatinine, phosphate, calcium, complete blood count (CBC)

Urinalysis (including urinary sediment examination)

Quantitative urine protein (24-hour urine protein collection or spot urine protein to creatinine ratio)

Ultrasonography

Sometimes renal biopsy

Chronic kidney disease (CKD) is usually first suspected when serum creatinine rises. The initial step is to determine whether the renal failure is acute, chronic, or acute superimposed on chronic (ie, an acute disease that further compromises renal function in a patient with CKD—see table Distinguishing Acute Kidney Injury From Chronic Kidney Disease ). The cause of renal failure is also determined. Sometimes determining the duration of renal failure helps determine the cause; sometimes it is easier to determine the cause than the duration, and determining the cause helps determine the duration.

Distinguishing Acute Kidney Injury From Chronic Kidney Disease

Testing includes urinalysis with examination of the urinary sediment, electrolytes, urea nitrogen, creatinine, phosphate, calcium, and CBC. Sometimes specific serologic tests are needed to determine the cause. Distinguishing acute kidney injury from CKD is most helped by a recent rapid rise in serum creatinine or abnormalities in the urinalysis. Urinalysis findings depend on the nature of the underlying disorder, but broad ( > 3 white blood cell diameters wide) or especially waxy (highly refractile) casts often are prominent in advanced renal failure of any cause.

An ultrasound examination of the kidneys is usually helpful in evaluating for obstructive uropathy and in distinguishing acute kidney injury from CKD based on kidney size. Except in certain conditions (see table Distinguishing Acute Kidney Injury From Chronic Kidney Disease ), patients with CKD have small shrunken kidneys (usually < 10 cm in length) with thinned, hyperechoic cortex. Obtaining a precise diagnosis becomes increasingly difficult as renal function reaches values close to those of end-stage kidney disease. The definitive diagnostic tool is renal biopsy , but it is not recommended when ultrasonography indicates small, fibrotic kidneys; high procedural risk outweighs low diagnostic yield.

Stages of chronic kidney disease

Staging CKD is a way of quantifying its severity. CKD has been classified into 5 stages.

Stage 1: Normal GFR ( ≥ 90 mL/min/1.73 m 2 ) plus either persistent albuminuria or known structural or hereditary renal disease

Stage 2: GFR 60 to 89 mL/min/1.73 m 2

Stage 3a: 45 to 59 mL/min/1.73 m 2

Stage 3b: 30 to 44 mL/min/1.73 m 2

Stage 4: GFR 15 to 29 mL/min/1.73 m 2

Stage 5: GFR < 15 mL/min/1.73 m 2

GFR (in mL/min/1.73 m 2 ) in CKD can be estimated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI 2021) creatinine equation :

Scr = standardized serum creatinine in mg/dL

κ = 0.7 (females) or 0.9 (males)

α = -0.241 (female) or -0.302 (male)

min(Scr/κ, 1) = minimum of Scr/κ or 1.0

max(Scr/κ, 1) = maximum of Scr/κ or 1.0

Age (years)

In contrast to prior versions, the most recent equation does not adjust for race, so as to reduce racial inequities in CKD diagnosis and thus treatment. Alternatively, GFR can be estimated using timed (most commonly 24-hour) urine creatinine clearance that includes measured serum and urine creatinine; this equation tends to overestimate GFR by 10 to 20%. It is used when serum creatinine assessment may not be as accurate (eg, in patients who are sedentary, very obese, or very thin). Serum cystatin C is an alternative endogenous GFR marker used as a confirmatory test in people with nonrenal factors affecting serum creatinine level (eg, extremely high or low muscle mass, exogenous creatine intake, amputations or neuromuscular diseases, and high protein or exclusively plant-based diets). GFR is calculated using CKD-EPI cystatin C equation .

The CKD-EPI 2021 formula is more accurate than the Modification of Diet in Renal Disease (MDRD) and Cockcroft-Gault formulas, particularly for patients with a GFR near normal values. The CKD-EPI equation yields fewer falsely positive results indicating chronic kidney disease and predicts outcome better than the other formulas.

Treatment of Chronic Kidney Disease

Control of underlying disorders

Possible restriction of dietary protein, phosphate, and potassium

Treatment of anemia

Treatment of contributing comorbidities (eg, heart failure, diabetes mellitus, nephrolithiasis, prostatic hypertrophy)

Doses of all medications adjusted as needed

Maintaining sodium bicarbonate level in the normal range (23–29 mmol/L)

Dialysis for severely decreased glomerular filtration rate (GFR) if symptoms and signs not adequately managed by medical interventions

Underlying disorders and contributory factors must be controlled. In particular, controlling hyperglycemia in patients with diabetic nephropathy and controlling hypertension in all patients substantially slows deterioration of GFR.

For hypertension , some guidelines suggest a target BP of < 140/90 mm Hg, the American Heart Association recommends 130/80, and some authors continue to recommend about 125 to 130/ < proteinuria more. Sodium-glucose cotransporter-2 (SGLT2) inhibitors delay progression of proteinuric CKD in patients with or without diabetes, although these medications are contraindicated in patients with type 1 diabetes mellitus ( 1, 2 ).

Activity need not be restricted, although fatigue and lassitude usually limit a patient’s capacity for exercise.

Pruritus may respond to dietary phosphate restriction and phosphate binders if serum phosphate is elevated.

Severe protein restriction in renal disease is controversial. However, moderate protein restriction (0.8 g/kg/day) among patients with estimated GFR (eGFR) < 60 mL/min/1.73 m 2 without nephrotic syndrome is safe and easy for most patients to tolerate. Some experts recommend 0.6 g/kg/day for patients with diabetes and for patients without diabetes if GFR is < 25 mL/min/1.73 m 2 . Many uremic symptoms markedly lessen when protein catabolism and urea generation are reduced. Also, rate of progression of CKD may slow down. Sufficient carbohydrate and fat are given to meet energy requirements and prevent ketosis. Patients for whom < 0.8 g/kg/day has been prescribed should be closely followed by a dietitian.

Because dietary restrictions may reduce necessary vitamin intake, patients should take a multivitamin containing water-soluble vitamins. Administration of vitamins A and E is unnecessary. Vitamins D2 (ergocalciferol) or D3 (cholecalciferol) are not given routinely but are used based on blood levels of vitamin D 25-OH and PTH.

Dyslipidemia rhabdomyolysis 3 ).

Mineral and bone disorders

Based on updated KDIGO (Kidney Disease Improving Global Outcomes) 2017 clinical practice guidelines ( 3

Hyperphosphatemia should be treated with

Dietary phosphate restriction

Phosphate binders

Phosphate restriction to 0.8 to 1 g/day of dietary intake is typically sufficient to normalize serum phosphate level in patients with eGFR < 60 mL/min/1.73 m 2 . Additional intestinal phosphate binders (calcium-containing or non–calcium-containing) may be necessary for adequate control of hyperphosphatemia, which has been associated with increased cardiovascular risk. Non–calcium-containing binders are preferred in patients with hypercalcemia , suspected adynamic bone disease, or evidence of vascular calcification on imaging. If calcium-containing binders are prescribed, then the total dietary and medication sources of calcium should not exceed 2000 mg/day in patients with eGFR < 60 mL/min/1.73 m 2 .

should be treated with cholecalciferol (vitamin D3) or ergocalciferol (vitamin D2) to target serum vitamin D 25-OH level approximately 30-50 ng/mL, as long as there is no hyperphosphatemia or hypercalcemia.

The optimal level of PTH in patients with CKD stages 3a to 5 not on dialysis is not known. However, if PTH levels are progressively rising or are markedly elevated (above 9 times the upper limit of normal for the assay), despite treatment of hyperphosphatemia and vitamin D

Fluid and electrolytes

Restricted water intake is required only when serum sodium concentration is < 135 mmol/L or there is heart failure or severe edema.

Sodium restriction of < 2 g/day is recommended for CKD patients with eGFR < 60 mL/m/1.73 m 2 who have hypertension , volume overload , or proteinuria .

Potassium restriction is individualized based on serum level, eGFR, dietary customs, and use of medications that increase potassium levels (eg, ACE, ARBs, or potassium-sparing diuretics). Typically, potassium restriction is not needed with eGFR > 30 mL/min/1.73 m 2 . Treatment of mild to moderate hyperkalemia (5.1 to 6 mmol/L) entails dietary restriction (including avoiding salt substitutes), correction of metabolic acidosis, and use of potassium-lowering diuretics and gastrointestinal cation exchangers. Severe hyperkalemia ( > 6 mmol/L) warrants urgent treatment .

Metabolic acidosis

Anemia and coagulation disorders

Anemia is a common complication of moderate to advanced CKD ( ≥ stage 3) and, when < stroke , thrombosis , and death, the lowest dose of these agents needed to keep the Hb between 10 and 11 g/dL is used.

Because of increased iron utilization with stimulated erythropoiesis, iron stores must be replaced, often requiring parenteral iron. Iron concentrations, iron-binding capacity, and ferritin concentrations should be followed closely. Target transferrin saturation (TSAT), calculated by dividing serum iron by total iron binding capacity and multiplying by 100%, should be > 20%. Target ferritin in patients not on dialysis is > 100 ng/mL. Transfusion should not be done unless anemia is severe (Hb < 8 g/dL) or causes symptoms.

Heart failure

Symptomatic heart failure is treated with

Sodium restriction

Sometimes, dialysis

ACE inhibitors (or ARBs ) and beta-blockers

Moderate or severe hypertension

Occasionally, dialysis may be required to control heart failure. If reduction of the volume of extracellular fluid does not control blood pressure, conventional antihypertensives are added. Azotemia may increase with such treatment and may be necessary for adequate control of heart failure and/or hypertension.

Medications

Hemodialysis reduces the serum concentrations of some medications, which should be supplemented after hemodialysis. It is strongly recommended that physicians consult a reference on drug dosing in renal failure before prescribing medications to these very vulnerable patients ( 4, 5, 6 ).

Most experts recommend avoiding NSAIDs (nonsteroidal anti-inflammatory drugs) in patients with CKD because they may worsen renal function, exacerbate hypertension, and precipitate electrolyte disturbances.

Certain medications should be avoided entirely in patients with chronic kidney disease with eGFR < 60 mL/min/1.73m 2 nephrogenic systemic fibrosis in patients with estimated GFR < 30 mL/min/1.73m 2 in the past. More recently, class II gadolinium agents are considered safer and preferred when gadolinium is indicated for patients with eGFR < 30 or on dialysis ( 7 ).

Dialysis is usually initiated at the onset of either of the following:

Uremic symptoms (eg, anorexia, nausea, vomiting, weight loss, pericarditis, pleuritis)

Difficulty controlling fluid overload, hyperkalemia, or acidosis with medications and lifestyle interventions

These problems typically occur when the estimated GFR reaches ≤ 10 mL/min in a patient without diabetes or ≤ 15 mL/min in a patient with diabetes; patients whose estimated GFR values are near these values should be closely monitored so that these signs and symptoms are recognized early. Dialysis is best anticipated so that preparations can be made and urgent insertion of a hemodialysis catheter can be avoided. Such preparations usually begin when the patient is in early to mid stage 4 CKD; preparation allows time for patient education, selection of the type of dialysis, and timely creation of an arteriovenous fistula or placement of a peritoneal dialysis catheter . (For dialysis preparation, see Hemodialysis .)

Pearls & Pitfalls

Transplantation

If a living kidney donor is available, better long-term outcomes occur when a patient receives the transplanted kidney early, even before beginning dialysis. Patients who are transplant candidates but have no living donor should be placed on the waiting list of their regional transplant center early because wait times may exceed several years in many regions of the United States.

Treatment references

1. Perkovic V, Jardine MJ, Neal B, et al N Engl J Med  380(24):2295-2306, 2019. doi: 10.1056/NEJMoa1811744

2. Heerspink HJL, Stefánsson BV,  Correa-Rotter R, et al N Engl J Med  383(15):1436-1446, 2020. doi: 10.1056/NEJMoa2024816

3. KDIGO 2017 Clinical Practice Guidelines for the Diagnosis, Evaluation, Prevention, and Treatment of Chronic Kidney Disease–Mineral and Bone Disorder (CKD-MBD) Kidney Int Suppl 7(1):1-59, 2017.

4. Determining Drug Dosing in Adults with Chronic Kidney Disease.

5. Munar MY, Singh HD : Drug dosing adjustments in patients with chronic kidney disease. Am Fam Physician 75:1487-1496, 2007.

6. Matzke GR, Aronoff GR, Atkinson AJ, et al : Drug dosing consideration in patients with acute and chronic kidney disease—a clinical update from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int 80:1122–1137, 2011. doi:10.1038/ki.2011.322

7. ACR Committee on Drugs and Contrast Media : ACR Manual on Contrast Media. American College of Radiology. 2021. ISBN: 978-1-55903-012-0

Prognosis for Chronic Kidney Disease

Progression of chronic kidney disease (CKD) is predicted in most cases by the degree of proteinuria. (See the Kidney Failure Risk Equation .) Patients with nephrotic-range proteinuria ( > 3 g/24 h or urine protein/creatinine ratio > 3) usually have a poorer prognosis and progress to renal failure more rapidly. Progression may occur even if the underlying disorder is not active. In patients with urine protein < 1.5 g/24 h, progression usually occurs more slowly if at all. Hypertension , acidosis , and hyperparathyroidism are associated with more rapid progression as well.

Common causes of chronic kidney disease (CKD) in the United States are diabetic nephropathy (the most common), hypertensive nephrosclerosis, glomerulopathies, and metabolic syndrome.

Effects of CKD can include hypocalcemia, hyperphosphatemia, metabolic acidosis, anemia, secondary hyperparathyroidism, and renal osteodystrophy.

Distinguish CKD from acute kidney injury based on history, clinical findings, routine laboratory tests, and ultrasonography.

Control underlying disorders (eg, diabetes) and BP levels (usually with an ACE inhibitor or ARB).

Treat patients with proteinuric CKD with an ACE inhibitor or ARB, plus an SGLT2 inhibitor.

Treat heart failure, anemia, and other complications.

Educate patients with advanced CKD on treatment options (dialysis, kidney transplantation, or palliative care) early, to allow adequate time for planning.

Initiate dialysis for patients with severely decreased eGFR when signs and symptoms are inadequately controlled with medications and lifestyle interventions.

• Patient Care & Health Information
• Diseases & Conditions
• Chronic kidney disease
• What is kidney disease? An expert explains

Learn more from kidney doctor Andrew Bentall, M.D.

I'm Dr. Andrew Bentall, a kidney doctor at Mayo Clinic. I look after patients with kidney disease, either in the early stages, or with more advanced kidney disease considering dialysis and transplantation as treatment options. In this video, we'll cover the basics of chronic kidney disease. What is it? Who gets it? The symptoms, diagnosis and treatment. Whether you are looking for answers for yourself or for someone you love, we're here to give you the best information available.

Chronic kidney disease is a disease characterized by progressive damage and loss of function in the kidneys. It's estimated that chronic kidney disease affects about one in seven American adults. And most of those don't know they have it. Before we get into the disease itself, let's talk a little bit about the kidneys and what they do. Our kidneys play many important roles keeping our bodies in balance. They remove waste and toxins, excess water from the bloodstream, which is carried out of the body in urine. They helped to make hormones to produce red blood cells, and they turn vitamin D into its active form, so it's usable in the body.

There are quite a few things that can cause or put you at higher risk for chronic kidney disease. Some of them are not things that can be avoided. Your risk is simply higher if you have a family history of certain genetic conditions like polycystic kidney disease or some autoimmune diseases like lupus or IgA nephropathy. Defects in the kidney structure can also cause your kidneys to fail, and you have an increased risk as you get older. Sometimes, other common medical conditions can increase your risk. Diabetes is the most common cause of kidney disease. Both type 1 and type 2 diabetes. But also heart disease and obesity can contribute to the damage that causes kidneys to fail. Urinary tract issues and inflammation in different parts of the kidney can also lead to long-term functional decline. There are things that are more under our control: Heavy or long-term use of certain medications, even those that are common over-the-counter. Smoking can also be a contributing factor to chronic kidney disease.

Often there are no outward signs in the earlier stages of chronic kidney disease, which is grouped into stages 1 through 5. Generally, earlier stages are known as 1 to 3. And as kidney disease progresses, you may notice the following symptoms. Nausea and vomiting, muscle cramps, loss of appetite, swelling via feet and ankles, dry, itchy skin, shortness of breath, trouble sleeping, urinating either too much or too little. However, these are usually in the later stages, but they can also happen in other disorders. So don't automatically interpret this as having kidney disease. But if you're experiencing anything that concerns you, you should make an appointment with your doctor.

Even before any symptoms appear, routine blood work can indicate that you might be in the early stages of chronic kidney disease. And the earlier it's detected, the easier it is to treat. This is why regular checkups with your doctor are important. If your doctor suspects the onset of chronic kidney disease, they may schedule a variety of other tests. They may also refer you to a kidney specialist, a nephrologist like myself. Urine tests can reveal abnormalities and give clues to the underlying cause of the chronic kidney disease. And this can also help to determine the underlying issues. Various imaging tests like ultrasounds or CT scans can be done to help your doctor assess the size, the structure, as well as evaluate the visible damage, inflammation or stones of your kidneys. And in some cases, a kidney biopsy may be necessary. And a small amount of tissue is taken with a needle and sent to the pathologist for further analysis.

Treatment is determined by what is causing your kidneys to not function normally. Treating the cause is key, leading to reduced complications and slowing progression of kidney disease. For example, getting better blood pressure control, improved sugar control and diabetes, and reducing weight are often key interventions. However, existing damage is not usually reversible. In some conditions, treatment can reverse the cause of the disease. So seeking medical review is really important. Individual complications vary, but treatment might include high blood pressure medication, diuretics to reduce fluid and swelling, supplements to relieve anemia, statins to lower cholesterol, or medications to protect your bones and prevent blood vessel calcification. A lower-protein diet may also be recommended. It reduces the amount of waste your kidneys need to filter from your blood. These can not only slow the damage of kidney disease, but make you feel better as well. When the damage has progressed to the point that 85 to 90 percent of your kidney function is gone, and they no longer work well enough to keep you alive, it's called end-stage kidney failure. But there are still options. There's dialysis, which uses a machine to filter the toxins and remove water from your body as your kidneys are no longer able to do this. Where possible, the preferred therapy is a kidney transplant. While an organ transplant can sound daunting, it's actually often the better alternative, and the closest thing to a cure, if you qualify for a kidney transplant.

If you have kidney disease, there are lifestyle choices. Namely quit smoking. Consuming alcohol in moderation. If you're overweight or obese, then try to lose weight. Staying active and getting exercise can help not only with your weight, but fatigue and stress. If your condition allows, keep up with your routine, whether that's working, hobbies, social activities, or other things you enjoy. It can be helpful to talk to someone you trust, a friend or relative who's good at listening. Or your doctor could also refer you to a therapist or social worker. It can also be helpful to find a support group and connect with people going through the same thing. Learning you have chronic kidney disease and learning how to live with it can be a challenge. But there are lots of ways to help you to be more comfortable for longer before more drastic measures are needed. And even then, there is plenty of hope. If you'd like to learn even more about chronic kidney disease, watch our other related videos or visit mayoclinic.org. We wish you well.

Chronic kidney disease, also called chronic kidney failure, involves a gradual loss of kidney function. Your kidneys filter wastes and excess fluids from your blood, which are then removed in your urine. Advanced chronic kidney disease can cause dangerous levels of fluid, electrolytes and wastes to build up in your body.

In the early stages of chronic kidney disease, you might have few signs or symptoms. You might not realize that you have kidney disease until the condition is advanced.

Treatment for chronic kidney disease focuses on slowing the progression of kidney damage, usually by controlling the cause. But, even controlling the cause might not keep kidney damage from progressing. Chronic kidney disease can progress to end-stage kidney failure, which is fatal without artificial filtering (dialysis) or a kidney transplant.

• How kidneys work

One of the important jobs of the kidneys is to clean the blood. As blood moves through the body, it picks up extra fluid, chemicals and waste. The kidneys separate this material from the blood. It's carried out of the body in urine. If the kidneys are unable to do this and the condition is untreated, serious health problems result, with eventual loss of life.

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Signs and symptoms of chronic kidney disease develop over time if kidney damage progresses slowly. Loss of kidney function can cause a buildup of fluid or body waste or electrolyte problems. Depending on how severe it is, loss of kidney function can cause:

• Loss of appetite
• Fatigue and weakness
• Sleep problems
• Urinating more or less
• Decreased mental sharpness
• Muscle cramps
• Swelling of feet and ankles
• Dry, itchy skin
• High blood pressure (hypertension) that's difficult to control
• Shortness of breath, if fluid builds up in the lungs
• Chest pain, if fluid builds up around the lining of the heart

Signs and symptoms of kidney disease are often nonspecific. This means they can also be caused by other illnesses. Because your kidneys are able to make up for lost function, you might not develop signs and symptoms until irreversible damage has occurred.

When to see a doctor

Make an appointment with your doctor if you have signs or symptoms of kidney disease. Early detection might help prevent kidney disease from progressing to kidney failure.

If you have a medical condition that increases your risk of kidney disease, your doctor may monitor your blood pressure and kidney function with urine and blood tests during office visits. Ask your doctor whether these tests are necessary for you.

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• Healthy kidney vs. diseased kidney

A typical kidney has about 1 million filtering units. Each unit, called a glomerulus, joins a tubule. The tubule collects urine. Conditions such as high blood pressure and diabetes harm kidney function by damaging these filtering units and tubules. The damage causes scarring.

• Polycystic kidney

A healthy kidney (left) removes waste from the blood and maintains the body's chemical balance. With polycystic kidney disease (right), fluid-filled sacs called cysts develop in the kidneys. The kidneys grow larger and slowly lose their ability to work as they should.

Chronic kidney disease occurs when a disease or condition impairs kidney function, causing kidney damage to worsen over several months or years.

Diseases and conditions that cause chronic kidney disease include:

• Type 1 or type 2 diabetes
• High blood pressure
• Glomerulonephritis (gloe-mer-u-low-nuh-FRY-tis), an inflammation of the kidney's filtering units (glomeruli)
• Interstitial nephritis (in-tur-STISH-ul nuh-FRY-tis), an inflammation of the kidney's tubules and surrounding structures
• Polycystic kidney disease or other inherited kidney diseases
• Prolonged obstruction of the urinary tract, from conditions such as enlarged prostate, kidney stones and some cancers
• Vesicoureteral (ves-ih-koe-yoo-REE-tur-ul) reflux, a condition that causes urine to back up into your kidneys
• Recurrent kidney infection, also called pyelonephritis (pie-uh-low-nuh-FRY-tis)

Risk factors

Factors that can increase your risk of chronic kidney disease include:

• Heart (cardiovascular) disease
• Being Black, Native American or Asian American
• Family history of kidney disease
• Abnormal kidney structure
• Frequent use of medications that can damage the kidneys

Complications

Chronic kidney disease can affect almost every part of your body. Potential complications include:

• Fluid retention, which could lead to swelling in your arms and legs, high blood pressure, or fluid in your lungs (pulmonary edema)
• A sudden rise in potassium levels in your blood (hyperkalemia), which could impair your heart's function and can be life-threatening
• Heart disease
• Weak bones and an increased risk of bone fractures
• Decreased sex drive, erectile dysfunction or reduced fertility
• Damage to your central nervous system, which can cause difficulty concentrating, personality changes or seizures
• Decreased immune response, which makes you more vulnerable to infection
• Pericarditis, an inflammation of the saclike membrane that envelops your heart (pericardium)
• Pregnancy complications that carry risks for the mother and the developing fetus
• Irreversible damage to your kidneys (end-stage kidney disease), eventually requiring either dialysis or a kidney transplant for survival

To reduce your risk of developing kidney disease:

• Follow instructions on over-the-counter medications. When using nonprescription pain relievers, such as aspirin, ibuprofen (Advil, Motrin IB, others) and acetaminophen (Tylenol, others), follow the instructions on the package. Taking too many pain relievers for a long time could lead to kidney damage.
• Maintain a healthy weight. If you're at a healthy weight, maintain it by being physically active most days of the week. If you need to lose weight, talk with your doctor about strategies for healthy weight loss.
• Don't smoke. Cigarette smoking can damage your kidneys and make existing kidney damage worse. If you're a smoker, talk to your doctor about strategies for quitting. Support groups, counseling and medications can all help you to stop.
• Manage your medical conditions with your doctor's help. If you have diseases or conditions that increase your risk of kidney disease, work with your doctor to control them. Ask your doctor about tests to look for signs of kidney damage.

Chronic kidney disease care at Mayo Clinic

• Goldman L, et al., eds. Chronic kidney disease. In: Goldman-Cecil Medicine. 26th ed. Elsevier; 2020. http://www.clinicalkey.com. Accessed April 27, 2021.
• Chronic kidney disease (CKD). National Institute of Diabetes and Digestive and Kidney Diseases. https://www.niddk.nih.gov/health-information/kidney-disease/chronic-kidney-disease-ckd#:~:text=Chronic kidney disease (CKD) means,family history of kidney failure. Accessed April 26, 2021.
• Rosenberg M. Overview of the management of chronic kidney disease in adults. https://www.uptodate.com/contents/search. Accessed April 26, 2021.
• Chronic kidney disease (CKD) symptoms and causes. National Kidney Foundation. https://www.kidney.org/atoz/content/about-chronic-kidney-disease. Accessed April 26, 2021.
• Chronic kidney disease. Merck Manual Professional Version. https://www.merckmanuals.com/professional/genitourinary-disorders/chronic-kidney-disease/chronic-kidney-disease?query=Chronic kidney disease. Accessed April 26, 2021.
• Ammirati AL. Chronic kidney disease. Revista da Associação Médica Brasileira. 2020; doi:10.1590/1806-9282.66.S1.3.
• Chronic kidney disease basics. Centers for Disease Control and Prevention. https://www.cdc.gov/kidneydisease/basics.html. Accessed April 26, 2021.
• Warner KJ. Allscripts EPSi. Mayo Clinic; April 21, 2021.
• Office of Patient Education. Chronic kidney disease treatment options. Mayo Clinic; 2020.
• Chronic kidney disease: Is a clinical trial right for me?
• Eating right for chronic kidney disease
• Effectively managing chronic kidney disease
• Kidney biopsy
• Kidney disease FAQs
• Low-phosphorus diet: Helpful for kidney disease?
• MRI: Is gadolinium safe for people with kidney problems?
• Renal diet for vegetarians

Associated Procedures

• Deceased-donor kidney transplant
• Hemodialysis
• Kidney transplant
• Living-donor kidney transplant
• Nondirected living donor
• Peritoneal dialysis
• Preemptive kidney transplant

News from Mayo Clinic

• Mayo Clinic Q and A: Diagnosed with chronic kidney disease. Now what? Aug. 31, 2024, 11:00 a.m. CDT
• Mayo Clinic Minute: Why Black Americans are at higher risk of chronic kidney disease March 05, 2024, 05:00 p.m. CDT
• Mayo Clinic Minute: Can extra salt hurt your kidneys? Feb. 16, 2024, 04:00 p.m. CDT
• Mayo Clinic Minute: Using AI to predict kidney failure in patients with polycystic kidney disease April 06, 2023, 04:00 p.m. CDT
• Mayo Clinic Q and A: Understanding chronic kidney disease March 23, 2023, 12:35 p.m. CDT
• Mayo Clinic Minute: Game-changing treatment for chronic kidney disease could slow down progression of the disease March 06, 2023, 04:01 p.m. CDT
• Science Saturday: Seeking a cellular therapy for chronic kidney disease Nov. 12, 2022, 12:00 p.m. CDT
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• Kidney Disease for Health Professionals
• Identify & Manage Patients with CKD
• Identify & Evaluate Patients with CKD

Identify & Evaluate Patients with Chronic Kidney Disease

Urine and blood tests are used to detect and monitor kidney disease. Currently, the key markers used include abnormal urine albumin levels and a persistent reduction in the estimated glomerular filtration rate (eGFR) . Identification of the etiology may help guide management. Diabetes and hypertension are the leading causes of CKD in adults. Many diseases that cause kidney failure may have their origins in childhood . Early detection and appropriate treatment may improve prognosis in all age groups.

Identify Patients with CKD

Screen people at risk for CKD, including those with

• diabetes mellitus type 1 or type 2
• hypertension
• cardiovascular disease (CVD)
• family history of kidney failure

The benefit of CKD screening in the general population is unclear.

The two key markers for CKD are urine albumin and eGFR. To screen for CKD:

• assess urine albumin excretion to diagnose and monitor kidney damage . Screen using a spot urine albumin-to-creatinine ratio.
• calculate eGFR from stable serum creatinine levels to assess kidney function . Use the Modification of Diet in Renal Disease (MDRD) Study Equation or the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation.

CKD is generally diagnosed when there is evidence, for more than 3 months, of

• kidney damage (usually urine albumin > 30 mg/g creatinine, but includes other clinical findings such as hematuria, congenital malformations, etc.) and/or
• decreased kidney function (eGFR < 60 mL/min/1.73 m 2 )

Staging systems for chronic disease should identify risk for progression and complications. The current staging system for CKD, based exclusively on eGFR, does not appear to reliably identify those people at greatest risk for progression. Emerging research suggests an approach that includes multiple factors, such as urine albumin, age, and diabetes status may better predict progression.

In addition, the current staging requires accuracy of eGFR above 60 mL/min/1.73 m 2 . However, values above 60 calculated using the MDRD Study equation are not accurate. When using the MDRD Study equation, NIDDK encourages laboratories to report eGFR above 60 as age "≥ 60" rather than as numerical values. While the CKD-EPI equation has increased accuracy for eGFR values above 60 mL/min/1.73 m 2 compared to the MDRD Study equation, the influence of imprecision of creatinine assays on the uncertainty of an eGFR value is greater at higher eGFR values.

Although kidney function tends to decrease with age, this process has not been well investigated. Many people with age-related kidney function decline may not progress to kidney failure. Thus, the prognosis for a 75-year-old patient with an eGFR of 55 may be different than that for a 45-year-old patient with the same eGFR.

In addition, GFR may be too narrow a basis on which to assess risk for progression. The approach to staging is likely to evolve as it is informed by ongoing longitudinal research, e.g., the Chronic Renal Insufficiency Cohort Study .

Establish Cause of CKD

Because kidney damage is generally irreversible, it is important to identify the etiology as early as possible. Specific treatments are available in many cases (e.g., membraneous nephropathy, lupus nephropathy) and a diagnosis will guide management.

Although diabetes is the most common cause of CKD, it is important not to assume that a patient with diabetes and CKD has diabetic kidney disease. However, non-diabetic kidney disease is unlikely in a person with diabetes of long duration with other diabetic complications, physical findings of end-organ diabetic damage, and negative screening laboratory studies.

Suggested initial evaluation:

• complete urinalysis (U/A)
• urine albumin-to-creatinine ratio (UACR)
• creatinine with estimated GFR, blood urea nitrogen (BUN), electrolytes, glucose, calcium, phosphorus, albumin
• complete blood count (CBC)

For further evaluation, the following tests are often ordered, depending on clinical presentation:

• hepatitis B serology
• hepatitis C serology
• antinuclear antibody test (ANA)
• rheumatoid factor (RF)
• complement 3 (C3)
• complement 4 (C4)
• serum protein electrophoresis (SPEP) and urine protein electrophoresis (UPEP) (in patients over the age of 40)
• renal ultrasound to measure kidney size and to check for echogenicity and hydronephrosis
• dilated retinal exam

If a patient with diabetes has retinopathy, albuminuria, and negative screening tests listed above, it is reasonable to assume the diagnosis is diabetic kidney disease. Patients who do not conform to these criteria should be discussed with a nephrologist .

Collaborate with the Health Care Team

Patients with CKD and other chronic illnesses benefit from interdisciplinary care. A cohesive, interdisciplinary care approach that begins in the primary care setting and includes referrals to appropriate health care professionals—including nephrologists, registered dietitians , and mental health professionals—is essential to CKD patients’ overall health. They also play an important role in improved patient outcomes.

Nephrologist

Due to the complex nature of CKD, a referral to a nephrologist is often beneficial to the patient. Consult with a nephrologist to

• assist with a diagnostic challenge (e.g., decision to biopsy)
• assist with a therapeutic challenge (e.g., blood pressure, anemia, hyperphosphatemia, secondary hyperparathyroidism, hyperkalemia, metabolic acidosis)
• assess rapid decrease of eGFR
• treat most primary kidney diseases (e.g., glomerulonephritis)
• prepare for RRT, especially when eGFR < 30 mL/min/1.73 m2

Use the NIDDK Nephrology Referral Form (PDF, 746 KB) to share important patient data with the consulting nephrologist.

explain to patients how what they eat and drink affects their health

• work with patients to create eating plans with the right foods and nutrients in the right amounts
• suggest adjustments to the amount and types of food CKD patients consume as their kidney disease progresses
• identify possible nutritional deficiencies caused by kidney disease
• advise patients on regulating fluid intake

To find an RD who specializes in kidney disease, visit the Academy of Nutrition and Dietetics. Use the NIDDK CKD Diet Counseling (MNT) Referral Form (PDF, 452 KB) to share important patient data with the consulting dietitian.

Mental Health Professional

Depression is common in any chronic disease, including CKD. A mental health professional, such as a psychologist, can help patients find healthy ways to cope with the anxiety and stress of having CKD.

Community Resources

Community support programs are a valuable resource to help patients overcome barriers to managing their kidney disease, such as lack of access to transportation, childcare, medicines, and healthy food. A social worker can help locate services such as transportation and counseling, recommend support groups, and help submit applications for Medicare and Medicaid.

Additional Links

• Quick Reference on UACR and GFR (PDF, 150.98 KB)
• Making Sense of CKD—A Concise Guide for Managing Chronic Kidney Disease in the Primary Care Setting (PDF, 3.66 MB)
• NIDDK’s Diabetes Discoveries and Practice Blog for health care professionals

ANDREW J. GOODBRED, MD, AND ROBERT C. LANGAN, MD

Am Fam Physician. 2023;108(6):554-561

Author disclosure: No relevant financial relationships.

Chronic kidney disease (CKD) affects approximately 15% of the U.S. population, and many people are unaware of their diagnosis. Screening may be considered for patients with cardiovascular disease, diabetes mellitus, hypertension, age 60 years and older, family history of kidney disease, previous acute kidney injury, or preeclampsia. Diagnosis and staging of CKD are based on estimated glomerular filtration rate (eGFR), excessive urinary albumin excretion, or evidence of kidney parenchymal damage lasting more than three months. eGFR should be determined using the CKD-EPI creatinine equation without the race variable. Risk calculators are available to estimate the risk of progression to end-stage renal disease. When possible, serum cystatin C should be measured to confirm eGFR in patients with CKD. Blood pressure should be maintained at less than 140/90 mm Hg, with a systolic blood pressure target of 120 mm Hg or less for patients tolerant of therapy, using an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker. Sodium-glucose cotransporter-2 inhibitors and metformin should be considered in patients with CKD and type 2 diabetes who have not reached their glycemic goal. Intravenous iodinated contrast media temporarily reduces eGFR and should be avoided in patients with advanced CKD. Interdisciplinary management of patients with CKD is important for reducing morbidity and mortality, and patients at high risk of progression to end-stage renal disease should be referred to a nephrologist.

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Chronic Kidney Disease (CKD)

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• Chronic kidney disease : abnormal kidney function/structure >3 months, affects 9-13% of adults worldwide.
• Causes : diabetes, vascular disease, glomerular disease (e.g. IgA nephropathy), nephrotoxic drugs (e.g aminoglycosides, NSAIDs), obstructive uropathy, multisystem diseases (e.g. lupus, vasculitis), hereditary kidney disease (e.g. polycystic kidney disease).
• Risk factors : age >50, history of AKI, history of childhood kidney disease, diabetes, cardiovascular disease, obesity, smoking, male gender, black/Hispanic ethnicity, gout.
• Symptoms : often asymptomatic; in advanced stages, fatigue, nausea, polyuria, fluid overload (dyspnoea, orthopnoea), sexual dysfunction.
• Clinical findings : uraemic fetor, pallor, cachexia, cognitive impairment, tachypnoea, hypertension, volume disturbance, peripheral neuropathy, microvascular damage.
• Investigations : BP, urinalysis, plasma glucose, ECG, FBC, U&Es, serum albumin, urinary albumin, serum calcium, phosphate, PTH, alkaline phosphatase, cholesterol and triglycerides, imaging (renal ultrasound, CT/MRI).
• Management : exercise, weight loss, smoking cessation, glycaemic control, BP control (ACE inhibitors/ARBs), immunisations (influenza and pneumococcus), avoid nephrotoxic medication, dietary phosphate restriction, phosphate binders, 1-alpha-hydroxycholecalciferol for hyperparathyroidism and addressing cardiovascular risk factors.
• Renal replacement therapy : dialysis (haemodialysis or peritoneal dialysis), kidney transplantation, conservative management for some patients. Generally patients begin dialysis when GFR reaches approx. 5-10 mL/min/1.73m.
• Complications : metabolic acidosis, pulmonary oedema, anaemia, uraemic encephalopathy, cardiovascular disease, hyperkalaemia, CKD-mineral bone disorder.

Introduction

Chronic kidney disease (CKD) is defined as abnormal kidney function or structure present for greater than three months , with subsequent implications for health. 1

CKD is a common condition estimated to affect about nine to thirteen per cent of the adult population worldwide. 2

Causes of CKD

The most common causes of CKD in adults are diabetes  and vascular disease . 3

Other causes of CKD include: 3

• Glomerular disease : such as IgA nephropathy, membranous nephropathy, focal segmental glomerulosclerosis
• Nephrotoxic drugs : aminoglycosides, bisphosphonates, calcineurin inhibitors (such as ciclosporin or tacrolimus), lithium, proton pump inhibitors, mesalazine and NSAIDs
• Obstructive uropathy or reflux nephropathy : structural renal tract disease, neurogenic bladder, benign prostatic hypertrophy, urinary diversion surgery, recurrent urinary tract calculi, or pathology outside the urinary tract such as malignancy or retroperitoneal fibrosis
• Multisystem diseases with renal involvement : systemic lupus erythematosus , vasculitis, myeloma , hepatitis B, hepatitis C, HIV
• Hereditary kidney disease : polycystic kidney disease, Alport syndrome

Pathophysiology 4

Chronic kidney disease is the end-stage for any cause of severe and/or long-standing kidney injury. Regardless of the cause, once half the nephrons are damaged CKD will progress. 

Damage to the kidneys reduces the number of functioning nephrons , which leads to several adaptations. There is hyperfiltration at the glomeruli, and the increased glomerular permeability contributes to the development of proteinuria .

Another adaptation is the activation of the renin-angiotensin-aldosterone system causing an increase in blood pressure, which furthers the hyperfiltration at the glomerular level. Other adaptations include the release of cytokines and growth factors. 

The increase in capillary pressure within the glomerulus and inflammatory mediators cause chronic inflammation . This reduces the filtration ability of the glomerulus, which manifests as a reduced glomerular filtration rate (eGFR). This can lead to systemic complications , which are discussed later in this article.

Classification of CKD

CKD is classified by  eGFR and amount of proteinuria . The prognosis of CKD is colour-coded as shown in Figure 1. Green represents “low risk”, yellow represents “moderate risk”, orange represents “high risk” and red represents “very high risk”. 

Risk factors

Risk factors for chronic kidney disease include:

• Age greater than 50 years
• History of acute kidney injury
• History of childhood kidney disease
• Family history of CKD stage 5
• Diabetes mellitus
• Cardiovascular disease
• Obesity with metabolic syndrome
• Solitary functioning kidney
• Black or Hispanic ethnicity
• Male gender

Clinical features

CKD is primarily asymptomatic , and symptoms usually only start developing when it is advanced (stages 4-5). 3

CKD is usually detected through the presence of hypertension, haematuria and/or proteinuria upon urinalysis, or a reduction in GFR with increased serum creatinine . 6

In advanced CKD, typical symptoms may include: 3,6

• General symptoms: such as fatigue, nausea and vomiting, cramps, insomnia, restless legs, taste disturbance, bone pain, and pruritus
• Abnormal urine output: such as polyuria, oliguria, or nocturia
• Fluid overload: may present as dyspnoea and orthopnoea
• Sexual dysfunction
• Severe uraemia may also cause hiccups, pericarditis, coma and seizures

Clinical examination

Typical clinical findings in CKD may include: 3,6

• Uraemic fetor: ammonia-like smell of the breath
• Pallor: due to anaemia
• Cognitive impairment: specifically affecting language, orientation and attention
• Tachypnoea: may be due to fluid overload, anaemia
• Hypertension
• Volume disturbance: volume overload (e.g. peripheral oedema, pulmonary oedema, pleural effusions, ascites) or volume depletion
• Peripheral neuropathy
• Fundoscopy may reveal microvascular damage in patients with diabetes or hypertension

There may be specific clinical findings depending on the underlying cause of CKD:

• Bilateral masses upon palpation of flanks, suggestive of adult polycystic kidney disease. May be accompanied by hepatomegaly due to liver cysts.
• Palpable bladder: may suggest obstructive uropathy, often accompanied by prostatic enlargement in men

Differential diagnoses

Differential diagnoses to consider in the context of suspected CKD include:

• Acute kidney injury : the presence of chronic symptoms of fatigue, weight loss, anorexia, nocturia and pruritus suggest a diagnosis of CKD over AKI
• Acute on chronic kidney disease : where patients with features of CKD experience an acute further deterioration in their renal function, often following a precipitant such as infection or diarrhoea

Investigations

Bedside investigations.

Relevant bedside investigations include: 3

• Blood pressure : hypertension is common in patients with CKD
• Urinalysis : may reveal haematuria and/or proteinuria, particularly in glomerular disease
• Plasma glucose : to detect undiagnosed diabetes or assess control of diabetes
• ECG : particularly to assess for evidence of left ventricular hypertrophy or ischaemia

Laboratory investigations

Relevant laboratory investigations include: 3,7

• Full blood count : may reveal normochromic normocytic anaemia due to erythropoietin deficiency or functional iron deficiency
• Urea and electrolytes : reveal an elevated serum creatinine and reduced eGFR; electrolyte abnormalities may also be present (e.g. raised potassium, low bicarbonate)
• Serum albumin : hypoalbuminaemia in patients who are nephrotic and/or malnourished
• Urinary albumin (albumin to creatinine ratio): may be increased
• Serum calcium : may be low, normal, or high
• Serum phosphate : often elevated
• Serum PTH : rises as GFR falls ( secondary and tertiary hyperparathyroidism )
• Serum alkaline phosphatase : may be raised when in the presence of hyperparathyroidism
• Cholesterol and triglycerides : hyperlipidaemia is common

Other specific laboratory investigations may be required depending on the suspected cause of CKD:

• Serum protein electrophoresis and free light chain measurement : for evidence of a monoclonal gammopathy such as multiple myeloma, primary amyloidosis
• Serology : autoantibodies such as ANCA (anti-neutrophil cytoplasmic antibodies, specifically proteinase 3 or myeloperoxidase) anti-nuclear antibodies (ANA) and serum complement (C3 and C4) when secondary glomerular disease is suspected
• Hepatitis B and C and HIV serology : if suspected as a cause of CKD or if a patient requires dialysis

Relevant imaging investigations include: 3

• Plain abdominal radiograph : may reveal radio-opaque stones or nephrocalcinosis
• Renal ultrasound : may reveal structural abnormalities (e.g. polycystic kidneys), hydronephrosis, infiltrative disease, loss of cortex, increased echogenicity, and reduction in kidney size (advanced CKD often leads to small, echogenic kidneys)
• CT or MRI scan : may be used to define renal masses and cysts or for further evaluation if obstructive uropathy suspected

A diagnosis of CKD requires evidence of kidney damage and/or a persistent reduction in renal function .

CKD stages 3 – 5 can be diagnosed based on GFR alone (<60 mL/min/1.73m 2 ).

CKD stages 1 – 2 require additional evidence of renal disease such as: 2

• Proteinuria
• Urine sediment abnormalities: particularly red blood cells or casts, or white blood cells
• Electrolyte abnormalities due to tubular dysfunction
• Structural abnormalities
• Histological abnormalities
• History of kidney transplantation

Accelerated progression of CKD

Accelerated progression of CKD is defined as a persistent decrease in eGFR of 25% or more and a change in CKD category within 12 months, or a persistent decrease in eGFR of 15 mL/min/1.73 m 2 within 12 months. 2

General management

General measures for the management of CKD include: 3,8

• Healthy weight loss
• Smoking cessation
• Good glycaemic control
• Control of blood pressure
• Immunisations: influenza and Pneumococcus
• Avoidance of nephrotoxic medication
• Diet: adequate protein intake, restricted sodium and phosphate intake

Patients should be assessed for cardiovascular risk factors (lipid profile, BMI, exercise, and alcohol and smoking consumption) and offered a statin and antiplatelet drug for the prevention of cardiovascular disease. 3,8

Good blood pressure control is vital in slowing the progression of CKD. In patients with diabetic renal disease or significant proteinuria, an ACE inhibitor or an angiotensin receptor blocker are the first agents of choice, but conversely, they need to be used with care in patients with renovascular disease or those who are at risk of volume depletion or impaired renal perfusion. 8

An SGLT-2 inhibitor may be offered if the patient is taking the highest dose of ACE inhibitor or angiotensin receptor blocker that they can tolerate. 9

Dietary phosphate restriction and phosphate binders (e.g. calcium acetate, sevelamer, lanthanum) to control hyperphosphataemia. 3

1-alpha-hydroxycholecalciferol is administered if secondary hyperparathyroidism is present.

Monitoring requirements include a full blood count and iron studies (for anaemia), serum calcium, phosphate, and parathyroid hormone level (for renal bone disease). 8

Risk level, determined by eGFR and albuminuria, guides the frequency of monitoring: 5

• Low-moderate risk : monitor annually
• High risk : monitor every 6 months
• Very high risk : monitor every 3-4 months

Renal replacement therapy

Renal replacement therapy is an important aspect of the treatment of end-stage CKD. This includes dialysis (either haemodialysis or peritoneal dialysis) and kidney transplantation .

Generally, patients begin dialysis when their GFR reaches approximately 5-10 mL/min/1.73m . 2 , 5

Some patients, particularly those who are elderly or have significant comorbidities, opt for conservative management (best supportive care) rather than renal replacement therapy.

Haemodialysis

Haemodialysis involves pumping blood from the patient’s body through a dialyser (artificial kidney). Solutes from the blood diffuse into the dialysate and are removed together with fluid. This can be performed in a hospital or at home. Hospital-based regimens are typically for 4 hours three times a week . 10

Good blood flow through the dialysis circuit is required, and patients require either an arterio-venous fistula (which typically takes 6-8 weeks to become usable after formation) or a tunnelled central venous catheter . 10 A fistula is the preferred option due to the higher rate of complications with lines (particularly infection).

Complications of haemodialysis include: 10

• Access-related: infection (including bacteraemia leading to endocarditis , discitis), venous stenosis, access failure
• Haemodynamic instability
• Nausea and vomiting, headache, cramps
• Reactions to dialysis membranes

Peritoneal dialysis

Peritoneal dialysis involves infusing dialysate into the peritoneal cavity through a tunnelled catheter. Solutes and fluid from the peritoneal vessels move across the peritoneal membrane into the dialysate and are removed. 10

This requires a functional peritoneal membrane, so patients may not be suitable if they have had previous intra-abdominal pathology (e.g. previous peritonitis, surgery, adhesions).

The two typical regimens , which may be combined: 11

• Continuous ambulatory peritoneal dialysis : manual dialysate exchanges are typically performed four times per day
• Automated dialysis : a machine performs exchanges overnight

Complications of peritoneal dialysis include: 10

• Bacterial or fungal peritonitis
• Catheter problems: infection, blockage, kinking, leaks, displacement (more likely if a patient becomes constipated)
• Weight gain
• Worsening glycaemic control in patients with diabetes
• Failure of peritoneal membrane requiring a switch to haemodialysis
• Encapsulating peritoneal sclerosis

Transplantation

Transplantation provides the best long-term outcome for a patient with CKD and has numerous benefits as it obviates the need for dialysis, can ameliorate anaemia and renal bone disease and improves quality of life and long-term survival. 10

Kidneys may be obtained either from cadaveric donors (heart beating or non-heart-beating) or live donors (genetically related or unrelated).

The patient’s native kidneys are normally left in situ, and the donor kidney is placed in the iliac fossa . Patients receive induction and maintenance immunosuppression to prevent graft rejection. 10

Contraindications to transplantation include active or recent malignancy, active infection, or significant comorbidity (e.g. ischaemic heart disease). 10

Complications of renal transplantation

Complications of renal transplantation include: 10

• Operative complications: infection, bleeding, arterial or venous thrombosis, problems with ureteric anastomosis
• Stenosis of graft artery or ureter
• Side effects from immunosuppressive therapy: nephrotoxicity and hypertension secondary to tacrolimus or ciclosporin
• Opportunistic infections particularly Cytomegalovirus (CMV)
• Malignancy: Epstein Barr virus-driven non-Hodgkin B cell lymphomas, and non-melanoma skin cancers (squamous cell and basal cell carcinomas)
• Recurrence of original renal disease in the transplant
• Hyperacute graft rejection: untreatable and should not occur if appropriate cross-matching has been performed
• Acute graft rejection: presents with creatinine rise, diagnosed by graft biopsy, initial treatment normally with intravenous steroids
• Chronic allograft nephropathy: can occur for multiple reasons, does not usually respond to increased immunosuppression

Complications

The complications of CKD can be related to the functions of the kidney. The mnemonic ‘ A WET BED ‘ is a useful way to recall the functions of the kidney and associated complications of CKD.

Table 1 . A WET BED: the functions of the kidney and associated complications of CKD

Prognosis 14

CKD is a long-term condition and may progress to end-stage renal disease . It cannot be cured, but many aspects can be managed as outlined above. CKD is a strong risk factor for vascular disease , which is often the cause of death in patients with CKD.

Dr Mahzuz Karim

Consultant nephrologist

Norfolk and Norwich University Hospital

Dr Chris Jefferies

• NICE CKS. Chronic Kidney Disease – Definition . 2021. Available from: [ LINK ]
• Singh, M. and Krause, M.,. Chronic Kidney Disease. Epidemiology . 2021. Available from: [ LINK ]
• Tidy C, Jarvis S. Chronic Kidney Disease (Chronic Renal Failure) . 2021. Available from: [ LINK ]
• Oiseth S, Jones L, Maza E. Chronic Kidney Disease | Concise Medical Knowledge. 2021. Available from: [ LINK ]
• Wilkinson I, Raine T, Wiles K, Goodhart A, Hall C, O’Neill H. Oxford handbook of clinical medicine. 10th ed. Oxford University Press; 2017.
• Singh, M. and Krause, M. Chronic Kidney Disease. Approach . 2021. Available from: [ LINK ]
• Singh, M. and Krause, M.  Chronic Kidney Disease. Investigations . 2021. Available from: [ LINK ]
• NICE CKS. Management of chronic kidney disease . 2021 [cited 15 January 2022]. Available from: [ LINK ]
• NICE Guideline. Chronic kidney disease: assessment and management.  2021 [cited 22 February 2022]. Available from: [ LINK ]
• Rull G, Bonsall A. Renal Replacement Therapy and Transplantation . 2016. Available from: [ LINK ]
• National Institute of Diabetes and Digestive and Kidney Diseases. Peritoneal Dialysis . 2022. Available from: [ LINK ]
• Bruce Blaus. Kidney Transplant. 2015. License: [ CC BY-SA ]
• Singh, M. and Krause, M. Chronic Kidney Disease. Complications . 2021. Available from: [ LINK ]
• Singh, M. and Krause, M. Chronic Kidney Disease. Prognosis . 2021. Available from: [ LINK ]

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Chronic Kidney Disease (CKD)

Last Updated: September 11, 2023

Medically reviewed by NKF Patient Education Team

Table of Contents

About chronic kidney disease (ckd), signs and symptoms, complications, preparing for your appointment, download the nkf fact sheet: newly diagnosed with kidney disease, more resources.

Your kidneys do many important jobs. Some of the ways they keep your whole body in balance include:

• Removing natural waste products and extra water from your body
• Helping make red blood cells
• Balancing important minerals in your body
• Helping maintain your blood pressure
• Keeping your bones healthy

Chronic kidney disease (CKD) is when the kidneys have become damaged over time (for at least 3 months) and have a hard time doing all their important jobs. CKD also increases the risk of other health problems like heart disease and stroke. Developing CKD is usually a very slow process with very few symptoms at first. So, CKD is divided into 5 stages to help guide treatment decisions.

Many people living with CKD do not have any symptoms until the more advanced stages and/or complications develop. If symptoms do happen, they may include:

• Foamy urine
• Urinating (peeing) more often or less often than usual
• Itchy and/or dry skin
• Feeling tired
• Loss of appetite
• Weight loss without trying to lose weight

People who have more advanced stages of CKD may also notice:

• Trouble concentrating
• Numbness or swelling in your arms, legs, ankles, or feet
• Achy muscles or cramping
• Shortness of breath
• Trouble sleeping
• Breath smells like ammonia (also described as urine-like or “fishy”)

Your kidney health is unique. Your path should be too.

Risk factors.

Anyone can develop CKD - at any age. However, some people are at a higher risk than others. The most common CKD risk factors are:

• High blood pressure (hypertension)
• Heart disease and/or heart failure
• Over the age of 60
• Family history of CKD or kidney failure
• Personal history of acute kidney injury (AKI)
• Smoking and/or use of tobacco products

For many people, CKD is not caused by just one reason. Instead, it is a result of many physical, environmental, and social factors . Early detection is important – CKD often begins without causing any noticeable symptoms. Knowing the risk factors can help you know your level of risk and if you should get checked for CKD.

Other causes

CKD can also be caused by many other conditions or circumstances. Some examples include:

• Glomerular diseases: glomerulonephritis , IgA nephropathy (IgAN) , and HIV nephropathy
• Inherited conditions: polycystic kidney disease
• Autoimmune conditions: lupus (lupus nephritis)
• Severe infections: sepsis and hemolytic uremic syndrome (HUS)
• Other causes: kidney cancer , kidney stones , frequent untreated and/or long-lasting urinary tract infections (UTIs) , hydronephrosis , and kidney and urinary tract abnormalities before birth

37 million adults in the United States are living with CKD - and approximately 90% do not even know they have it. Take this one-minute quiz to find out if you are at high risk for CKD. 

As CKD worsens, the risk of getting complications goes up. Some examples include:

• Cardiovascular disease (heart disease and/or stroke)
• High blood pressure
• Anemia (low levels of red blood cells)
• Metabolic acidosis (buildup of acid in the blood)
• Mineral and bone disorder (when blood levels of calcium and phosphorus are out of balance leading to bone and/or heart disease)
• Hyperkalemia (high levels of potassium in the blood)
• Kidney failure

Some conditions, like cardiovascular disease and high blood pressure, can also cause or worsen CKD.

Checking for CKD is easy with two simple tests:

• a blood test known as the estimated glomerular filtration rate (eGFR)
• a urine test known as the urine albumin-creatinine ratio (uACR)

Both tests are needed to have a clear picture of your kidney health. Having an eGFR under 60 and/or a uACR over 30 for three months or more is a sign you may have kidney disease.

The eGFR is an estimate of how well your kidneys are removing waste products from the blood. It is calculated using your serum creatinine level, age, and sex. It can also be calculated using your cystatin C level. A “normal” eGFR varies according to age – it decreases as you get older. For this test, a higher number is better. Your eGFR number is used to determine your stage of CKD .

The uACR measures the amount of two different substances in your urine – albumin (protein) and creatinine. Healthy kidneys keep the albumin in your blood while filtering the creatinine out into the urine. So, there should be very little or no albumin in your urine. The uACR is calculated by dividing the amount of urine albumin by the amount of urine creatinine to find the ratio. For this test, a lower number is better. Your uACR number is used to test for albuminuria - a significant risk factor for complications.

In some cases, your healthcare professional may order additional tests to get more information about your kidney health. Some examples include a kidney biopsy or medical imaging (CT scan, ultrasound, or MRI).

Understanding my kidney numbers

Watch a playlist of short, animated videos with information about your kidney numbers, including: 

• A brief explanation of the uACR and eGFR tests
• Reading the CKD Heat Map and understanding your risk
• Important steps for managing CKD

Managing CKD is focused on four very important goals:

• Managing the disease(s) or condition(s) that are most likely causing the CKD (for example, your diabetes, high blood pressure, or IgA nephropathy)
• Taking steps to slow down the CKD disease process directly (also known as “slowing CKD progression”)
• Lowering your risk of cardiovascular disease (having a heart attack or stroke)
• Treating any complications that you may have because of your CKD

Specific treatment recommendations depend on your stage of CKD and what other health conditions you have (including any CKD complications). Below are recommendations that apply to most people with CKD. No two people are the same, so talk with your healthcare professional about recommendations tailored to you. 

Medications

Your healthcare professional may prescribe one or more medicines to help slow down or stop your CKD from getting worse. These medicines can include an ACE inhibitor/ARB , an SGLT2 inhibitor and/or an nsMRA .

Your healthcare professional may also prescribe a statin (cholesterol medicine). Guidelines recommend a statin for people with CKD who also have diabetes, a history of heart disease, or are age 50 or older. Even if you do not have high cholesterol, a statin can help lower your risk of having a heart attack or stroke.

You may also need to take additional medications or supplements to manage any CKD complications you might have (if applicable).

It is important to limit your sodium (salt) intake to less than 2300 mg per day (about 1 teaspoon of salt from all the food and drinks you consume each day). This recommendation is very important if you also have high blood pressure. Your healthcare professional may advise an even lower target depending on your other health conditions. This means a lot more than not using a saltshaker, but also limiting foods with high levels of sodium listed on their nutrition facts label . Some foods that don’t taste salty can have a surprising amount of sodium when you check their nutrition facts label.

Based on the results of your blood tests, your healthcare professional or kidney dietitian may also advise you to change how much potassium , phosphorus , and/or calcium you might be getting through your diet.

Meeting with a dietitian can be especially helpful if you also have other health conditions like high blood pressure, diabetes, or heart failure where it is even more important to integrate a healthy diet into your lifestyle to help prevent complications. It can feel overwhelming to keep track of so many changes, and a dietitian can help you identify what works best for you.

Additional information about eating healthy with kidney disease can be found on the Nutrition and Early Kidney Disease page.

Lifestyle recommendations

Now is a great time to make healthier lifestyle choices:

• If you smoke and/or use tobacco products , stop. Smoking can speed up the kidney disease process and increase your risk of getting kidney failure. It also increases your risk for other serious health problems, including high blood pressure, heart disease, cancers, and stroke.
• Exercise regularly . Remember, it’s okay to start slowly – taking short walks is a great way to begin.
• Sleeping well is important, too. Try to get enough sleep so you are well-rested.
• If you are overweight , losing weight through a balanced diet and physical activity can help improve your health in many ways.
• Find ways to reduce and manage stress in your life.

Other ways to lower your risk

Taking steps to manage other health conditions you may also have can also help your CKD. This includes high blood pressure , diabetes , and high cholesterol .

People with CKD should also avoid certain pain medicines known as non-steroid anti-inflammatory drugs (NSAIDs) . These can be harmful to your kidneys, especially at higher doses and/or with long-term use. Some examples include:

• ibuprofen (Motrin, Advil)
• indomethacin (Indocin)
• naproxen (Aleve, Naprosyn)
• diclofenac tablets or capsules (Cataflam, Zipsor)
• celecoxib (Celebrex)
• meloxicam (Mobic)
• aspirin (only if more than 325 mg per day)

Many of these NSAID medicines are available over-the-counter (OTC) and may be sold under a different name or be mixed with other ingredients (like cough & cold medicines). Sometimes it may not be possible to avoid using these products depending on your other health conditions. Always ask your healthcare professional before using any products with these drug names or if the word “NSAID” is printed on the product’s label. In general, acetaminophen, also called Tylenol, is safe for your kidneys at recommended doses - but check with your healthcare professional first to determine the cause of your pain and the best way to treat it.

If your healthcare professional says you have metabolic acidosis , increasing the amount of fruits and vegetables you eat everyday can help lower the level of acid in your blood. This can also help slow down your CKD progression (worsening).

Check out our online communities to connect, learn more and hear from others going through similar experiences.

Questions to ask.

• What are my eGFR and uACR numbers? What is my CKD stage?
• How high is my level of risk for developing heart disease or a stroke? What can I do to lower my risk?
• When should I have my eGFR and uACR tested again?
• Am I at a healthy weight?
• Is my blood pressure within the recommended goal range?
• Do I have diabetes or prediabetes? If so, is my A1C within the recommended goal range?
• Do I have albuminuria?
• Are there any changes I should make to my diet?
• Should I take any medication(s) to help lower my risk for CKD getting worse?
• Download the NKF fact sheet:  Newly diagnosed with kidney disease: English
• Download the NKF fact sheet: Newly diagnosed with kidney disease: Spanish

Stages of Chronic Kidney Disease (CKD)

Learn more information about chronic kidney disease (CKD), including:

• How CKD is detected and classified
• Risk factors for developing CKD
• Information for managing CKD at each stage
• Kidneys and Chronic Kidney Disease
• Kidney Disease and Albuminuria/Proteinuria
• Kidney Numbers and the CKD Heat Map
• Plant Based Diets and Early CKD
• 7 Ways to Help Manage Your Kidney Disease
• NKF Council on Renal Nutrition CKD Kidney Dietitian Directory

How helpful was this content?

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JSmol Viewer

Does the composition of gut microbiota affect chronic kidney disease molecular mechanisms contributed to decreasing glomerular filtration rate.

1. Introduction

2. review methodology, 3. what is renal failure, 3.1. definition, types, 3.2. etiology and causes, 3.3. standard treatment, 3.3.1. treatment of hypertension, 3.3.2. treatment of diabetes mellitus, 3.3.3. cardiovascular disease risk reduction, 3.4. complications, 4. molecular basis of renal failure, 4.1. programmed cell death, 4.2. the co-occurrence of obesity and renal failure, 4.3. uremic toxins, 5. association between chronic kidney disease and gut microbiota, 5.1. basic microbiological information and molecular aspects, 5.2. microbiological assessment and used technical methods, 5.3. quantitative and qualitative gut microbiota analysis in patients with ckd and esrd compared to the healthy population, 6. potential role of probiotics in the treatment of chronic kidney disease, 6.1. gut dysbiosis and chronic kidney disease—can we treat both, 6.2. what are probiotics, 6.3. probiotics and renal failure: mechanisms of action.

• Reduction in uremic toxins: Probiotics could support a reduction in the production and absorption of uremic toxins by modifying the gut microbiota composition. Research has shown that specific probiotic strains, including Lactobacillus and Bifidobacterium, have the potential to decrease the levels of indoxyl sulfate and p-cresyl sulfate, which may potentially slow the progression of kidney disease [ 92 ].
• Improvement of gut barrier function: Renal failure could compromise the integrity of the gut barrier, leading to increased intestinal permeability (leaky gut). Moreover, probiotics could strengthen the gut barrier by promoting the growth of beneficial bacteria that enhance gut integrity. These microorganisms might reduce the translocation of harmful bacteria and toxins from the gut into the bloodstream while also potentially mitigating systemic inflammation and further kidney damage [ 115 ].
• Metabolic benefits: Probiotics have the potential to enhance metabolic profiles by increasing insulin sensitivity, reducing oxidative stress, and lowering lipid levels [ 21 ].
• Anti-inflammatory effects: Chronic inflammation represents a pivotal element in the advancement of renal failure. Probiotics could exert anti-inflammatory effects by modulating the immune response and reducing the production of pro-inflammatory cytokines, thereby aiding in the protection of kidney tissues from further damage [ 116 ].
• Regulation of blood pressure: Hypertension is both a cause and a consequence of renal failure. Some probiotic strains could help regulate blood pressure by producing bioactive peptides that inhibit angiotensin-converting enzyme (ACE), a key regulator of blood pressure. Improved blood pressure control can reduce the stress on the kidneys and slow the progression of kidney disease [ 117 ].

6.4. The Use of Probiotics and Synbiotics in Kidney Diseases

6.5. the use of probiotics and synbiotics in chronic kidney disease, 7. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Młynarska, E.; Budny, E.; Saar, M.; Wojtanowska, E.; Jankowska, J.; Marciszuk, S.; Mazur, M.; Rysz, J.; Franczyk, B. Does the Composition of Gut Microbiota Affect Chronic Kidney Disease? Molecular Mechanisms Contributed to Decreasing Glomerular Filtration Rate. Int. J. Mol. Sci. 2024 , 25 , 10429. https://doi.org/10.3390/ijms251910429

Młynarska E, Budny E, Saar M, Wojtanowska E, Jankowska J, Marciszuk S, Mazur M, Rysz J, Franczyk B. Does the Composition of Gut Microbiota Affect Chronic Kidney Disease? Molecular Mechanisms Contributed to Decreasing Glomerular Filtration Rate. International Journal of Molecular Sciences . 2024; 25(19):10429. https://doi.org/10.3390/ijms251910429

Młynarska, Ewelina, Emilian Budny, Maciej Saar, Ewa Wojtanowska, Justyna Jankowska, Szymon Marciszuk, Marcin Mazur, Jacek Rysz, and Beata Franczyk. 2024. "Does the Composition of Gut Microbiota Affect Chronic Kidney Disease? Molecular Mechanisms Contributed to Decreasing Glomerular Filtration Rate" International Journal of Molecular Sciences 25, no. 19: 10429. https://doi.org/10.3390/ijms251910429

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Transition from Acute Kidney Injury to Chronic Kidney Disease: Mechanisms, Models, and Biomarkers

Affiliations.

• 1 Pharmacology, Monash University, Clayton, Vic, Australia.
• 2 Phramacology, Monash University, Melbourne, VIC, Australia.
• 3 Pharmacology, Monash University, Clayton, Victoria, Australia.
• PMID: 39298548
• DOI: 10.1152/ajprenal.00184.2024

Acute kidney injury (AKI) and chronic kidney disease (CKD) are increasingly recognized as interconnected conditions with overlapping pathophysiological mechanisms. This review examines the transition from AKI to CKD, focusing on the molecular mechanisms, animal models, and biomarkers essential for understanding and managing this progression. AKI often progresses to CKD due to maladaptive repair processes, persistent inflammation, and fibrosis, with both conditions sharing common pathways involving cell death, inflammation, and extracellular matrix (ECM) deposition. Current animal models, including ischemia/reperfusion injury (IRI) and nephrotoxic damage, help elucidate these mechanisms but have limitations in replicating the complexity of human disease. Emerging biomarkers such as kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), and soluble tumor necrosis factor receptors (TNFRs) show promise in early detection and monitoring of disease progression. The review highlights the need for improved animal models and biomarker validation to better mimic human disease and enhance clinical translation. Advancing our understanding of the AKI-to-CKD transition through targeted therapies and refined research approaches holds the potential to significantly improve patient outcomes.

Keywords: acute kidney injury; animal models; biomarkers; chronic kidney disease; fibrosis.

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Estimates for survival in the year following hospitalization, with a single low-to-normal estimated glomerular filtration rate (eGFR) exposure group (A) and with a subdivision of the low-to-normal eGFR exposure group (B). Patients for whom both the first and last eGFR values were over 60 mL/min/1.73 m 2 were defined as having normal to normal kidney function. Patients for whom the first value (ie, at presentation) was under 60 mL/min/1.73 m 2 and the last value (ie, at discharge) was over 60 mL/min were defined as having low to normal kidney function. The low to normal group was subdivided into 2 levels: less than 45 mL/min/1.73 m 2 at presentation and 45 to 60 mL/min/1.73 m 2 at presentation. Shaded areas indicate 95% CI.

Estimated glomerular filtration rate (eGFR) for end-stage kidney disease in the 10 years following hospitalization, with a single low-to-normal eGFR exposure group (A) and a subdivision of the low-to-normal eGFR exposure group (B). Shaded areas indicate 95% CI.

eTable 1. Definitions of Variables Used for the Exposure, Eligibility, and Adjustment

eTable 2. Treatment Frequency of Diuretics or Renin-Angiotensin-Aldosterone System Inhibitors on Admission and Discharge

eTable 3. The Association Between Kidney Function at Admission and Outcomes Following the Index Hospitalization With Adjustment to eGFR at Discharge

eTable 4. Additional Analyses of the Association Between Kidney Function at Admission and Outcomes Following the Index Hospitalization

eFigure. Proportionality of Hazards of the Main Exposure Assessed by Schoenfeld Residuals

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Efros O , Beckerman P , Basson AA, et al. Fluctuations in Serum Creatinine Levels During Hospitalization and Long-Term End-Stage Kidney Disease and Mortality. JAMA Netw Open. 2023;6(8):e2326996. doi:10.1001/jamanetworkopen.2023.26996

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Fluctuations in Serum Creatinine Levels During Hospitalization and Long-Term End-Stage Kidney Disease and Mortality

• 1 National Hemophilia Center and Thrombosis & Hemostasis Institute, Sheba Medical Center, Ramat Gan, Israel
• 2 Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
• 3 Institute of Nephrology and Hypertension, Sheba Medical Center, Ramat Gan, Israel
• 4 TIMNA–Israel National Big Data Platform for Health Research, Ministry of Health, Jerusalem, Israel
• 5 ARC Innovation Center, Sheba Medical Center, Ramat Gan, Israel
• 6 Department of Medical Management, Sheba Medical Center, Ramat Gan, Israel
• 7 Internal Medicine B, Assuta Medical Center, Ashdod, Israel
• 8 Ben-Gurion University of the Negev, Be’er Sheva, Israel
• 9 Software and Information Systems Engineering, Ben Gurion University, Be’er Sheva, Israel
• 10 Epidemiology, Biostatistics, and Community Health Services, Ben-Gurion University of the Negev, Be’er Sheva, Israel
• 11 Internal Medicine Wing, Sheba Medical Center, Ramat Gan, Israel

Question   What are the long-term outcomes for hospitalized patients with reduced kidney function on admission who are discharged with apparently normal kidney function?

Findings   In this cohort study that included 40 558 adults, patients with reduced kidney function on admission who were discharged with apparently normal kidney function experienced 18% increased mortality in the year following the hospitalization. The risk of end-stage kidney disease increased by 267% in the 10 years following the hospitalization.

Meaning   The findings of this study suggest that reversible reduction in kidney function among hospitalized patients is associated with an increased long-term risk for end-stage kidney disease and mortality.

Importance   Acute kidney injury is associated with poor outcomes, but the clinical implication of reversible serum creatinine level fluctuations during hospitalization not necessarily defined as acute kidney injury is poorly understood.

Objective   To investigate the long-term outcomes of patients without previously diagnosed kidney disease who present with decreased kidney function and are subsequently discharged with apparently normal kidney function.

Design, Setting, and Participants   A retrospective cohort study was conducted of patients hospitalized in a large tertiary hospital in Israel between September 1, 2007, and July 31, 2022. The study included patients admitted to an internal medicine ward. Patients had not undergone dialysis during the index hospitalization, had at least 3 creatinine tests performed during hospitalization, and had a discharge estimated glomerular filtration rate (eGFR) exceeding 60 mL/min/1.73 m 2 . Patients with preexisting chronic kidney disease were excluded.

Exposure   Glomerular filtration rate was estimated from serum creatinine values using the updated 2022 Chronic Kidney Disease Epidemiology Collaboration formula, and eGFR greater than 60 mL/min/1.73 m 2 was regarded as normal. Exposure was defined based on the association between the first and last values determined during hospitalization.

Main Outcomes and Measures   All-cause mortality in the year following the index hospitalization and end-stage kidney disease (ESKD) in the 10 years following the index hospitalization.

Results   A total of 40 558 patients were included. Median age was 69 (IQR, 56-80) years, with 18 004 women (44%) and 22 554 men (56%). A total of 34 332 patients (85%) were admitted with a normal eGFR and 6226 (15%) with decreased eGFR. Patients with decreased eGFR on presentation had an 18% increased mortality in the year following hospitalization (adjusted hazard ratio [AHR], 1.18; 95% CI, 1.11-1.24) and a 267% increased risk of ESKD in the 10 years following hospitalization (AHR, 3.67; 95% CI, 2.43-5.54), despite having been discharged with apparently normal kidney function. The highest risk was noted in patients who presented to the hospital with an eGFR of 0 to 45 mL/min/1.73 m 2 .

Conclusions and Relevance   The findings of this cohort study suggest that patients who present with decreased kidney function and are discharged without clinically evident residual kidney disease may be at increased long-term risk for ESKD and mortality.

The global incidence of acute kidney injury (AKI) is rapidly increasing, particularly among hospitalized patients with acute illness. 1 , 2 In a systematic review of large cohort studies, which included 49 million patients, 1 in 5 adults worldwide experienced AKI during hospitalization. 3

Several studies have reported that AKI during hospitalization is associated with poor outcomes and high use of health care resources. 1 , 4 - 9 A meta-analysis of 49 studies containing a total of 47 017 participants noted that patients who developed AKI during hospitalization had a higher rate of long-term mortality than patients without AKI during hospitalization. 7 In a large observational study of 104 764 hospitalized veterans without chronic kidney disease (CKD), even a mild episode of in-hospital AKI with full recovery was associated with the eventual development of CKD. 10

The Kidney Disease Improving Global Outcomes (KDIGO) staging system defines AKI as an increase in the serum creatinine level over hours to days (ie, ≥0.3 mg/dL within 48 hours or ≥1.5 times baseline within the previous 7 days [to convert to micromoles per liter, multiply by 88.4]) or a decrease in urine output (≤0.5 mL/kg/h for 6 hours). 11 Therefore, AKI may only partially represent the prognostic importance of serum creatinine level fluctuations during hospitalization.

Indeed, worsening kidney function was also noted to be a predictor of increased mortality, even when not meeting the definition of AKI. 12 - 15 Givertz et al 14 examined data from 1962 patients with acute heart failure and kidney dysfunction from the PROTECT study. In this analysis, an increase of more than 0.1 mg/dL per day in serum creatinine levels increased mortality risk, whereas stable or decreasing creatinine levels were associated with reduced risk.

However, the clinical implication of creatinine level changes, which are not necessarily defined as AKI, with subsequent full recovery, is poorly described. This study aimed to investigate the long-term outcome of patients without previously diagnosed kidney disease who presented with decreased kidney function but may not have met the full AKI criteria 16 and were subsequently discharged from the hospital with apparently normal kidney function.

This was a retrospective cohort study based on the integration of the electronic medical records from Sheba Medical Center (SMC) with Israeli nationwide records regarding end-stage kidney disease (ESKD) using TIMNA, a national research platform established by the Israeli government for conducting big-data research and combining deidentified health data from multiple health organizations. All medical data generated by SMC are recorded in electronic medical records and subsequently stored in an analytic data warehouse for further study. By a directive in the national health care insurance law, data regarding all patients in Israel with ESKD (chronic dialysis treatment and kidney transplant) are collected in a central registry maintained by the Ministry of Health. These data are manually verified and constantly updated. The mortality status of patients was identified using the official death records maintained by the Ministry of Interior in the State of Israel, which provides comprehensive and up-to-date information on all deaths occurring within the country. The study was approved by the SMC Institutional Review Board and was exempt from the requirement for informed consent due to the use of deidentified data. The reporting of this study aligns with the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline. Patients included in the study were those admitted to an internal medicine ward in SMC between September 1, 2007, and July 31, 2022, were older than 18 years at hospitalization, were hospitalized between 2 and 14 days, had not undergone dialysis during the index hospitalization, and had at least 3 creatinine tests performed during their hospitalization. Although our primary analysis focused on the first and last creatinine values, by mandating 3 or more creatinine level determinations, we indirectly ensured sufficient monitoring of kidney function during the patients’ hospitalizations. For patients admitted multiple times during the study period, only the first hospitalization was retained.

Glomerular filtration rate (GFR) was estimated from creatinine values using the Chronic Kidney Disease Epidemiology Collaboration formula, updated for the year 2022. 17 Only patients with discharge estimated GFR (eGFR) values over 60 mL/min/1.73 m 2 were included.

Individuals with a history of CKD, dialysis therapy, or kidney transplant, as noted by the admitting physician, were excluded from the study. Documentation of CKD was identified in the admission file by the relevant International Statistical Classification of Diseases and Related Health Problems: Alphabetical Index codes 18 and diagnosis-free text (eTable 1 in Supplement 1 provides the full code listing).

Exposure was defined based on the association between the first and last eGFR measurements performed during hospitalization. Patients for whom both the first and last values were over 60 mL/min/1.73 m 2 were defined as having normal to normal kidney function. Patients for whom the first value was under 60 mL/min/1.73 m 2 and the last value was over 60 mL/min/1.73 m 2 were defined as having low to normal kidney function. To account for minor test-to-test variations and ensure we were capturing a substantial change in kidney function, patients were included in the low-to-normal kidney function category only if the increase in eGFR was 15% or more of the initial value.

Two outcomes were considered. The first was all-cause mortality in the year following the index hospitalization. The second was ESKD in the 10 years following the index hospitalization. Covariates for adjustment were the same for both outcomes, were chosen based on domain expertise, and included age, sex, and a history of hypertension, diabetes, ischemic heart disease, heart failure, cancer, atrial fibrillation, and chronic obstructive pulmonary disease. Additional variables were included to describe the study population. The specific criteria used to identify each condition are detailed in eTable 1 in Supplement 1 .

Several additional analyses were performed. First, subgroup analyses were performed for groups defined by age, sex, background diseases, and treatment with either angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers. We then considered the exposure in a more refined manner, separating patients with a first eGFR value between 45 and 60 mL/min/1.73 m 2 and patients with a first eGFR value of less than 45 mL/min/1.73 m 2 . We further adjusted for discharge eGFR to directly compare patients with the same discharge kidney function. We also performed the main analysis allowing a different baseline hazard across age groups. For a sensitivity analysis, we changed the normal eGFR threshold to 90 mL/min/1.73 m 2 .

To ensure that normal eGFR on discharge was not due to decreased creatinine levels secondary to factors other than improved kidney function, such as loss of muscle mass during critical illness, 19 we conducted numerous analyses to address further possible misclassification, including a subgroup analysis of patients with a hospital stay of 5 days or less and those hospitalized for more than 5 days and a subgroup analysis that only included patients in the low-to-normal kidney function category if they had an increase in eGFR of 30% or more.

We explored temporal trends in mortality and ESKD over the study period by estimating the interaction between primary exposure and calendar time. Finally, we also defined the exposure solely based on creatinine levels, without relying on eGFR. For this analysis, we considered 2 groups: patients with admission creatinine levels above the normal limit (1.3 mg/dL for men and 1.1 mg/dL for women) and patients with admission creatinine levels below the normal limit, both with normal creatinine levels on discharge. To ensure sufficient kidney function changes, we still required at least a 15% improvement in creatinine levels for the low-to-normal group.

The study population was described in terms of sociodemographic variables, physical measurements, and background medical conditions. Appropriate statistical tests were selected for each variable. Crude survival curves for each outcome were calculated using the Kaplan-Meier estimator, stratified by the exposure, and compared using the log-rank test.

Cox proportional hazards regression was used to estimate the hazard ratio (HR) for each outcome between the 2 exposure groups over the study period, adjusted for the aforementioned variables. The assumption of proportionality of hazards was checked using Schoenfeld residuals.

Missing data, which are rare in the SMC database for the variables used in this study, were handled using a complete case analysis. The analysis was performed using the R statistical software, version 4.1.2 (R Foundation for Statistical Computing). The significance threshold, set at P  < .05, was unpaired and 2-sided.

Following the application of the eligibility criteria, 40 558 individuals were included in the study; of these, 34 332 (85%) belonged to the normal-to-normal group and 6226 (15%) to the low-to-normal group. A total of 765 patients were excluded due to not meeting the 15% or more increase in eGFR from the initial value required for inclusion in the low-to-normal category. The median age was 69 (IQR, 56-80) years, with 18 004 women (44%) and 22 554 men (56%). Patients in the low-to-normal group were older; had a higher prevalence of comorbid conditions, such as diabetes, ischemic heart disease, heart failure, chronic obstructive pulmonary disease, hypertension, and atrial fibrillation; and were more likely to be treated with diuretics or renin-angiotensin-aldosterone system inhibitors on admission and discharge ( Table 1 ; eTable 2 in Supplement 1 ). A total of 1195 patients in the low-to-normal group had a further decrease in eGFR during hospitalization before the eGFR increased to the normal range.

Crude analysis showed increased mortality in the year following the index hospitalization ( Figure 1 A) and increased risk for ESKD in the 10 years following the index hospitalization ( Figure 2 ) in the low-to-normal group. The adjusted analysis estimated an 18% increased risk of death for the low-to-normal group in the year following hospitalization compared with the normal-to-normal group (adjusted HR [AHR], 1.18; 95% CI, 1.11-1.24) and a 267% increased risk for ESKD for the low-to-normal group in the 10 years following hospitalization compared with the normal-to-normal group (AHR, 3.67; 95% CI, 2.43-5.54). No substantial heterogeneity of the association was observed when looking at different age groups, sex, or specific comorbidities ( Table 2 ; eTable 4 in Supplement 1 ). Inspecting Schoenfeld residuals, we found that the main exposure obeyed the proportional hazards assumption (eFigure in Supplement 1 ).

For the mortality outcome in the full study population and within subgroups a dose-response association was evident, with worse outcomes for patients whose admission eGFR was lower ( Figure 1 B, Table 2 ). In the full population, we estimated a higher risk of death in patients with an eGFR of 0 to 45 mL/min/1.73 m 2 on admission (AHR, 1.42; 95% CI, 1.31-1.54) than for patients with an eGFR of 45 to 60 mL/min/1.73 m 2 (AHR, 1.05; 95% CI, 0.98-1.13).

Further adjustment for discharge eGFR did not substantially alter the estimates (eTable 3 in Supplement 1 ), nor did allowing a different baseline hazard by age group (eTable 4 in Supplement 1 ). In our sensitivity analysis using an eGFR threshold of 90 mL/min/1.73 m 2 , we did not find an association between the exposure group and 1-year mortality (AHR, 0.95; 95% CI, 0.87-1.04) and did not have enough data to analyze the risk for 10-year ESKD.

Subgroup analyses of patients with a hospital stay of 5 days or less, those hospitalized for more than 5 days, and a subgroup from the low-to-normal group with an increase in eGFR of 30% or more showed a persistently higher risk of 1-year mortality and ESKD within 10 years in the low-to-normal group compared with the normal-to-normal group (eTable 4 in Supplement 1 ). Interaction analysis did not reveal a significant temporal trend in the incidence of 1-year-mortality (interaction HR, 1.00; 95% CI, 1.00-1.03) or 10-year risk for ESKD (interaction HR, 1.01; 95% CI, 0.89-1.14) over the study timeframe.

The results from our creatinine level–based analysis mirrored the trends we observed in our eGFR-based analysis. The adjusted analysis estimated a 25% increased risk of death in the year following hospitalization for patients with admission creatinine levels above the normal limit that subsequently decreased upon discharge compared with patients with admission and discharge normal creatinine levels (AHR, 1.25; 95% CI, 1.18-1.33). A 209% increased risk for ESKD was found for patients with admission creatinine levels above the normal limit that subsequently decreased upon discharge compared with patients with admission and discharge normal creatinine levels (AHR, 3.09; 95% CI, 2.02-4.71).

This study of a large cohort of hospitalized patients discharged with an apparently normal eGFR, defined as eGFR greater than or equal to 60 mL/min/1.73 m 2 , noted a higher risk of mortality and ESKD among participants with decreased eGFR on admission that was not necessarily confined to the KDIGO definition of AKI 11 compared with participants who presented with a normal eGFR. Our findings remained consistent when defining the exposure solely based on creatinine levels. The risk seemed to be graded, with the highest risk for mortality noted in patients who presented to the hospital with an eGFR of less than 45 mL/min/1.73 m 2 than with an eGFR of 45 to 60 mL/min/1.73 m 2 . This increased risk persisted after adjusting for confounders; stratifying by age groups, sex, background disease, and treatment with either angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers; and when allowing a different baseline HR across age groups. It was not altered by adjusting for discharge eGFR, and we did not observe temporal trends. These results suggest that patients who present with decreased kidney function and are discharged without clinically evident residual kidney disease are at increased long-term risk of ESKD.

The high 1-year mortality rate observed in our study reflects the patient cohort, which primarily consists of older individuals with acute or complex conditions. Similar trends have been noted in other studies, such as that by Fløjstrup et al, 16 emphasizing the serious outcomes often associated with acute hospital admissions in cohorts with these demographic characteristics.

The association between recovered kidney injury and long-term clinical outcomes was previously described. 10 , 20 - 22 Bucaloiu et al 20 found an increased mortality risk and future CKD following an in-hospital reversible AKI among 1610 patients without preexisting kidney disease. Similar findings were found in other studies, with a consistent association between reversible AKI and subsequent clinical outcomes, including subsequent CKD and mortality rate. 22 , 23 However, kidney outcomes and mortality risk following any reduction in GFR with subsequent full recovery were not studied. Moreover, current guidelines do not recommend long-term follow-up of patients with non-AKI. 11 To our knowledge, this is the first study to investigate the mortality risk and ESKD among a large cohort of patients discharged from the hospital with apparently recovered kidney function following any eGFR reduction and without necessarily meeting time-dependent creatinine level–based KDIGO-defined AKI.

Creatinine level–based eGFR may not accurately reflect the severity of the kidney injury in the acute setting, as creatinine levels are often not increased until several days after AKI has occurred. 24 Despite this shortcoming, the use of creatinine level–based eGFR has distinct advantages compared with current risk stratification strategies, which focus on the presence of AKI and an increase in serum creatinine levels over time. 7 , 11 , 25 - 27 First, reliance on the definition of AKI may fail to recognize clinical outcomes of patients with smaller serum creatinine increases or variable creatinine level fluctuations. Second, these approaches still require information on baseline serum creatinine levels, which is not always available. In addition, efforts to estimate baseline creatinine levels from in-hospital creatinine tests or by using other patient-based equations were inaccurate and resulted in misclassifications of AKI. 28

A possible explanation for our findings is that an observed decrease in kidney function during hospitalization might reveal an existing decreased kidney reserve, unmasked by the stress of acute illness. 29 Even though kidney function may seem to be recovered at discharge, the persistent reduction in kidney reserve could have long-term implications. Setting the threshold for normal kidney function at an eGFR of 90 mL/min/1.73 m 2 revealed no associations with 1-year mortality, implying that more substantial kidney damage may be required to influence long-term outcomes.

Our study has several limitations. We did not have access to the baseline prehospitalization serum creatinine levels of the patients included in our study and therefore cannot definitively establish a full recovery to baseline eGFR. We included only patients with 3 or more creatinine tests during hospitalization, which could result in selectively including patients admitted for more severe medical conditions requiring serial blood testing. We included a heterogeneous hospitalized population with different admission diagnoses and etiologies for reduced kidney function on presentation. We only considered a single hospitalization per patient, because evaluating further hospitalizations was beyond the scope of our study and limited by our lack of access to patient data from other medical institutions.

The main challenge to the robustness of our results could be the potential misclassification of exposure groups. Relying on creatinine levels to estimate GFR values may not perfectly represent the measured GFR on an individual level and could result in misclassification by several mechanisms. 24 , 30 First, it is possible that creatinine levels have not yet reached their steady-state peak at the time of measurement, leading to some participants with low-to-normal kidney function being misclassified as having normal-to-normal kidney function. However, such misclassification would likely result in an underestimation of the long-term risks for ESKD and mortality in the low-to-normal group in our findings. Second, Prowle et al 19 described a decrease in discharge serum creatinine levels among patients hospitalized in intensive care units, attributed by the authors to a decrease in muscle mass over time during critical illness. This could have potentially misclassified some patients with low to normal eGFR as having normal to normal eGFR. However, the patient population in our study had a substantially shorter hospital stay than those in the Prowle et al study, and a subgroup analysis of patients hospitalized for less than 5 days showed consistent results, limiting the potential for extensive muscle mass loss. The inclusion criteria for the low-to-normal group of at least a 15% eGFR improvement and the additional analysis of patients with more than 30% eGFR improvement indicated substantial creatinine level change unlikely due to critical illness alone. Here again, an underestimation of discharge creatinine levels due to factors other than recovery reinforces our conclusions about the need for long-term follow-up for these patients. In addition, our study could have encountered potential misclassification by including patients with CKD. However, CKD is conventionally indicated by an eGFR of less than 60 mL/min/1.73 m 2 for a period exceeding 3 months and has implications for health, as per the KDIGO guidelines. 31 By selectively including patients with restored normal eGFR at discharge and excluding those with a previous CKD diagnosis recorded by the admitting physician, this risk is mitigated.

The findings of this cohort study suggest that, in hospitalized patients discharged with apparently recovered kidney function, a decreased eGFR on presentation may be associated with increased mortality in the year following the hospitalization and increased risk of ESKD in the 10 years following the hospitalization. Currently, these populations are not considered at risk unless AKI, as defined by KDIGO, was observed. Therefore, these patients should be advised to continue medical observation following their discharge from the hospital.

Accepted for Publication: June 22, 2023.

Published: August 3, 2023. doi:10.1001/jamanetworkopen.2023.26996

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Efros O et al. JAMA Network Open .

Corresponding Author: Orly Efros, MD, MHA, National Hemophilia Center and Thrombosis & Hemostasis Institute, Sheba Medical Center, Ramat Gan, Israel ( [email protected] ).

Author Contributions: Drs Efros and Barda had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the analysis. Drs Barda and Grossman contributed equally.

Concept and design : Efros, Beckerman, Klang, Soffer, Barda, Grossman.

Acquisition, analysis, or interpretation of data: Efros, Basson, Cohen, Klang, Frenkel Nir, Barda, Grossman.

Drafting of the manuscript: Efros, KLang, Barda, Grossman.

Critical review of the manuscript for important intellectual content: Efros, Beckerman, Basson, Cohen, Klang, Frenkel Nir, Soffer, Barda, Grossman.

Statistical analysis: Efros, Barda.

Administrative, technical, or material support: Efros, Basson, Cohen, Frenkel Nir, Soffer.

Supervision: Efros, Beckerman, Klang, Frenkel Nir, Barda, Grossman.

Conflict of Interest Disclosures: Dr Barda reported receiving grants to Sheba Medical Center from Pfizer and Moderna with no direct or indirect personal benefit. No other disclosures were reported.

Data Sharing Statement: See Supplement 2 .

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• Published: 27 September 2024

Nonlinear association between atherogenic index of plasma and chronic kidney disease: a nationwide cross-sectional study

• Bo Wang 1 ,
• Chunqi Jiang 2 ,
• Yinuo Qu 2 ,
• Jun Wang 2 ,
• Chuanzhu Yan 2 &
• Xin Zhang 3  

Lipids in Health and Disease volume  23 , Article number:  312 ( 2024 ) Cite this article

Metrics details

The interplay between metabolic disorders and chronic kidney disease (CKD) has been well-documented. However, the connection between CKD and atherogenic index of plasma (AIP) remains understudied. This research delves into the correlation between these two factors, aiming to shed new light on their potential association.

The relationship between AIP and CKD was evaluated using a weighted multivariate logistic regression model, and the curvilinear relationship between AIP and CKD was explored through smooth curve fitting. We engaged a recursive partitioning algorithm in conjunction with a two-stage linear regression model to precisely determine the inflection point. By conducting stratified analyses, the heterogeneity within subpopulations was explored.

In the regression model that accounted for all covariates, ORs (95% CI) for the association between CKD and AIP were 1.12 (0.91, 1.36), indicating no significant association between AIP and CKD. However, sensitivity analyses suggested that the relationship between them may be non-linear. Smooth curve analysis confirmed the non-linear relationship between AIP and CKD, identifying an inflection point at -0.55. Below this threshold, AIP exhibited a significant inverse correlation with CKD. Conversely, above this threshold, a pronounced positive correlation was detected. Stratified analyses elucidated that a non-linear association between AIP and CKD was observed among female participants and those aged 50 and above.

We found a curvilinear relationship between chronic kidney disease and atherogenic index of plasma.

Introduction

Chronic kidney disease (CKD) is a condition characterized by irreversibility and a progressive course of development, which significantly contributes to increased mortality from cardiovascular death and diabetes [ 1 ]. CKD imposes a substantial burden on global public health. An estimated 850 million individuals globally are afflicted with kidney disorders [ 2 ]. Risk factors for CKD include proteinuria, metabolic syndrome, diabetes, hypertension, advanced age, nephrotoxic drugs, etc. [ 3 ]. In recent years, there has been a growing recognition of the role that dyslipidemia plays in the pathogenesis of chronic kidney disease. Evidence is mounting that dyslipidemia significantly contributes to the development and progression of nephropathies. It is becoming clear that perturbations in lipid metabolism are associated with a deterioration of renal function [ 4 ]. Renal disorders,in turn, can intensify metabolic imbalances. The studies conducted by Vaziri ND and colleagues have elucidated that nephrotic syndrome results in profound disruptions to lipid metabolism [ 5 ]. Early identification and intervention of these risk factors play a crucial role in preventing CKD and improving renal outcomes.

The plasma atherosclerosis index (AIP) was introduced by Dobiasova and Frohlich in 2001, not only reflecting the ratio of pro-atherosclerotic lipids to protective lipids in plasma but also indicating particle size and esterification rate of HDL-C particles [ 6 ]. Studies have demonstrated associations between AIP and various conditions. A recent systematic review and meta-analysis has reported notably higher AIP levels in individuals with Obstructive Sleep Apnea (OSA) [ 7 ]. Additionally, elevated AIP values have been found to be independently associated with coronary artery disease (CAD) [ 8 ]. The AIP also stands out as a trustworthy biomarker for diagnosing Non-Alcoholic Fatty Liver Disease (NAFLD) [ 9 ].

Preliminary explorations into the relationship between AIP and the onset of CKD have been conducted. Evidence suggests that elevated AIP levels are correlated with an increased risk of CKD among adults with metabolic disorders [ 10 ]. Particularly, the risk of diabetic kidney disease (DKD) escalates significantly with higher AIP values, proposing its potential as a biomarker for early renal impairment [ 11 ]. Nonetheless, the current body of research exploring the connection between AIP and the initiation or progression of CKD remains scarce, resulting in a constrained comprehension of their association. Consequently, leveraging data from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2003 to 2020 in the United States, the present study embarked on a cross-sectional investigation to elucidate the association between AIP and CKD. The objective was to yield fresh evidence that could inform lipid management interventions for the treatment of CKD.

Materials and methods

Study participants.

Our data comes from the NHANES database in the United States. The data covers nine periods from 2003 to 2020. Demographic, lifestyle, and blood biochemical data on the U.S population were collected through home visits, mobile screening centers (MECs), and laboratory tests. This is an open database that researchers can access without any permission. The survey protocol was approved by the National Center for Health Statistics Research Ethics Review Board, and written informed consent was obtained from all participants involved. To safeguard the privacy of the participants, all personal identifying information was de-identified. In data processing, we excluded 38,416 subjects < 18 years of age, 6447 subjects lacking CKD data, 26639 subjects lacking  TG or HDL-C data, 482 subjects pregnant women, leaving 23888 subjects to participate in our study (Fig. 1 ).

Flow chart of sample selection from the 2003-2020

Study variables

Definition of chronic kidney disease.

CKD definition adheres to the guidelines provided by the Kidney Disease: Improving Global Outcomes (KDIGO) Glomerular Diseases Work Group. A diagnosis of CKD is warranted with the fulfillment of one or more of the following conditions for a period of three months or more: 1. An estimated glomerular filtration rate (eGFR) that is persistently below 60 mL/min/1.73 m2, as determined by the CKD Epidemiology Collaboration (CKD-EPI) creatinine equation. 2. A urine albumin-to-creatinine ratio (UACR) that surpasses the threshold of 30 mg/g [ 12 ].

Definition of atherogenic index of plasma

AIP represents a quantitative metric for evaluating lipid profiles, calculated from the ratio of fasting triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C) following logarithmic transformation. The AIP was determined using the formula: AIP = Log [TG (mmol/L) / HDL-C (mmol/L)] [ 13 , 14 ]. HDL-C and TC were meticulously assessed by specialists, who were trained in accordance with the rigorous standards set by the National Center for Health Statistics (NCHS) and executed under the guidance of the Centers for Disease Control and Prevention (CDC) protocols. The blood lipid levels were measured from peripheral blood samples collected in the morning after at least 8 h of fasting. Enzymatic methods were used to determine the serum levels of triglycerides. High-density lipoprotein cholesterol (HDL-C) in serum is quantified using either direct immunoassay or precipitation techniques.

Assessment of other variables

CDC systematically and comprehensively collected demographic, lifestyle, self-reported health, physical measurements, and biochemical data from participants in the form of personal interviews using computer assistance. In our study, the main demographic variables needed were participants' age, sex, race, education, marriage, and income-poverty ratio; The lifestyle variables we took into account were participants' smoking status, drinking status and recreational activities; Self-reported health conditions included diabetes, hypertension and cardiovascular disease. Physical variables included body mass index (BMI); Biochemical detection variables included hemoglobin, triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), serum uric acid (SUA), blood urea nitrogen (BUN), serum creatinine (SCR), urinary albumin (on-site collection). Smoking status: Never: By now, participants had smoked fewer than 100 cigarettes; Former: Participants had a history of smoking but did not currently smoke; "Now": Participants are still smoking [ 15 ]. Engage in recreational activities: “Yes” and “no.” Diabetes diagnosis (Including pre-diabetes): At least one of the following is present.1. Fasting blood glucose (FPG > 7.0 mmol/L). 2. Glycosylated hemoglobin HbA1c (> = 6.5%). 3. Random blood glucose (> = 11.1 mmol/ L). 4. Two hours OGTT blood glucose (> = 11.1 mmol/ L). 5. Doctor tells you have diabetes. 6.IFG (6.11 mmol/L <  = FPG <  = 7.0 mmol/L) or IGT (7.7 mmol/L <  = OGTT <  = 11.1 mmol/L). High blood pressure: At least one of the following occurs. 1. Systolic blood pressure ≥ 140 mmHg. 2. Diastolic blood pressure ≥ 90 mmHg. 3. Taking blood pressure medications 4. Self-report hypertension. Alcohol consumption: heavy (women: ≥ 3 drinks per day or ≥ 4 drinks on the same occasion; For men: ≥ 4 cups per day or ≥ 5 cups on the same occasion; Binge drinking ≥ 5 days per month); Moderate (women: ≥ 2 cups per day; For men: ≥ 3 cups per day; Binge drinking ≥ 2 days per month);Light (women: 1 cup per day; Men: 2 cups per day); never (< 12 drinks in a lifetime);Former (Participants had a history of drinking but did not currently drink). CVD was identified through a medical status questionnaire that recorded whether participants had been diagnosed by a physician with conditions such as coronary artery disease, congestive heart failure, or heart attack [ 16 ].

Statistical analysis

The study data were appropriately weighted to ensure representation. Participants were grouped based on the presence or absence of chronic kidney disease, according to their baseline characteristics. Data presentation was structured as follows: continuous variables were described using means ± standard errors, and categorical variables were represented as percentages. Weighted logistic regression analyses were used to explore the relationship between CKD and AIP. We used odds ratios (ORs) and 95% confidence interval (95% CI) to report results. A linear trend test was used to investigate the stability of the relationship between AIP and CKD. The nonlinear relationship between CKD and AIP was evaluated by restricted cubic spline analysis. Recursive algorithm and a two-stage linear regression model were utilized to calculate the curve inflection point. Stratified analysis was employed to assess the presence of specific populations.

Baseline characteristics

Table 1 presents the demographic and clinical profiles of the enrolled participants. Comparatively, participants diagnosed with CKD manifest higher levels of age, BMI, BUN, SCR, SUA, and AIP, while exhibiting reduced income levels, hemoglobin, and LDL-C concentrations. Among female participants, participants with no recreational activities, diabetes, hypertension, and heart disease had a higher proportion of CKD.

Association between AIP and CKD

In Model 1, with no covariate adjustments, ORs (95%CI) were 2.00 (1.81, 2.20), signifying a doubling of the risk for CKD with each unit increment in AIP (Table 2 ). Upon covariate adjustment for age, sex, and ethnicity in Model 2, the OR (95% CI) escalated to 2.18 (1.94, 2.43), denoting a 118% elevation in CKD risk for every unit increase in AIP. In Model 3, after comprehensive adjustment for sex, age, ethnicity, BMI, educational attainment, poverty income ratio, marital status, smoking behavior, recreational activities, hemoglobin levels, LDL-C, SUA, SCR, BUN, as well as diabetes, hypertension, and cardiovascular diseases, the OR (95% CI) moderated to 1.12 (0.91, 1.36), suggesting a lack of significant association between AIP and the risk of CKD. Sensitivity analyses, contrasting the reference quartile Q1, yielded ORs (95% CI) of 0.91 (0.78, 1.07), 0.92 (0.78, 1.08), and 1.10 (0.93, 1.31) for quartiles Q2, Q3, and Q4, respectively. These findings intimate a potential non-linear relationship between AIP levels and the incidence of CKD.

Stratified analyses by sex and age, with all covariates accounted for, revealed a significant positive correlation between AIP and CKD uniquely within the cohort aged less than 50 years. Conversely, stratified analyses across other age and sex did not demonstrate a significant association between AIP and CKD.

We conducted an extensive analysis to elucidate the non-linear correlation between AIP and CKD, after rigorously controlling for a spectrum of confounding variables. These included age, sex, ethnicity, poverty income ratio, educational level, marital status, smoking behavior, recreational activities, BMI, LDL-C, SUA, SCR, BUN, hypertension, diabetes, and CVD. Our findings, illustrated in Fig. 2 , reveal a non-linear association between AIP and CKD, with a significant inflection point identified at -0.55. Below this threshold, OR (95% CI) were 0.14 (0.04, 0.54), signifying a pronounced negative correlation. Above the inflection point, the ORs (95% CI) were 1.25 (1.01, 1.55), indicating a substantial positive correlation, as detailed in Table  3 .

The association between AIP and CKD

Stratified analyses by sex and age demarcated distinct patterns of association. In female participants and individuals over 50 years of age, a non-linear relationship was observed, while a linear relationship was noted in men and participants under 50 years old (Figs. 3 and 4 ). Female participants exhibited an inflection point at -0.57, with ORs (95% CI) of 0.15 (0.03, 0.86), suggesting an 85% decrease in CKD risk per unit increase in AIP below this threshold. Post-inflection, the ORs (95% CI) was 1.38 (1.01, 1.89), reflecting a 38% increase in CKD risk for each unit increment in AIP. In participants over 50, the inflection point was -0.55, with ORs (95% CI) of 0.05 (0.01, 0.27), indicating a 95% reduction in CKD risk per unit increase in AIP below this point. Beyond the inflection, the ORs (95% CI) was 1.08 (0.83, 1.42), which suggests a not significant association between AIP and CKD risk.

Association between AIP and CKD stratified by sex (a female; b male). In the subgroup analysis stratified by sex, the model is not adjusted for sex

Association between AIP and CKD stratified by age (a age > = 50 ;b age < 50). In the subgroup analysis stratifed by age, the model is not adjusted for age

This extensive study encompassed 23888 participants from the United States. We discovered a non-linear relationship between CKD and the plasma atherosclerosis index, with an inflection point at -0.55. Before this inflection point, a significant negative correlation was observed between the plasma atherosclerosis index and CKD; however, following the inflection point, a significant positive correlation was noted. As far as we are aware, our research stands as the most comprehensive study of its kind to date.

Although research on the correlation between AIP and CKD is limited, the association between lipids and chronic kidney disease has been extensively studied. A study from China by Oh et al. found a nonlinear relationship between the two [ 10 ]. They found that the critical threshold for the atherosclerosis index to be associated with the composite kidney outcome is 0.51. They observed that as the AIP exceeded 0.51, the risk ratio for composite renal outcomes significantly increased with higher AIP levels. A retrospective analysis by Toth PP and colleagues has identified hypertriglyceridemia as a significant potential risk factor for the development of kidney disease [ 17 ]. A retrospective investigation led by Jairoun AA and colleagues has revealed that statin therapy potentially arrests the progression of renal function deterioration, thus providing additional validation to our conclusions from an alternative vantage point [ 18 ].

The potential pathogenic mechanisms linking AIP with CKD remain unclear. The negative correlation observed below the inflection point potentially links to the adverse impacts of malnutrition and systemic inflammation on renal function [ 19 ]. The positive correlation observed beyond the inflection point may be attributed to several potential mechanisms. Firstly, genetic factors are pivotal. For instance, the SNP rs12951387 site predisposes individuals to obesity, which in turn triggers a cascade of metabolic disruptions, including the abnormal accumulation of lipids, resistance to insulin, imbalances in adipokine function, and the activation of inflammatory signaling pathways [ 20 ]. Secondly, an overabundance of caloric intake can lead to the anomalous deposition of lipids within the kidneys, inciting inflammatory responses within these tissues [ 21 ]. Inflammation and metabolic disorders are intrinsically linked in the complex relationship between AIP and CKD. The inflammatory process is mediated through the adipose-kidney axis [ 20 ]. In the context of metabolic dysregulation, adipose tissue hypertrophy and the aggregation of M1 macrophages can induce insulin resistance, leading to adipokine dysfunction and dyslipidemia. These conditions further propagate lipotoxicity, insulin resistance, and inflammatory responses. Studies have demonstrated that the buildup of TG can trigger the generation of reactive oxygen species, which in turn causes an increase in the permeability of the glomerular filtration barrier, resulting in renal tubular injury and interstitial fibrosis [ 22 ]. Concurrently, the lipotoxicity of TG may induce mitochondrial dysfunction within cells, which in turn can lead to an exacerbation of lipid deposition [ 23 ]. Adipose tissue-derived factors such as leptin, Tumor Necrosis Factor (TNF), and angiotensin II contribute to oxidative stress, inflammation, and the progression of fibrotic scarring, culminating in damage to both the glomeruli and renal tubules [ 24 ]. Moreover, Endothelial activation and systemic endothelial dysfunction are pivotal in the interplay between kidney disease and AIP. These endothelial changes can precipitate lipid transport impairments and instigate oxidative stress and inflammation, thereby aggravating the injury to glomeruli and tubules [ 25 ]. Studies have demonstrated that sustained endothelial alterations can identify patients with Minimal Change Disease (MCD) or Secondary Nephrotic Syndrome (SSNS) who are at an elevated risk of progression to Focal Segmental Glomerulosclerosis (FSGS) or the advanced stages of chronic kidney disease [ 26 ]. Additionally, CKD can reciprocally elevate levels of TG and decrease HDL-C. Hypertriglyceridemia (HTG) arises from impaired metabolism of Very-Low-Density Lipoprotein (VLDL) and diminished activity of Lipoprotein Lipase (LPL). The reduction in HDL-C is correlated with a decrease in Lecithin Cholesterol Acyltransferase (LCAT). This reduction in LCAT activity impacts the expression of the liver’s apolipoprotein A-I (apoA-I) gene and LCAT mRNA, resulting in diminished HDL-C levels [ 27 ].

Upon stratification by sex and age, distinct variations were observed in the association between AIP and CKD across different groups. In the sex-specific analysis, a nonlinear relationship was evident between AIP and CKD among female participants, whereas a straightforward linear association was noted among male participants. Furthermore, age-stratified analysis has demonstrated a direct linear correlation between AIP and CKD in participants aged 50 years or younger. Above this age threshold, a significant non-linear association has emerged, with an inflection point identified at -0.55. Existing research has consistently revealed pronounced disparities in lipid metabolism between the sexes. A cross-sectional study conducted by Yadegar A et al. revealed that HDL-C levels significantly decrease with the progression of CKD stages in males, while no such change is observed in females [ 28 ]. Dyslipidemia has been shown to induce inflammation, endoplasmic reticulum stress, and consequently, insulin resistance [ 29 ]. Inflammatory status, oxidative stress, and insulin resistance show pronounced disparities across genders and age groups [ 30 ]. These factors could potentially explain the noted differences.

Our research has delineated a sophisticated curvilinear relationship between AIP and CKD, underscoring the pivotal regulatory effects of gender and age on their dynamic interaction. The clinical relevance of our study results underscores the essential role of individualized lipid management in the trajectory of CKD.

Our data is derived from NHANES database, renowned for its stringent data collection protocols and extensive sample sizes, which lend considerable credibility and reliability to our findings. Utilizing stratified and subgroup analyses, we have delved into the nexus between AIP and CKD, as well as scrutinized the variations in this relationship across diverse demographic groups. Nevertheless, our research is not without its inherent limitations. Firstly, as a cross-sectional observational study, it does not establish a causal link between CKD and AIP, underscoring the necessity for longitudinal research to ascertain causality and the chronological order of events. Secondly, despite accounting for a range of covariates, there may remain unmeasured confounding factors influencing the relationship between AIP and CKD, including personal lifestyle choices and genetic propensities. Thirdly, disparities in socioeconomic status and healthcare access could affect the outcomes of the study. Urgently needed are robust longitudinal studies to substantiate our findings and clarify the long-term implications of the AIP-CKD relationship, essential for enhancing predictive modeling and tailoring clinical preventive and therapeutic approaches.

This investigation, drawing on data from NHANES between 2003 and 2020, has revealed a nonlinear association between AIP and CKD, characterized by an inflection point at -0.55. Below this threshold, there was a significant negative correlation between AIP and CKD. In contrast, above this inflection point, a significant positive correlation was observed. This finding carries profound implications for clinical practice, especially in the meticulous management of lipid profiles in CKD patients. The revealed nonlinear relationship between AIP and CKD emphasizes the critical role of individualized lipid management strategies in curbing the disease's progression, highlighting the need for precise lipid regulation.Our study enriches the scientific comprehension of the AIP-CKD nexus and offers actionable insights for clinical decision-making. The ultimate objective is to prevent or decelerate the advance of CKD, aiming to enhance patient outcomes and improve the quality of care in the management of this debilitating condition.

Availability of data and materials

The datasets generated and analysed during the current study are publicly available from the National Center for Health Statistics: wwwn.cdc.gov/nchs/nhanes/Default.aspx .

Data availability

No datasets were generated or analysed during the current study.

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The authors express their gratitude to the NHANES database for their uploading valuable datasets.

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Wang, B., Jiang, C., Qu, Y. et al. Nonlinear association between atherogenic index of plasma and chronic kidney disease: a nationwide cross-sectional study. Lipids Health Dis 23 , 312 (2024). https://doi.org/10.1186/s12944-024-02288-6

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Epidemiological analysis of chronic kidney disease from 1990 to 2019 and predictions to 2030 by Bayesian age-period-cohort analysis

Boqing dong.

a Department of Renal Transplantation, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China

Yuting Zhao

b Department of Gynecologic Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

c Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China

Huanjing Bi

Jingwen wang, xiaoming ding, associated data.

This work used the resource from the Global Burden of Disease Study ( https://www.healthdata.org/research-analysis/gbd ). All resources are free to obtain online.

Chronic Kidney Disease (CKD) has emerged as a significant global health issue. This study aimed to reveal and predict the epidemiological characteristics of CKD.

Data from the Global Burden of Disease Study spanning the years 1990 to 2019 were employed to analyze the incidence, prevalence, death, and disability-adjusted life year (DALY) of CKD. Joinpoint analysis assessed epidemiological trends of CKD from 1990 to 2019. An age-period-cohort model evaluated risk variations. Risk factor analysis uncovered their influences on DALYs and deaths of CKD. Decomposition analysis explored the drivers to CKD. Frontier analysis evaluated the correlations between CKD burden and the sociodemographic index (SDI). A Bayesian Age-Period-Cohort model was employed to predict future incidence and death of CKD.

In 2019, there were 18,986,903 incident cases, 697,294,307 prevalent cases, 1,427,232 deaths, and 41,538,592 DALYs of CKD globally. Joinpoint analysis showed increasing age-standardized rates of CKD incidence, prevalence, mortality, and DALY from 1990 to 2019. High systolic blood pressure significantly contributed to CKD-related deaths and DALYs, particularly in the high SDI region. Decomposition analysis identified population growth as the primary driver of CKD incident cases and DALYs globally. Countries like Nicaragua showed the highest effective differences, indicating room for improvement in CKD management. By 2030, while incident cases of CKD were predicted to rise, the global deaths might decrease.

Conclusions

The study revealed a concerning upward trend in the global burden of CKD, emphasizing the need for targeted management strategies across different causes, regions, age groups, and genders.

Introduction

Chronic kidney disease (CKD) is a leading cause of global mortality among non-communicable diseases, characterized by a sustained decline in glomerular function and elevated levels of albuminuria [ 1 , 2 ]. According to the international guidelines, CKD is defined by the presence of markers of kidney damage or a glomerular filtration rate (GFR) of less than 60 mL/min per 1.73 m 2 for three months or longer [ 3 ]. Once diagnosed with CKD, patients typically require lifelong renal replacement therapy (RRT), such as kidney transplantation or dialysis, imposing a significant burden on healthcare systems [ 4 ]. The decline in kidney function escalates the risk for cardiovascular morbidity and mortality, making CKD not only a direct cause of death but also a potent risk multiplier for other non-communicable diseases [ 5 , 6 ].

The epidemiology of CKD is complex and varies by region, presenting challenges for medical interventions across diverse geographical regions [ 7 ]. Variability contributing to CKD epidemiology encompasses regional disparities, differing disease definitions, and variations in the utilization of one-time testing for kidney function or albuminuria in determining CKD prevalence in epidemiological research [ 7 ]. The Global Burden of Disease Study (GBD) provides a comprehensive framework for understanding these discrepancies and predicting future trends of CKD [ 8 ]. This study aimed to offer an overview of CKD epidemiology by analyzing its incidence, prevalence, death, and disability-adjusted life year (DALY). Our goal was to offer an understanding of the changing epidemiological characteristics of CKD, facilitating better-targeted interventions and resource allocation for managing this global health challenge.

Materials and methods

Data sources.

The data utilized in this study were obtained from the GBD 2019, which provided epidemiological data across 204 countries and territories worldwide [ 8 ]. The definition of CKD used in the GBD study differs from that in the KDIGO guidelines [ 1 , 3 ]. The GBD definition relies on a single measurement of estimated glomerular filtration rate (eGFR) and albumin-to-creatinine ratio (ACR), which does not meet the KDIGO criteria requiring abnormalities to persist for over three months and consider other markers of kidney damage. The incidence, prevalence, death, DALY, and risk factors of CKD were extracted using the GBD Results Tool [ 9–11 ]. The risk factors of DALYs and deaths were displayed as attributable percent. Furthermore, the computation of DALYs involved summing two components: years lived with disability (YLD) and years of life lost (YLL) [ 8 ]. Age-standardized rates (ASRs) for CKD, including age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), age-standardized mortality rate (ASMR), and age-standardized DALY rate (ASDR), were calculated through the direct method, with the GBD 2019 world population as the standard reference [ 12 ]. The certainty of estimates was represented by the uncertainty interval (UI). Each estimate in the GBD was calculated 1000 times. The 95% UI was then determined by taking the 25th and 975th values after sorting these 1000 results from smallest to largest. To explore differences in the burden of CKD based on per capita income, educational attainment, and fertility rates, all countries were categorized into five groups according to the sociodemographic index (SDI), including high SDI, high-middle SDI, middle SDI, low-middle SDI, and low SDI [ 13 ].

Joinpoint analysis

We utilized Joinpoint analysis to identify significant temporal turning points in global ASR from 1990 to 2019. The average annual percent change (AAPC) was employed to describe the average annual percentage change in ASR over specified time intervals, while the annual percent change (APC) quantified the percentage variation in ASR within specific time segments.

Age-period-cohort analysis

To illustrate the evolving trends in CKD incidence and mortality from 1990 to 2019, we conducted an age-period-cohort analysis using a tool developed by Rosenberg and his colleagues [ 14 ]. Age effects denote variations associated with individual aging processes, while period effects encompass external factors that uniformly influence outcomes across all age groups during specific calendar periods. Cohort effects represent the cumulative impact of all unique exposures experienced by a cohort from birth.

Decomposition analysis

Decomposition analysis in epidemiology decomposed changes in health indicators, revealing the influence of factors such as population growth, aging, risk factors, or medical advancements [ 15 ]. We evaluated the contributions of various factors, including population growth, aging, and epidemiological changes. Furthermore, in analyzing DALYs, we deconstructed the epidemiological changes, by categorizing them into specific etiological factors such as glomerulonephritis, hypertension, type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), and other causes.

Frontier analysis

Frontier analysis was performed to identify the minimum achievable DALYs based on development levels [ 16 ]. This analysis defines a frontier that represents the lowest possible DALYs for each country or territory given its SDI. The distance from this frontier, referred to as the effective difference, indicates potential opportunities for reducing CKD DALYs in relation to a country or region’s developmental status. We employed data envelopment analysis with the free disposal hull method to delineate a non-linear frontier for ASDR using data from 1990 to 2019 [ 13 , 17 , 18 ]. To account for uncertainty, we generated 100 bootstrapped samples by randomly sampling with replacement across all countries and years. The mean CKD DALYs at each SDI value from these bootstrapped samples were then smoothed using LOESS regression [ 13 ]. Super-efficient countries were excluded to prevent outliers from distorting the frontier. Finally, we calculated the effective difference for each country or territory using 2019 SDI and ASDR data, with those below the frontier assigned a zero distance.

The Bayesian Age-Period-Cohort model

The Bayesian Age-Period-Cohort (BAPC) model integrates age, period, and cohort effects to analyze and predict disease trends, accounting for demographic changes [ 19 ]. This model offers a nuanced approach to projecting disease trends by considering the complex interplay of demographic shifts over time. In this study, we applied the BAPC model to forecast incidence and death from 2020 to 2030. All statistical analyses and visualizations were performed using R statistical software program (version 4.1.3), with statistical significance defined as a two-sided p  < 0.05.

The global incidence, prevalence, death, and DALY of CKD from 1990 to 2019

The global maps of ASIR and ASDR of CKD in 2019 are shown in Figure 1(A,B) , respectively. The higher ASIRs per 100,000 population (271.7–561.4) were mainly found in regions such as Australia, North America, and northern Africa, while the higher ASDRs per 100,000 population (1154.8–2162.7) were mainly found in regions such as North and South America, and the Middle East. There were 18,986,903 (95% UI = 17,556,534–20,518,156) incident cases, 697,294,307 (95% UI = 650,045,551–741,080,754) prevalent cases, 1,427,232 (95% UI = 1,313,735–1,524,548) deaths, and 41,538,592 (95% UI = 38,291,808–45,037,864) DALYs globally in 2019 ( Table 1 ). ASIR, ASPR, ASMR, and ASDR of CKD per 100,000 population were 233.7 (95% UI = 165.7–311.1), 8600.3 (95% UI = 7107.1–10,278.2), 18.3 (95% UI = 16.3–19.8), and 515.0 (95% UI = 454.0–588.1) globally in 2019, respectively. The ASIR per 100,000 population (281.8, 95% UI = 202.5–374.4) in the high SDI region and ASPR per 100,000 population (9495.7, 95% UI = 7836.9–11,361.4) in the middle SDI region, as well as the ASMR per 100,000 population (25.3, 95% UI = 22.1–28.4) and ASDR per 100,000 population (682.6, 95% UI = 593.9–779.2) in the low SDI region, surpassed global levels and other SDI regions. In the low SDI region, the ASR per 100,000 population for ASIR (161.4, 95% UI = 112.7–216.8) and ASPR (7060.4, 95% UI = 5781.8–8514.9) showed the lowest levels. In comparison, the ASMR per 100,000 population (11.8, 95% UI = 10.4–12.9) in the high-middle SDI region and ASDR per 100,000 population (304.3, 95% UI = 260.2–358.8) in the high SDI region reported the lowest levels worldwide, respectively.

Global ASIR (A) and ASDR (B) of CKD in 2019 (per 100,000 population). ASIR: age-standardized incidence rate; ASDR: age-standardized disability-adjusted life year rate; CKD: chronic kidney disease.

The incidence, prevalence, death, DALY, and age-standardized rates, and their temporal trends of chronic kidney disease*.

SDI: social-demographic index; UI: uncertainty interval; ASIR: age-standardized incidence rate; ASPR: age- standardized prevalence rate; ASMR: age- standardized mortality rate; DALYs: disability-adjusted life years; ASDR: age-standardized disability-adjusted life year rate; EAPC: estimated annual percentage change; CI: confidence interval.

According to the analysis of the trends of ASR ( Table 1 ), global ASIR (estimated annual percentage change (EAPC) =0.69, 95% confidence interval (CI) = 0.67–0.72), ASPR (EAPC = 0.31, 95% CI = 0.30–0.32), ASMR (EAPC = 0.73, 95% CI = 0.61–0.86), and ASDR (EAPC = 0.45, 95% CI = 0.34–0.56) illustrated an increasing trend from 1990 to 2019. Within five SDI quantiles, the middle SDI region displayed the highest absolute EAPCs for ASIR (EAPC = 1.14, 95% CI = 1.03–1.25) and ASPR (EAPC = 0.43, 95% CI = 0.40–0.47). The high SDI region exhibited the highest absolute EAPCs for ASMR (EAPC = 1.13, 95% CI = 0.82–1.45) and ASDR (EAPC = 0.78, 95% CI = 0.52–1.05), indicating the most rapid increase in burden. To assess the trends in the ASR over time from 1990 to 2019, Joinpoint analysis was used ( supplemental Table S1 and Figure S1 ). The AAPCs for ASIR, ASPR, ASMR, and ASDR were consistent with the findings from EAPCs. The ASIR and ASPR of females were consistently higher than males, while ASMR and ASDR of males were lower than those of females from 1990 to 2019. A significant temporal turning point was found in the APC for ASMR globally in 2014. From 1990 to 2014, the global ASMR gradually increased, but after this turning point, the ASMR began to decline (−0.39, 95% CI = −0.58 to −0.20, p  < 0.001).

Incidence, prevalence, death, and DALY of CKD by age and SDI from 1990 to 2019

From 1990 to 2019, there was a consistent increase in CKD incident and prevalent cases across all age groups ( supplemental Figure S2A-B ). In 2019, the highest number of incident cases was observed in the age group of 65 and older (10,479,450, 95% UI = 7,587,790–13,721,140), surpassing the incident cases in both the age groups of less than 40 years (1,702,782 95% UI = 1,084,820–2,450,023) and 40–64 years (6,804,674, 95% UI = 4,789,427–9,106,637). As for prevalent cases from 1990 to 2019, the age group of 40-64 consistently remained higher compared to the other two age groups in all periods, reaching 273,676,189 (95% UI = 220,227,928–335,989,767) in 2019.

From 1990 to 2019, the global deaths and DALYs of CKD exhibited consistent upward trajectories across all age groups ( supplemental Figure S2C-D ). The highest number of CKD-related deaths was observed in the age group of 65 years and older, while the age group of 40-64 exhibited the highest DALYs from 1990 to 2019. Notably, the 40–64 age group consistently had higher DALYs compared to both the younger than 40 years and older than 65 years age groups, reaching 16,463,816 (95% UI = 14,658,979–18,775,233) in 2019 globally.

Age-period-cohort analyses on incidence and mortality of CKD

In the age-period-cohort analysis of CKD incidence among the global population from 1990 to 2019, a unimodal pattern was observed in age-specific incidence rate ( Figure 2(A) ). Between the ages of 0 and 84, the incidence rate of CKD gradually increased with age. However, beyond this age range, the incidence rate began to decline as individuals continued to age. In contrast to the unimodal pattern of incidence rate, the global CKD mortality rate demonstrated a consistent upward trend with increasing age ( Figure 2(D) ).

Age-period-cohort analysis of incidence (A–C) and mortality (D–F) of CKD in the globe, 1990–2019. Longitudinal age curves of incidence rate (A) and mortality rate (D). Period effects are displayed by the relative risk of incidence rate ratio (B) and mortality rate ratio (E) by comparing age-specific rates between 1990–1994 (the reference period) and 2015–2019. Cohort effects are determined by comparing the relative risk of incidence rate ratio (C) and mortality rate ratio (F) between the 1890 cohort and the 2019 cohort, with the 1985 cohort as the reference point. The dots and shaded areas represent the rate or rate ratio and their corresponding 95% CIs. CKD: chronic kidney disease; SDI: sociodemographic index; CIs: confidence intervals.

Regarding the period effect, the incidence rate ratio of CKD consistently increased globally from 1990 to 2019 ( Figure 2(B) ). In contrast, the global mortality rate ratio exhibited a complex trend, with an initial decrease followed by an increase, reaching 1.02 (95% CI = 1.00–1.03) in the years 2000 to 2004, and subsequently showing a decline ( Figure 2(E) ). The incidence rate ratio of CKD showed a rising trend across birth cohorts globally ( Figure 2(C) ). The mortality rate ratio for cohorts born after 1890 increased with each successive birth cohort until it reached 1.16 (95% CI = 1.10–1.22) for the 1955 to 1964 cohort, after which it began to steadily decline ( Figure 2(F) ).

Risk factors attributable to the burden of CKD

The contributions of risk factors to deaths and DALYs of CKD are displayed in Figure 3 . Globally, high systolic blood pressure (Deaths, 61.6%; DALYs, 51.8%) was the most common contributing factor to deaths and DALYs of CKD globally, followed by high fasting plasma glucose (Deaths, 34.2%; DALYs, 31.5%) and high body-mass index (BMI) (Deaths, 27.8%; DALYs, 27.2%). In 2019, compared to other SDI regions, diet high in sodium contributed more significantly to deaths (8.1%) and DALYs (8.7%) of CKD in the high-middle SDI region, while low temperature had a greater impact on deaths (8.9%) and DALYs (6.3%) of CKD in the high SDI region.

Percentage of seven risk factors for the burden of CKD. CKD: chronic kidney disease.

Decomposition analysis in epidemiology of incident cases and DALYs of CKD

A decomposition analysis of CKD incident cases was conducted globally, across five SDI regions, and within six WHO regions to investigate the impact of aging, population growth, and epidemiologic change from 1990 to 2019. On a global scale, population growth was the primary driver, contributing to 41.31% of the increased incident cases between 1990 and 2019 ( Figure 4 and supplemental Table S2 ).

Changes in the incident cases of CKD according to the three causes from 1990 to 2019 at the global level and by SDI quintile and WHO regions. The black dot represents the overall value of incidence change contributed from all causes. CKD: chronic kidney disease; SDI: sociodemographic index; WHO: World Health Organization. Specific data is presented in supplemental Table S2 .

As shown in Figure 5 and supplemental Table S3 , population growth was also the primary driver of the global increase in DALYs, contributing 63.20% to the rise in DALYs from 1990 to 2019. However, in the high SDI region (38.13%), Western Pacific Region (63.79%), and European Region (53.91%), aging was the predominant driver. Conversely, in the low SDI region (−2.20%) and African Region (−2.60%), aging was a negative driver for DALYs. To further analyze the driving forces of DALYs between 1990 and 2019 by different etiologies, epidemiological changes were decomposed into five detailed causes of CKD. Globally, T2DM was the most significant driver among the five diseases, accounting for 5.02%, followed closely by hypertension at 3.14%. The relative contribution of T2DM to DALYs varied across different SDI regions, being higher in high SDI (11.69%), middle SDI (2.94%), and low-middle SDI regions (2.88%). In comparison, T2DM was a negative driver in the low SDI region (−0.68%).

Changes in DALYs of CKD according to seven causes from 1990 to 2019 at the global level and by SDI quintile and WHO regions. The black dot represents the overall value of DALYs change contributed from all causes. DALYs: disability-adjusted life years; CKD: chronic kidney disease; SDI: sociodemographic index; WHO: World Health Organization; T1DM: type 1 diabetes mellitus; T2DM: type 2 diabetes mellitus; GN: glomerulonephritis; HP: hypertension. Specific data is presented in supplemental Table S3 .

Frontier analysis of ASDR in CKD across different countries and regions

To investigate changing trends in CKD burden across various territories, a frontier analysis of ASDR spanning 204 countries and regions worldwide was conducted from 1990 to 2019. This analysis, which uses ASDR as a key metric for understanding the impact of CKD, delineates countries and regions along a frontier line based on their respective SDI levels ( Figure 6(A) ). The top five countries with the greatest effective difference from the frontier, ranging from 1816.76 to 2033.74 ( Figure 6(B) and supplemental Table S4 ), included Micronesia (Federated States of), Nicaragua, Mauritius, Palau, and Nauru. These nations exhibited a disproportionately higher ASDR compared to countries with similar sociodemographic resources. Conversely, the top five countries with the lowest ASDR within their development spectrum, with effective differences ranging from 0.00 to 42.51 included Somalia, Finland, Iceland, San Marino, and Belarus.

(A) Frontier analysis of CKD based on SDI and ASDR from 1990 to 2019. The color scale represents the years from 1990, depicted in black, to 2019, shown in blue. The frontier is delineated in a solid black color. (B) Frontier analysis based on SDI and CKD ASDR in 2019. The frontier line is black; countries and territories are represented as dots. The top 15 countries with the most considerable effective difference of ASDR from the frontier line are marked in black words; examples of the countries with low SDI (<0.5) and low effective difference are labeled in blue (e.g., Somalia, Niger, Burundi, Papua New Gui). Examples of countries and territories with high SDI (>0.85) and relatively high effective distance for their level of development are labeled in red (e.g., United Arab Emirates, Taiwan (Province of China), United States of America, Kuwait, Singapore). Red dots indicate an increase in ASDR of CKD from 1990 to 2019; blue dots indicate a decrease in ASDR of CKD between 1990 and 2019. CKD: chronic kidney disease; SDI: sociodemographic index; ASDR: age-standardized disability-adjusted life year rate. Specific data is presented in supplemental Table S4 .

Prediction of incidence and deaths of CKD using the Bayesian Age-Period-Cohort model

The BAPC model was employed to predict the evolving global trends in the incidence of CKD from 2020 to 2030 ( Figure 7 and supplemental Table S5 ). The global incidence rate per 100,000 population is expected to increase from 234.72 (95% CI = 135.40–586.10) in 2020 to 246.36 (95% CI = 0.93–2973.94) in 2030. The global incident cases will also increase from 19,627,543 (95% CI = 19,332,649–19,922,437) in 2020 to 26,346,589 (95% CI = 22,303,728–30,389,451) in 2030. This trend is consistent across different genders and SDI. Subsequently, based on mortality rate and deaths from 1990 to 2019, predictions were made for the global death trends of CKD from 2020 to 2030 ( supplemental Figure S3 and Table S6 ). By 2030, the global mortality rate per 100,000 population will decrease from 18.45 (95% CI = 1.23–543.11) in 2020 to 17.41 (95% CI = 0.00–5203.99) in 2030. Meanwhile, the global deaths were expected to increase from 1,483,812 (95% CI = 1,452,296–1,515,327) in 2020 to 1,924,241 (95% CI = 1,541,145–2,307,336) in 2030.

The trends of incident cases and ASIR in CKD in the globe and five SDI regions by sex, 1990–2030. ASIR: age-standardized incidence rate; CKD: chronic kidney disease; SDI: sociodemographic index; ASR: age-standardized rate. Specific data is presented in supplemental Table S5 .

In the predicted year 2030, the global incidence rate per 100,000 population is expected to be higher in females (251.78, 95% CI = 213.35–290.21) than in males (239.44, 95% CI = 202.48–276.41), with the number of incident cases also higher in females (14,330,860, 95% CI = 12,143,305–16,518,416) compared to males (12,015,729, 95% CI = 10,160,423–13,871,035). However, the mortality rate per 100,000 population is anticipated to be higher in males (20.82, 95% CI = 16.90–24.74) than in females (15.58, 95% CI = 12.30–18.85), with the number of deaths also expected to be greater in males (991,441, 95% CI = 804,591–1,178,290) than in females (932,800, 95% CI = 736,554–1,129,046).

While previous studies have utilized GBD data to explore the epidemiology of CKD, many were either descriptive or focused on specific aspects of the disease ( supplemental Table S7 ). For instance, Hu et al. concentrated on glomerulonephritis-induced CKD, emphasizing its significant burden in low SDI regions [ 20 ]. Similarly, Qing et al. and Feng et al. mapped the global burden of CKD using GBD 2019 data but did not investigate the potential drivers of CKD burden growth or predict future trends [ 21 , 22 ]. In contrast, our study provides more comprehensive analysis covering 204 countries and territories, offering a global perspective on CKD’s burden. We employed a variety of statistical methods, including decomposition analysis, frontier analysis, and BAPC modeling. These approaches allowed us to identify the primary drivers of CKD burdens, assess the efficiency of CKD management in relation to sociodemographic development, and predict future trends in CKD incidence and mortality. From 1990 to 2019, there was a notable rise in the burden of CKD, evidenced by its increased incidence, prevalence, mortality, and DALYs. On a global scale, in 2019, there were over 18 million new cases of CKD, reflecting a 69% increase, with 697 million prevalent cases, marking a 31% rise. Additionally, CKD accounted for nearly 1.4 million deaths, signifying a 73% surge, and resulted in 41 million years of healthy life lost, representing a 45% uptick. The BAPC model predicted a consistent increase of incidence and death from 2020 to 2030, reinforcing the persistent need for effective CKD management on a global scale.

In 2019, high systolic blood pressure was identified as a major risk factor of deaths and DALYs attributed to CKD globally. This finding is consistent with previous prospective observational studies that demonstrated a strong association between elevated blood pressure and the risk of CKD and end-stage renal disease (ESRD) [ 23 , 24 ]. Additionally, decomposition analysis highlighted hypertension as a key contributor to the global increase in CKD-related DALYs. These findings emphasize the critical importance of blood pressure management in the prevention and treatment of CKD. Hypertension and CKD often coexist, with poor blood pressure control significantly elevating the risk of developing cardiovascular and cerebrovascular complications [ 25 , 26 ]. The KDIGO guidelines recommend intensified antihypertensive therapy for CKD patients, targeting blood pressure control at 120/80 mmHg [ 27 ], while the European Renal Association advocated the use of ambulatory blood pressure monitoring with a target of 130/80 mmHg in patients on chronic dialysis [ 28 ]. Although intensified blood pressure control has not been conclusively shown to improve renal function, it reduces the incidence of cardiovascular complications [ 26 , 29 ]. Public health policies should prioritize early detection and management of hypertension among CKD patients, incorporating regular blood pressure monitoring and individualized antihypertensive therapy. Furthermore, public health initiatives should encourage lifestyle interventions, such as sodium reduction and fluid management. Given the challenges with patient compliance, especially concerning sodium intake, educating CKD patients to adopt and maintain these lifestyle changes is necessary [ 28 ]. Effective management of hypertension through a combination of pharmacological and non-pharmacological strategies can significantly reduce the burden of CKD and improve patient outcomes.

High fasting plasma glucose emerged as another significant risk factor contributing to the global burden of CKD in 2019. Decomposition analysis further identified T2DM as the primary driver of the increasing burden from 1990 to 2019. According to the International Diabetes Federation data in 2021, the global adult population with diabetes has reached 537 million and is expected to continue rising [ 30 ]. In the United States, nearly one-fourth of healthcare costs were related to T2DM, with a significant portion of these expenses attributable to T2DM-related CKD [ 31 ]. These results indicated that the burden of T2DM and T2DM-related CKD has been increasing year by year, leading to significant personal and social burdens. Public health policies for T2DM patients should emphasize early detection and glycemic control to prevent the development of CKD. Regular kidney function screening and provision of renal protective treatments, such as ACE inhibitors and SGLT2 inhibitors, could reduce CKD incidence [ 32 ]. Diabetic nephropathy (DN) is a complication of diabetic microvascular disease and has become one of the leading causes of ESRD. To prevent the progression of DN and the subsequent cardiovascular morbidity and mortality, it is crucial to implement personalized treatment, including strict blood glucose control, blood pressure management through RAAS inhibitors, aspirin, and lipid-lowering drugs [ 33 ]. Our study also found that in the low SDI region, T2DM was a negative driver of the increase in CKD burden from 1990 to 2019. It is necessary to cautiously interpret this result, as data collection and T2DM diagnosis in the low SDI region may be inadequate. Additionally, due to a lack of medical resources, T2DM patients may die prematurely from other infectious diseases before progressing to CKD, masking T2DM’s contribution to CKD burden [ 34 ]. Therefore, when formulating CKD-related health policies in the low SDI region, it is important to consider data quality and the most urgent health challenges faced by the local population.

From 1990 to 2019, ASIR and ASPR of CKD continued to rise for both males and females, while the ASDR and ASMR have shown a declining trend. Notably, the ASIR has consistently been higher in females. In contrast, males had higher ASDR and ASMR, indicating their worse outcomes. These gender differences were also found in the results by the BAPC model predictions, which indicated a higher incidence rate and incident cases of CKD in females, while mortality rates and deaths were higher in males. Previous epidemiological studies have also shown that CKD prevalence was generally higher in females, but kidney function declined faster in males [ 35 , 36 ]. The underlying reasons for this epidemiological difference between genders in CKD remain largely unexplored. Potential factors include physiological and lifestyle differences, such as longer life expectancy in females, the impact of pregnancy and estrogen, the detrimental effect of testosterone on male renal function, and unhealthy lifestyle choices among males [ 37 ]. It is noteworthy that many studies have revealed that in some countries, there are more male CKD patients undergoing RRT than females [ 38 ]. These data suggested, on the one hand, that CKD progresses more rapidly in males, and on the other hand, it indicated that females may tend to opt for conservative treatment modalities. Data from deceased kidney transplantation in the United States indicated that both the absolute number and transplantation rate of females were lower than those of males [ 39 ]. The difference in RRT between genders needs to be interpreted cautiously, and it cannot be directly concluded that there was unfair CKD management between males and females because most of this data originated from the United States and lacked high-quality research reports from other regions. Given the epidemiological differences in CKD between genders, gender-specific preventive, diagnosis, and management measures for CKD are crucial. For females, early detection and prevention are crucial, with an emphasis on educating them about CKD risks and encouraging regular screenings to reduce higher incidence rates. In contrast, male-focused strategies should prioritize managing complications, particularly cardiovascular issues, and promoting lifestyle interventions to address the faster disease progression and higher mortality rates. Additionally, policies should ensure equitable access to RRT and consider gender disparities in kidney transplantation.

In 2019, the highest number of incidence cases was seen in individuals aged 65 and older, while this age group consistently displayed the highest CKD-related mortality. The Age-Period-Cohort analysis of CKD showed that the mortality rate of CKD consistently rose with age. Decomposition analysis identified aging as the primary driver of the increasing burden in the high SDI region. According to the results from the US Renal Data System, the prevalence of CKD among individuals aged 65 and older was 33.2% in 2020, compared to 9% among younger adults [ 40 ]. Additionally, with the global increase in life expectancy, it is projected that by 2050, people aged 65 and older will make up more than 16% of the global population, with about two-thirds of those over 60 years old living in low-middle income countries [ 41 ]. This poses significant challenges for the formulation of public health policies in these countries. There are several potential reasons why older adults are more susceptible to CKD, including the loss of functional nephrons and the common presence of chronic conditions such as cardiovascular diseases and atherosclerosis [ 42 ]. Early vascular aging, characterized by accelerated arterial stiffness and endothelial dysfunction, plays a critical role in CKD pathogenesis among the elderly [ 43 ]. Early vascular aging not only contributes to the progression of CKD but also exacerbates cardiovascular complications, further increasing mortality risk in this population. To enhance CKD management in the elderly, public health policies should consider adopting age-specific eGFR thresholds and biomarkers to improve diagnosis and stratification. Incorporating routine assessments of arterial stiffness and endothelial function into CKD screening could also improve risk stratification and prevent cardiovascular complications. Finally, comprehensive pharmacological treatments, including anti-aging drugs and integrated antihypertensive treatments for arterial stiffness, are essential to further reducing mortality and improving outcomes in the elderly population [ 44 ]. In countries where CKD medications are unaffordable, dietary and behavioral therapies like calorie restriction, regular exercise, and a protein-restricted diet can promote healthy aging and reduce CKD progression [ 45 , 46 ].

The epidemiological features of CKD vary globally, with the United States having a 14% prevalence, driven by factors like T2DM, hypertension, and obesity [ 47 , 48 ]. In East Asia, CKD also poses a significant health challenge, with an estimated prevalence of 28.7% [ 49 ]. Besides diabetes and high blood pressure, major contributors to CKD in Eastern Asia include exposure to renal toxic substances and high-salt diets [ 50–52 ]. The SDI, covering per capita income, education levels, and fertility rates, is important for understanding the epidemiological characteristics of CKD globally. Overall, as SDI increased, ASIR rose, while ASMR and ASDR decreased from 1990 to 2019. This phenomenon has complex reasons, including disparities in healthcare funding, diagnostic criteria, and data entry quality [ 53 ]. Decomposition analysis revealed differences in CKD burden increases among regions with different SDI levels. In high, high-middle, and middle SDI regions, aging is the primary driver of CKD incidence increase, whereas in low-middle and low SDI regions, population growth is the main factor. Regarding the increase in CKD-related DALYs, besides aging being the primary driver in high SDI regions, population growth predominantly drives this increase in other SDI regions, particularly in low SDI regions (109.32%). Considering these findings, attention to CKD in elderly populations is warranted in high SDI regions, along with encouraging optimized fertility rates [ 2 ]. Globally, T2DM and hypertension play the most significant role in increasing CKD-related DALYs in high SDI regions. Therefore, emphasis should be placed on managing these comorbidities and promoting healthy lifestyle habits in these regions [ 54 ]. In contrast, countries with lower SDI levels exhibit lower social development, making it challenging to meet the healthcare needs of CKD. The intervention measures should prioritize disease care, treatment management, and improvement of environmental sanitation conditions [ 55 ]. Frontier analysis assessed the burden of CKD in different countries and regions, identifying areas for improvement based on SDI evaluation. Our analysis indicated that some high SDI countries exhibit higher disease burdens, such as the United Arab Emirates, Qatar, and Guam, necessitating targeted healthcare policies to ensure appropriate CKD management. Conversely, high-SDI countries like Switzerland, Norway, and Monaco showed minimal disparities between frontier DALYs and ASDR, suggesting progress in CKD management and efficient utilization of healthcare resources. These interplays between socio-economic development, healthcare accessibility, and CKD burden underscored the demand for customized healthcare strategies in regions of varying developmental stages to address the evolving burden of CKD.

Our study has several limitations. First, the definition of CKD in GBD relies on a single measurement of eGFR and ACR, which allows for broader and more inclusive estimates of CKD prevalence, making it useful for capturing a wide range of cases globally. However, this approach may include individuals with temporary or reversible kidney issues, as it does not meet the KDIGO criteria requiring abnormalities to persist for over three months. Additionally, the GBD definition does not consider other kidney damage markers beyond ACR, which are often unreported in the epidemiological studies that inform disease prevalence estimates. Second, variations in data quality and regional registration systems within the GBD dataset may introduce biases and affect the precision of our results. While the GBD study provides a comprehensive and standardized approach to estimating risk factor exposure and attributable burdens, it is based on aggregated data, limiting the application of traditional methods for controlling confounding factors. Third, the uncertainty inherent in the BAPC model can result in wider confidence intervals. This is due to the model’s reliance on past trends, which may be increasingly affected by data sparsity and variability over longer time horizons. Additionally, unanticipated health events, such as the emergence of Corona Virus Disease 2019 and other infectious diseases, can disrupt healthcare systems and population health trends, impacting the accuracy of our predictions.

In conclusion, this study examined the epidemiological trends of CKD from 1990 to 2019 and projected them through 2030. The findings underscore the escalating global burden of CKD, driven by age, SDI, lifestyle changes, and gender. The Age-Period-Cohort analysis highlights the importance of age-specific preventive strategies. Effective management of blood pressure and blood glucose is essential, particularly in high SDI regions. Public health policies should prioritize early detection and the integration of CKD prevention into broader health initiatives, while addressing regional and demographic disparities to mitigate CKD’s future impact and improve global health outcomes.

Supplementary Material

Acknowledgments.

We express our gratitude to the personnel at the Institute for Health Metrics and Evaluation and their collaborators for their efforts in making these data publicly accessible. Their dedication to advancing our understanding of CKD is greatly appreciated.

Funding Statement

This work was supported by China Organ Transplantation Development Foundation Scientific research subject and Natural Science Foundation of China (NSFC-81970668).

Authors contributions

Boqing Dong and Yuting Zhao conceived and designed the study, collected and analyzed the data, and drafted the manuscript. Jiale Wang, Ruiyang Ma, and Cuinan Lu participated in study design, conducted experiments, analyzed data, and contributed to manuscript preparation. Huanjing Bi, Zuhan Chen, Jingwen Wang, and Ying Wang contributed to research design, literature review, and manuscript drafting and revision. Xiaoming Ding and Yang Li supervised the project, provided guidance on design and analysis, and critically revised the manuscript. All authors have read and approved the final manuscript, taking public responsibility for its integrity and accuracy.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement