Evidence map›Paper›PMID 26630928›Full record

ArticleBMC nephrology2015

The Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation does not improve the underestimation of Glomerular Filtration Rate (GFR) in people with diabetes and preserved renal function.

Richard J MacIsaac, Elif I Ekinci, Erosha Premaratne, Zhong X Lu, Jas-Mine Seah, Yue Li, Ray Boston, Glenn M Ward, George Jerums

Open access · goldAbstract read
In one paragraph

Article in BMC nephrology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 2 pooled it
3.7field-weighted citation impact, top 7% of its field
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

32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 70 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Richard J MacIsaacDepartment of Endocrinology and Diabetes, St Vincent's Hospital Melbourne, 4th Floor, Daly Wing, 35 Victoria Parade, PO Box 2900, Fitzroy, VIC, 3065, Australia. r.macisaac@unimelb.edu.au.
Elif I EkinciEndocrine Centre, Austin Health, West Heidelberg, 3081, Victoria, Australia. elif.ekinci@unimelb.edu.au.
Erosha PremaratneEndocrine Centre, Austin Health, West Heidelberg, 3081, Victoria, Australia. erosha.premaratne@gmail.com.
Zhong X LuMelbourne Pathology, Collingwood, 3066, Victoria, Australia. Zhong.Lu@mps.com.au.
Jas-Mine SeahEndocrine Centre, Austin Health, West Heidelberg, 3081, Victoria, Australia. jmseah@gmail.com.
Yue LiDepartment of Endocrinology and Diabetes, St Vincent's Hospital Melbourne, 4th Floor, Daly Wing, 35 Victoria Parade, PO Box 2900, Fitzroy, VIC, 3065, Australia. Yue.Lii@svha.org.au.
Ray BostonDepartment of Endocrinology and Diabetes, St Vincent's Hospital Melbourne, 4th Floor, Daly Wing, 35 Victoria Parade, PO Box 2900, Fitzroy, VIC, 3065, Australia. drrayboston@yahoo.com.
Glenn M WardDepartment of Endocrinology and Diabetes, St Vincent's Hospital Melbourne, 4th Floor, Daly Wing, 35 Victoria Parade, PO Box 2900, Fitzroy, VIC, 3065, Australia. Glenn.Ward@svha.org.au.
George JerumsEndocrine Centre, Austin Health, West Heidelberg, 3081, Victoria, Australia. g.jerums@unimelb.edu.au.
Austin Health · AUSt Vincent's Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOur hypothesis was that both the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations would underestimate directly measured GFR (mGFR) to a similar extent in people with diabetes and preserved renal function.

methodsIn a cross-sectional study, bias (eGFR - mGFR) was compared for the CKD-EPI and MDRD equations, after stratification for mGFR levels. We also examined the ability of the CKD-EPI compared with the MDRD equation to correctly classify subjects to various CKD stages. In a longitudinal study of subjects with an early decline in GFR i.e., initial mGFR > 60 ml/min/1.73 m(2) and rate of decline in GFR (ΔmGFR) > 3.3 ml/min/1.73 m(2) per year, ΔmGFR (based on initial and final values) was compared with ΔeGFR by the CKD-EPI and MDRD equations over a mean of 9 years.

resultsIn the cross-sectional study, mGFR for the whole group was 80 ± 2.2 ml/min/1.73 m(2) (n = 199, 75 % type 2 diabetes). For subjects with mGFR >90 ml/min/1.73 m(2) (mGFR: 112 ± 2.0, n = 76), both equations significantly underestimated mGFR to a similar extent: bias for CKD-EPI: -12 ± 1.4 ml/min/1.73 m(2) (p < 0.001) and for MDRD: -11 ± 2.1 ml/min/1.73 m(2) (p < 0.001). Using the CKD-EPI compared with the MDRD equation did not improve the number of subjects that were correctly classified to a CKD-stage. No biochemical or clinical patient characteristics were identified to account for the under estimation of mGFR values in the normal to high range by the CKD-EPI equation. In the longitudinal study (n = 30, 66 % type 1 diabetes), initial and final mGFR values were 102.8 ± 6 and 54.6 ± 6.0 ml/min/1.73 m(2), respectively. Mean ΔGFR (ml/min/1.73 m(2) per year) was 6.0 by mGFR compared with only 3.0 by MDRD and 3.2 by CKD-EPI (both p < 0.05 vs mGFR)

conclusionsBoth the CKD-EPI and MDRD equations underestimate reference GFR values > 90 ml/min/1.73 m(2) as well as an early decline in GFR to a similar extent in people with diabetes. There is scope to improve methods for estimating an early decline in GFR.

Indexed as

Glomerular Filtration RateAgedAustraliaBiomarkersComorbidityCreatinineCross-Sectional StudiesCystatin CDiabetes ComplicationsDiagnosis, Computer-AssistedEpidemiologic Research DesignFemaleHumansMaleMiddle AgedPrevalenceBiomarkersCreatinineCystatin C

Identifiers

PMID26630928
PMCPMC4668645
OpenAlexW2186157026

What OpenQuestion holds

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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 OpenQuestion graph.