Evidence map›Paper›PMID 42014030›Full record

ArticleJournal of cachexia, sarcopenia and muscle2026

Longitudinal Study of Frailty Phenotype in Relation to Chronic Kidney Disease Incidence.

Yong-Xiang Ruan, Da-Chuan Guo, Wen-Hao Liu, Jia-Man Ou, Qi Guo, Jing-Wei Gao, Yang-Wei Cai, Mao-Xiong Wu, Xiao-Tian Liang, Jie-Wen Cai and 4 more

Abstract read
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

14 authors.

Yong-Xiang RuanDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Da-Chuan GuoDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Wen-Hao LiuDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Jia-Man OuDepartment of Cardiology, Yangjiang Hospital of Guangdong Medical University, Yangjiang, Guangdong, People's Republic of China.
Qi GuoDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Jing-Wei GaoDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Yang-Wei CaiDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Mao-Xiong WuDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Xiao-Tian LiangDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Jie-Wen CaiDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Pin-Ming LiuDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Jing-Feng WangDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.ORCID 0000-0002-5827-7876
Hai-Feng ZhangDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.
Yang-Xin ChenDepartment of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China.

Funding

National Natural Science Foundation of China 82070237National Natural Science Foundation of China 82170457National Natural Science Foundation of China 82271609National Natural Science Foundation of China 82371573
6 · The paper itself

Abstract

backgroundThe longitudinal relationship between frailty phenotype and CKD development, and the modifying role of genetic CKD risk in this association, remains unclear. Research on simple, noninvasive and quantifiable CKD prediction models incorporating frailty is limited.

methodsWe analysed 214 502 CKD-free participants from the UK Biobank cohort. Frailty was assessed using a modified phenotype with five components: weight loss, exhaustion, low grip strength, low physical activity and slow gait speed, to match UK Biobank data. Self-reported walking pace and weight change served as proxies where objective measures were unavailable. A polygenic risk score for CKD was calculated based on 258 single nucleotide polymorphisms. Cox proportional hazards models were used to assess the association between the frailty phenotype and new-onset CKD. The interaction between frailty and genetic risk on CKD outcomes was also examined. A noninvasive CKD prediction model, integrating frailty, age, gender, diabetes, hypertension, BMI and smoking status, was developed and validated internally using the UK Biobank and externally using CHARLS cohorts.

resultsAmong the 214 502 CKD-free participants with a median age of 57 (49-62) years, 50.3% were female. A total of 109 290 individuals (51.0%) were classified as non-frail, 96 941 (45.2%) as pre-frail and 8271 (3.9%) as frail. Over the course of a median follow-up period of 12.9 years, we documented 8079 (3.8%) cases of CKD. Compared with non-frailty, the hazard ratio (HR) for new-onset CKD in prefrailty and frailty was 1.143 (95% CI, 1.090-1.199, p < 0.001) and 1.606 (95% CI, 1.474-1.749, p < 0.001) in the multivariate model, respectively. Each one-point increase in frailty score was associated with a higher risk of CKD (HR = 1.142; 95% CI, 1.116-1.170, p < 0.001) in the multivariable model. Participants with frailty and high genetic risk had the greatest risk of CKD (HR = 1.981; 95% CI, 1.733-2.266, p < 0.001) compared with those without frailty and low genetic risk. In the simple CKD prediction model incorporating frailty, it demonstrated an AUC of 0.734 at 5 years, 0.745 at 8 years and 0.749 at 10 years in internal testing. External validation also showed consistent discrimination and calibration with an AUC of 0.740.

conclusionsPre-frail and frail phenotypes were associated with a higher risk of developing CKD, showing a dose-response relationship. A noninvasive prediction model incorporating frailty and clinical parameters exhibited stable discriminative performance over a decade in both European and Asian cohorts.

Indexed as

FrailtyRenal Insufficiency, ChronicFemaleGenetic Risk ScoreHumansIncidenceLongitudinal StudiesMaleMiddle AgedPhenotypeRisk FactorsUK BiobankUnited Kingdomchronic kidney diseasefrailty phenotypegenetic predispositionpredictive model

Identifiers

PMID42014030
PMCPMC13099170

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.