Evidence map›Paper›PMID 42516504›Full record

ArticleClinical kidney journal2026

Clinical factors associated with biased estimation of glomerular filtration rate: a cross-sectional study.

Alexandre Lahens, Emmanuelle Vidal-Petiot, Nahid Tabibzadeh, Anne Boutten, François Rouzet, Timothée Fearon, François Vrtovsnik, Martin Flamant, Jimmy Mullaert

Abstract read
In one paragraph

Article in Clinical kidney journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Alexandre LahensPhysiology Department, Assistance Publique Hôpitaux de Paris, Hôpital Bichat-Claude Bernard, Paris, France.
Emmanuelle Vidal-PetiotPhysiology Department, Assistance Publique Hôpitaux de Paris, Hôpital Bichat-Claude Bernard, Paris, France.ORCID https://orcid.org/0000-0001-9356-7302
Nahid TabibzadehPhysiology Department, Assistance Publique Hôpitaux de Paris, Hôpital Bichat-Claude Bernard, Paris, France.ORCID https://orcid.org/0000-0001-5803-0163
Anne BouttenBiochemistry Department, Assistance Publique Hôpitaux de Paris, Hôpital Bichat-Claude Bernard, Paris, France.
François RouzetUniversité Paris Cité, Mecidine UFR, Paris, France.
Timothée FearonPhysiology Department, Assistance Publique Hôpitaux de Paris, Hôpital Bichat-Claude Bernard, Paris, France.
François VrtovsnikUniversité Paris Cité, Mecidine UFR, Paris, France.
Martin FlamantPhysiology Department, Assistance Publique Hôpitaux de Paris, Hôpital Bichat-Claude Bernard, Paris, France.
Jimmy MullaertInstitut Curie, INSERM, U1331 Computational Oncology, Saint-Cloud, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and hypothesis: Equations estimating glomerular filtration rate (GFR) based on creatinine and/or cystatin C incorporate demographic variables such as age and sex. However, clinical determinants may lead to substantial bias in GFR estimation. We aimed to identify clinical factors associated with biased GFR estimation with the Modification of Diet in Renal Disease, Chronic Kidney Disease-Epidemiology Collaboration, and European Kidney Function Consortium equations. Methods: In this retrospective cross-sectional study, we included patients referred for GFR measurement from March 2008 to February 2024 in the Physiology unit of Bichat Hospital, Paris, France. GFR was measured as the urinary clearance of a radio-isotopic tracer and the error of estimated GFR (eGFR), was expressed as log(eGFR/measured GFR) and analyzed with linear regression models. Results: Among 3838 patients (mean age 51 ± 15 years, mean measured GFR 59 ± 26 ml/min/1.73 m²), several clinical variables were associated with significant estimation error in the multivariable analysis. For all creatinine-based equations, underestimation occurred with HIV infection, high BMI, loop diuretics, and cotrimoxazole use, while overestimation occurred with younger age, female sex, lower BMI, history of kidney transplantation, and cirrhosis. For all cystatin C-based equations, underestimation was associated with older age, HIV infection, corticosteroid use, and history of kidney transplantation; overestimation was associated with younger age, female sex, and sub-Saharan African origin. Equations using both biomarkers performed better in conditions affecting each biomarker in opposite directions. By cumulating several conditions, bias can vary from -50% to more than +50% leading to a completely erroneous GFR estimation. Conclusion: Common clinical features are independently associated with biased GFR estimation that can be of high clinical relevance, especially when cumulated. Our results guide GFR evaluation by giving a qualitative and most importantly quantitative estimation of the expected bias depending on individual patient profile and comorbidities.

Indexed as

CKD-EPI equationcreatininecreatinine clearancecystatin CGFR

Identifiers

PMID42516504
PMCPMC13403280

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.