Evidence map›Paper›PMID 35911392›Full record

ArticleFrontiers in medicine2022

Impact of Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) GFR Estimating Equations on CKD Prevalence and Classification Among Asians.

Bjorn Kaijun Betzler, Rehena Sultana, Feng He, Yih Chung Tham, Cynthia Ciwei Lim, Ya Xing Wang, Vinay Nangia, E Shyong Tai, Tyler Hyungtaek Rim, Mukharram M Bikbov and 5 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
6.0field-weighted citation impact, top 3% 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

27 citing papers in PubMed, 44 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

15 authors at 11 institutions in 7 countries.

Bjorn Kaijun BetzlerYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Rehena SultanaCentre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
Feng HeSingapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
Yih Chung ThamSingapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
Cynthia Ciwei LimDepartment of Renal Medicine, Singapore General Hospital, Singapore, Singapore.
Ya Xing WangBeijing Institute of Ophthalmology, Beijing Ophthalmology & Visual Sciences Key Laboratory, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Vinay NangiaSuraj Eye Institute, Nagpur, India.
E Shyong TaiDepartment of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Tyler Hyungtaek RimSingapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
Mukharram M BikbovUfa Eye Research Institute, Ufa, Russia.
Jost B JonasBeijing Institute of Ophthalmology, Beijing Ophthalmology & Visual Sciences Key Laboratory, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Se Woong KangDepartment of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Kyu Hyung ParkDepartment of Ophthalmology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, South Korea.
Ching-Yu ChengSingapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
Charumathi SabanayagamSingapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
Duke-NUS Medical School · SGNational University of Singapore · SGSingapore National Eye Center · SGCapital Medical University · CNSamsung Medical Center · KRSeoul National University Bundang Hospital · KRSingapore Eye Research Institute · SGSingapore General Hospital · SGSuraj Eye Institute · INUfa Eye Research Institute · RUUniversity Medical Centre Mannheim · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In 2021, the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) validated a new equation for estimated glomerular filtration rate (eGFR). However, this new equation is not ethnic-specific, and prevalence of CKD in Asians is known to differ from other ethnicities. This study evaluates the impact of the 2009 and 2021 creatinine-based eGFR equations on the prevalence of CKD in multiple Asian cohorts. Methods: Eight population-based studies from China, India, Russia (Asian), Singapore and South Korea provided individual-level data ( Findings: Of 67,233 adults, CKD prevalence was 8.6% ( Interpretation: eGFRcr (2021, AS) consistently provided reduced CKD prevalence and higher estimation of GFR among Asian cohorts than eGFRcr (2009, ASR). Based on current risk-stratified approaches to CKD management, more patients reclassified to lower-risk GFR categories could help reduce inappropriate care and its associated adverse effects among Asian renal patients. Comparison of both equations to predict progression to renal failure or adverse outcomes using prospective studies are warranted. Funding: National Medical Research Council, Singapore.

Indexed as

Asianchronic kidney diseasecreatininecystatin Cepidemiologyglomerular filtration rateprevalence

Identifiers

PMID35911392
PMCPMC9329617
OpenAlexW4285391358

What OpenQuestion holds

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Registered trials

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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.