Evidence map›Paper›PMID 35721706›Full record

ArticleFrontiers in endocrinology2022

Effect of Glomerular Filtration Rate by Different Equations on Prediction Models for End-Stage Renal Disease in Diabetes.

Liangjing Lv, Xiangjun Chen, Jinbo Hu, Jinshan Wu, Wenjin Luo, Yan Shen, Rui Lan, Xue Li, Yue Wang, Ting Luo and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Observational
  2. Article
  3. Article
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

13 authors at 2 institutions in 1 country.

Liangjing LvDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xiangjun ChenDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Jinbo HuDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Jinshan WuDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Wenjin LuoDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yan ShenDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Rui LanDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xue LiDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yue WangDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Ting LuoDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Shumin YangDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Qifu LiDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Zhihong WangDepartment of Endocrinology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
First Affiliated Hospital of Chongqing Medical University · CNChongqing Medical University · CN

Funding

Medical Research Council MC_PC_17228Medical Research Council MC_QA137853
6 · The paper itself

Abstract

Background and Objectives: The study aimed to evaluate the performance of a predictive model using the kidney failure risk equation (KFRE) for end-stage renal disease (ESRD) in diabetes and to investigate the impact of glomerular filtration rate (GFR) as estimated by different equations on the performance of the KFRE model in diabetes. Design Setting Participants and Measurements: A total of 18,928 individuals with diabetes without ESRD history from the UK Biobank, a prospective cohort study initiated in 2006-2010, were included in this study. Modification of diet in renal disease (MDRD), chronic kidney disease epidemiology collaboration (CKD-EPI) or revised Lund-Malmö (r-LM) were used to estimate GFR in the KFRE model. Cox proportional risk regression was used to determine the correlation coefficients between each variable and ESRD risk in each model. Harrell's C-index and net reclassification improvement (NRI) index were used to evaluate the differentiation of the models. Analysis was repeated in subgroups based on albuminuria and hemoglobin A1C (HbA1c) levels. Results: Overall, 132 of the 18,928 patients developed ESRD after a median follow-up of 12 years. The Harrell's C-index based on GFR estimated by CKD-EPI, MDRD, and r-LM was 0.914 (95% CI = 0.8812-0.9459), 0.908 (95% CI = 0.8727-0.9423), and 0.917 (95% CI = 0.8837-0.9496), respectively. Subgroup analysis revealed that in diabetic patients with macroalbuminuria, the KFRE model based on GFR estimated by r-LM (KFRE-eGFR Conclusions: In adults with diabetes, the r-LM equation performs better than the CKD-EPI and MDRD equations in the KFRE model for predicting ESRD, especially for those with macroalbuminuria and poor glycemic control (HbA1c >8.5%).

Indexed as

Diabetes MellitusKidney Failure, ChronicRenal Insufficiency, ChronicAdultGlomerular Filtration RateGlycated HemoglobinHumansProspective StudiesGlycated Hemoglobindiabetic kidney diseaseESRD prediction modelestimated GFRglomerular filtration raterevised Lund–Malmö equation

Identifiers

PMID35721706
PMCPMC9205244
OpenAlexW4281702655

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.