Evidence map›Paper›PMID 38689834›Full record

ArticleKidney medicine2024

External Validation of the Kidney Failure Risk Equation Among Urban Community-Based Chinese Patients With CKD.

Ling Pan, Jinwei Wang, Yang Deng, Yexiang Sun, Zhenyu Nie, Xiaoyu Sun, Chao Yang, Guohui Ding, Ming-Hui Zhao, Yunhua Liao and 1 more

Open access · goldAbstract read
In one paragraph

Article in Kidney medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 19% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

11 authors at 6 institutions in 1 country.

Ling PanRenal Division, Department of Medicine, Peking University First Hospital, Beijing, China.
Jinwei WangRenal Division, Department of Medicine, Peking University First Hospital, Beijing, China.
Yang DengRenal Division, the First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Yexiang SunYinzhou District Center for Disease Control and Prevention, Ningbo, China.
Zhenyu NieRenal Division, Ningbo Yinzhou No. 2 Hospital, Ningbo, China.
Xiaoyu SunNational Institute of Health Data Science at Peking University), Beijing, China.
Chao YangRenal Division, Department of Medicine, Peking University First Hospital, Beijing, China.
Guohui DingCollege of Computer Science, Shenyang Aerospace University, Shenyang, China.
Ming-Hui ZhaoRenal Division, Department of Medicine, Peking University First Hospital, Beijing, China.
Yunhua LiaoRenal Division, the First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Luxia ZhangRenal Division, Department of Medicine, Peking University First Hospital, Beijing, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNGuangxi Medical University · CNNingbo Center for Disease Control and Prevention · CNNingbo No. 2 Hospital · CNPeking University · CNShenyang Aerospace University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rationale & Objective: The Kidney Failure Risk Equations have been proven to perform well in multinational databases, whereas validation in Asian populations is lacking. This study sought to externally validate the equations in a community-based chronic kidney disease cohort in China. Study Design: A retrospective cohort study. Setting & Participants: Patients with and estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m Exposure: Age, sex, eGFR, and albuminuria were included in the 4-variable model, whereas serum calcium, phosphate, bicarbonate, and albumin levels were added to the previously noted variables in the 8-variable model. Outcome: Initiation of long-term dialysis treatment. Analytical Approach: Model discrimination, calibration, and clinical utility were evaluated by Harrell's C statistic, calibration plots, and decision curve analysis, respectively. Results: A total of 4,587 participants were enrolled for validation of the 4-variable model, whereas 1,414 were enrolled for the 8-variable model. The median times of follow-up were 4.0 (interquartile range: 2.6-6.3) years for the 4-variable model and 3.4 (2.2-5.6) years for the 8-variable model. For the 4-variable model, the C statistics were 0.750 (95% CI: 0.615-0.885) for the 2-year model and 0.766 (0.625-0.907) for the 5-year model, whereas the values were 0.756 (0.629-0.883) and 0.774 (0.641-0.907), respectively, for the 8-variable model. Calibration was acceptable for both the 4-variable and 8-variable models. Decision curve analysis for the models at the 5-year scale performed better throughout different net benefit thresholds than the eGFR-based (<30 mL/min/1.73 m Limitations: A large proportion of patients lack albuminuria measurements, and only a subset of population could provide complete data for the 8-variable equation. Conclusions: The kidney failure risk equations showed acceptable discrimination and calibration and better clinical utility than the eGFR-based strategy for incidence of kidney failure among community-based urban Chinese patients with chronic kidney disease.

Indexed as

CKDclinical utilityexternal validationkidney failurekidney failure risk equation

Identifiers

PMID38689834
PMCPMC11059393
OpenAlexW4393204524

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.