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Creatinine

Drugs and Chemicals · NLM MeSH · updated 2026-10-31 · version 1

Citations verified against PubMedNot yet clinician-reviewed10 referencesApproximately 5 min read

A waste product produced by dietary protein digestion and breakdown product of creatine phosphate in muscle.

Table of Contents

1. Definition2. Research landscape3. Reading the evidence4. Open-access studies5. Key reviews6. References7. About this article

Definition and research guide

This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.

Content available: 4 complete abstracts (1,026 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.

Definition

A waste product produced by dietary protein digestion and breakdown product of creatine phosphate in muscle. Creatinine levels in the blood can be an indicator of kidney function.

Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.

Also known as: 2-Amino-1-methyl-1,5-dihydro-4H-imidazol-4-one; Creatinine Sulfate Salt; Salt, Creatinine Sulfate; Sulfate Salt, Creatinine; Krebiozen.

Where it fits in the MeSH classification

Broader topics
Imidazoles

Related concepts

  • Creatine Phosphate
  • Kidney

Research landscape

PubMed indexes 66,252 records tagged with the MeSH heading “Creatinine” (counts retrieved 2026-10-31). 9,945 of them (15.0%) were published from 2020 onward, and the busiest period so far is through 1999 with 25,927 records.

Reviews account for 2,578 records (3.9%) and meta-analyses for 504. Randomized controlled trials number 3,608 (5.4%) as a share of all records on the topic.

PubMed records by publication periodthrough 1999: 25,927 records; 2000-2009: 13,330 records; 2010-2019: 17,050 records; 2020 onward: 9,945 records25,927through 199913,3302000-200917,0502010-20199,9452020 onward
Records in PubMed indexed with this heading, by publication period. Real counts from NCBI E-utilities; the final period covers only part of the current year. Volume reflects how much has been published, not how strong the evidence is.
Show the data
PeriodRecords
through 199925,927
2000-200913,330
2010-201917,050
2020 onward9,945
Share of records by publication typeReviews: 3.9 percent; Meta-analyses: 0.8 percent; Randomized controlled trials: 5.4 percentReviews3.9% (2,578)Meta-analyses0.8% (504)Randomized controlled trials5.4% (3,608)
Share of all PubMed records on this heading that carry each publication type. Types overlap with other records, so the shares do not sum to 100%.
Publication-type chart data
Publication types among 66,252 PubMed records
TypeRecordsShare
Reviews2,5783.9%
Meta-analyses5040.8%
Randomized controlled trials3,6085.4%

Method: PubMed query "Creatinine"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-31.

Reading the evidence in drugs and chemicals

Studies of a chemical or drug can answer very different questions: what it is and how it behaves in cells and animals, how the body handles it, and whether it changes outcomes in people. Laboratory and animal findings often do not carry over to patients, and observational studies of exposures are confounded by who uses a substance and why. Nothing on this page is a recommendation to use, avoid, start or stop any substance or medicine; talk to a qualified clinician or pharmacist about your own situation. Check the dose, the species, the comparison group and whether a patient-relevant outcome was measured.

Evidence from open-access studies

These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.

Study comparison — selected abstracts, not a systematic review
Study / authorsYearSource label / designEurope PMC citationsLicence / source
Machine learning derived serum creatinine trajectories in acute kidney injury in critically ill patients with sepsis
Takkavatakarn K, Oh W, Chan L, Hofer I, Shawwa K, Kraft M, et al.
2024Research article
Design not recorded in structured metadata
57cc by
PMID 38730421 · DOI · PMC11084026
The Metabolism of Creatinine and Its Usefulness to Evaluate Kidney Function and Body Composition in Clinical Practice
Ávila M, Mora Sánchez MG, Bernal Amador AS, Paniagua R
2025Review article
Design not recorded in structured metadata
51cc by
PMID 39858438 · DOI · PMC11764249
Creatinine, cystatin C, muscle mass, and mortality: Findings from a primary and replication population-based cohort
Groothof D, Shehab NBN, Erler NS, Post A, Kremer D, Polinder-Bos HA, et al.
2024Research article
Design not recorded in structured metadata
45cc by
PMID 38898741 · DOI · PMC11294032
Different eGFR markers and prediction of cardiovascular risk
Tydén M, Batra G, Fellström B, Held C, Lindbäck J, Soveri I, et al.
2026Randomized controlled trial
Design not recorded in structured metadata
3cc by
PMID 41273211 · DOI · PMC12678217

Machine learning derived serum creatinine trajectories in acute kidney injury in critically ill patients with sepsis [1]

Research article Takkavatakarn K, Oh W, Chan L, Hofer I, Shawwa K, Kraft M, et al. · · 2024 · cited 57 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundCurrent classification for acute kidney injury (AKI) in critically ill patients with sepsis relies only on its severity-measured by maximum creatinine which overlooks inherent complexities and longitudinal evaluation of this heterogenous syndrome.
Closing excerpt
ConclusionsThese 8 classes of AKI in critically ill patients with sepsis, stratified by early creatinine trajectories, were good predictors for key outcomes in patients with AKI in critically ill patients with sepsis independent of their AKI staging.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (266 words)

BackgroundCurrent classification for acute kidney injury (AKI) in critically ill patients with sepsis relies only on its severity-measured by maximum creatinine which overlooks inherent complexities and longitudinal evaluation of this heterogenous syndrome. The role of classification of AKI based on early creatinine trajectories is unclear.MethodsThis retrospective study identified patients with Sepsis-3 who developed AKI within 48-h of intensive care unit admission using Medical Information Mart for Intensive Care-IV database. We used latent class mixed modelling to identify early creatinine trajectory-based classes of AKI in critically ill patients with sepsis. Our primary outcome was development of acute kidney disease (AKD). Secondary outcomes were composite of AKD or all-cause in-hospital mortality by day 7, and AKD or all-cause in-hospital mortality by hospital discharge. We used multivariable regression to assess impact of creatinine trajectory-based classification on outcomes, and eICU database for external validation.ResultsAmong 4197 patients with AKI in critically ill patients with sepsis, we identified eight creatinine trajectory-based classes with distinct characteristics. Compared to the class with transient AKI, the class that showed severe AKI with mild improvement but persistence had highest adjusted risks for developing AKD (OR 5.16; 95% CI 2.87-9.24) and composite 7-day outcome (HR 4.51; 95% CI 2.69-7.56). The class that demonstrated late mild AKI with persistence and worsening had highest risks for developing composite hospital discharge outcome (HR 2.04; 95% CI 1.41-2.94). These associations were similar on external validation.ConclusionsThese 8 classes of AKI in critically ill patients with sepsis, stratified by early creatinine trajectories, were good predictors for key outcomes in patients with AKI in critically ill patients with sepsis independent of their AKI staging.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 38730421 · DOI · PMC11084026

The Metabolism of Creatinine and Its Usefulness to Evaluate Kidney Function and Body Composition in Clinical Practice [2]

Review article Ávila M, Mora Sánchez MG, Bernal Amador AS, Paniagua R · · 2025 · cited 51 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Serum creatinine levels are the most used clinical marker to estimate renal function as the glomerular function rate because it is simple, fast, and inexpensive.
Closing excerpt
The variability in the creatinine generation rate among individuals should be considered when assessing the glomerular function rate.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (151 words)

Serum creatinine levels are the most used clinical marker to estimate renal function as the glomerular function rate because it is simple, fast, and inexpensive. However, creatinine has limitations, as its levels can be influenced by factors such as advanced age, physical activity, protein-rich diets, male gender, medications, and ethnicity. Serum cystatin C and its combination with serum creatinine may serve as an alternative since these factors do not affect it. Most creatinine synthesis occurs in the muscles, making it a valuable marker for assessing lean body mass within body composition. This measurement is crucial for evaluating and monitoring nutritional status in patients with chronic kidney disease. This review aimed to discuss the literature on creatinine metabolism, its advantages and disadvantages in assessing renal function, and its utility in measuring lean body mass. The variability in the creatinine generation rate among individuals should be considered when assessing the glomerular function rate.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 39858438 · DOI · PMC11764249

Creatinine, cystatin C, muscle mass, and mortality: Findings from a primary and replication population-based cohort [3]

Research article Groothof D, Shehab NBN, Erler NS, Post A, Kremer D, Polinder-Bos HA, et al. · · 2024 · cited 45 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundSerum creatinine is used as initial test to derive eGFR and confirmatory testing with serum cystatin C is recommended when creatinine-based eGFR is considered less accurate due to deviant muscle mass.
Closing excerpt
The minimal association between serum cystatin C and muscle mass supports its increased use as a more reliable alternative in routine clinical practice.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (353 words)

BackgroundSerum creatinine is used as initial test to derive eGFR and confirmatory testing with serum cystatin C is recommended when creatinine-based eGFR is considered less accurate due to deviant muscle mass. Low muscle mass is associated with increased risk of premature mortality. However, the associations of serum creatinine and cystatin C with muscle mass and mortality remain unclear and require further investigation to better inform clinical decision-making.MethodsWe included 8437 community-dwelling adults enrolled in the Dutch PREVEND study and 5033 in the US NHANES replication cohort. Associations of serum creatinine and/or cystatin C with muscle mass surrogates and mortality were quantified with linear and Cox proportional hazards regression, respectively. Missing observations in covariates were multiply imputed using Substantive Model Compatible Fully Conditional Specification.ResultsMean (SD) age of PREVEND and NHANES participants (50% and 48% male) were 49.8 (12.6) and 48.7 (18.7) years, respectively. Median (Q1-Q3) serum creatinine and cystatin C were 71 (61-80) and 80 (62-88) μmol/L and 0.87 (0.78-0.98) and 0.91 (0.80-1.10) mg/L, respectively. Higher serum creatinine was associated with greater muscle mass, while serum cystatin C was not associated with muscle mass. Adjusting both markers for each other strengthened the positive relationship between serum creatinine and muscle mass and revealed an inverse association between serum cystatin C and muscle mass. In the PREVEND cohort, 1636 (19%) deaths were registered over a median follow-up of 12.9 (5.8-16.3) years with a 10-year mortality rate (95% CI) of 7.6% (7.1-8.2%). In the NHANES, 1273 (25%) deaths were registered over a median follow-up of 17.9 (17.3-18.5) years with a 10-year mortality rate of 13.8% (12.8-14.7%). Both markers were associated with increased mortality. Notably, when adjusted for each other, higher serum creatinine was associated with decreased mortality, while the association between serum cystatin C and increased mortality strengthened. The shapes of the associations in the PREVEND study and NHANES were almost identical.ConclusionsThe strong association between serum creatinine and muscle mass challenges its reliability as GFR marker, necessitating a more cautious approach in its clinical use. The minimal association between serum cystatin C and muscle mass supports its increased use as a more reliable alternative in routine clinical practice.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 38898741 · DOI · PMC11294032

Different eGFR markers and prediction of cardiovascular risk [4]

Randomized controlled trial Tydén M, Batra G, Fellström B, Held C, Lindbäck J, Soveri I, et al. · · 2026 · cited 3 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundRenal dysfunction increases cardiovascular (CV) risk.
Closing excerpt
eGFRcys had the strongest association; eGFRcr and eGFRratio added limited incremental value.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (256 words)

BackgroundRenal dysfunction increases cardiovascular (CV) risk. We compared cystatin C-based estimated glomerular filtration rate (eGFRcys), creatinine-based eGFR (eGFRcr), and their ratio (eGFRcys/eGFRcr) in relation to major adverse cardiovascular events (MACE) and all-cause mortality in chronic coronary syndrome, assessing the added prognostic value of the eGFRratio.MethodsIn this post hoc analysis of 14,513 Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy trial patients, we investigated associations between baseline eGFRcys, eGFRcr, their ratio, and MACE and all-cause death using Cox regression models, unadjusted and adjusted for eGFRcys, eGFRcr, and their combination. Discrimination was assessed using Harrell's C-index; added value by the fraction of new information (FNI).ResultsMedian age was 65 years; 82% were male. Median eGFRcys was 77 (interquartile range [IQR]: 61-94) and eGFRcr 79 (IQR: 65-91) mL/min/1.73 m2. Over 3.7 years, 1449 MACE and 1063 deaths occurred. Lower eGFR values and eGFRratio were associated with increased MACE risk, primarily driven by CV death. For eGFRcys 60 versus 90, the hazard ratio (HR) for MACE adjusted for eGFRcr was 1.77 (95% CI: 1.49-2.09, FNI 54%). In contrast, eGFRcr adjusted for eGFRcys showed no positive association (HR 0.82, 95% CI: 0.68-0.97, FNI 3%). A lower eGFRratio was linked to higher MACE risk (HR 1.99, 95% CI: 1.80-2.21), which remained after eGFRcr adjustment (HR 1.89, 95% CI: 1.70-2.10, FNI 54%) but was attenuated after eGFRcys adjustment (HR 1.29, 95% CI: 1.13-1.46, FNI 5%).ConclusionIn chronic coronary syndrome, lower eGFRcys, eGFRcr, and eGFRratio were associated with higher MACE and mortality risk. eGFRcys had the strongest association; eGFRcr and eGFRratio added limited incremental value.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41273211 · DOI · PMC12678217

Key reviews and meta-analyses

The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.

  • Research article Creatine and creatinine metabolism [5]
    Wyss M, Kaddurah-Daouk R · Physiol Rev · 2000 · cited 2,025 times (Europe PMC)
  • Research article Cystatin C versus creatinine in determining risk based on kidney function [6]
    Shlipak MG, Matsushita K, Ärnlöv J, Inker LA, Katz R, Polkinghorne KR, et al. · N Engl J Med · 2013 · cited 751 times (Europe PMC)
  • Research article Acute kidney injury in sepsis [7]
    Bellomo R, Kellum JA, Ronco C, Wald R, Martensson J, Maiden M, et al. · Intensive Care Med · 2017 · cited 568 times (Europe PMC)
  • Research article Interpretation of urine results used to assess chemical exposure with emphasis on creatinine adjustments: a review [8]
    Boeniger MF, Lowry LK, Rosenberg J · Am Ind Hyg Assoc J · 1993 · cited 532 times (Europe PMC)
  • Research article Serum creatinine and renal function [9]
    Levey AS, Perrone RD, Madias NE · Annu Rev Med · 1988 · cited 404 times (Europe PMC)
  • Research article Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes: An Individual-Participant Data Meta-Analysis [10]
    Writing Group for the CKD Prognosis Consortium, Grams ME, Coresh J, Matsushita K, Ballew SH, Sang Y, et al. · JAMA · 2023 · cited 339 times (Europe PMC)

References

  1. Takkavatakarn K, Oh W, Chan L, Hofer I, Shawwa K, Kraft M, et al.. Machine learning derived serum creatinine trajectories in acute kidney injury in critically ill patients with sepsis. . 2024. PMID 38730421 · DOI · PMC11084026
  2. Ávila M, Mora Sánchez MG, Bernal Amador AS, Paniagua R. The Metabolism of Creatinine and Its Usefulness to Evaluate Kidney Function and Body Composition in Clinical Practice. . 2025. PMID 39858438 · DOI · PMC11764249
  3. Groothof D, Shehab NBN, Erler NS, Post A, Kremer D, Polinder-Bos HA, et al.. Creatinine, cystatin C, muscle mass, and mortality: Findings from a primary and replication population-based cohort. . 2024. PMID 38898741 · DOI · PMC11294032
  4. Tydén M, Batra G, Fellström B, Held C, Lindbäck J, Soveri I, et al.. Different eGFR markers and prediction of cardiovascular risk. . 2026. PMID 41273211 · DOI · PMC12678217
  5. Wyss M, Kaddurah-Daouk R. Creatine and creatinine metabolism. Physiol Rev. 2000. PMID 10893433 · DOI
  6. Shlipak MG, Matsushita K, Ärnlöv J, Inker LA, Katz R, Polkinghorne KR, et al.. Cystatin C versus creatinine in determining risk based on kidney function. N Engl J Med. 2013. PMID 24004120 · DOI · PMC3993094
  7. Bellomo R, Kellum JA, Ronco C, Wald R, Martensson J, Maiden M, et al.. Acute kidney injury in sepsis. Intensive Care Med. 2017. PMID 28364303 · DOI
  8. Boeniger MF, Lowry LK, Rosenberg J. Interpretation of urine results used to assess chemical exposure with emphasis on creatinine adjustments: a review. Am Ind Hyg Assoc J. 1993. PMID 8237794 · DOI
  9. Levey AS, Perrone RD, Madias NE. Serum creatinine and renal function. Annu Rev Med. 1988. PMID 3285786 · DOI
  10. Writing Group for the CKD Prognosis Consortium, Grams ME, Coresh J, Matsushita K, Ballew SH, Sang Y, et al.. Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes: An Individual-Participant Data Meta-Analysis. JAMA. 2023. PMID 37787795 · DOI · PMC10548311

About this article

Sources
NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
Verification
Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
Review state
automated source verified; no human expert review has been recorded yet.
Version
1, last updated 2026-10-31.

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At a glance

66,252
PubMed records on this heading
15%
published since 2020
2,578
review articles
3,608
randomized trials
10
verified references below

Counts come from PubMed on 2026-10-31; they show how much has been written, not how strong the evidence is.

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