Evidence map›Paper›PMID 41742052›Full record

ArticleBMC nephrology2026

A retrospective cohort study on the association between RAR and mortality in peritoneal Dialysis patients.

Mengwei Zhang, Zhouhao Ren, Shunshun Zhang, Yurui Lü, Ruting Fu, Shuwen Gong, Shuijuan Shen

Abstract read
In one paragraph

Article in BMC nephrology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mengwei ZhangDepartment of Nephrology, Shaoxing People's Hospital (The First Affiliated Hospital, Shaoxing University), Shaoxing, Zhejiang, 312000, P.R. China.
Zhouhao RenSchool of Medicine, Shaoxing University, Shaoxing, Zhejiang, 312000, P.R. China.
Shunshun ZhangSchool of Medicine, Shaoxing University, Shaoxing, Zhejiang, 312000, P.R. China.
Yurui LüSchool of Medicine, Shaoxing University, Shaoxing, Zhejiang, 312000, P.R. China.
Ruting FuSchool of Medicine, Shaoxing University, Shaoxing, Zhejiang, 312000, P.R. China.
Shuwen GongDepartment of Nephrology, Shaoxing People's Hospital (The First Affiliated Hospital, Shaoxing University), Shaoxing, Zhejiang, 312000, P.R. China.
Shuijuan ShenDepartment of Nephrology, Shaoxing People's Hospital (The First Affiliated Hospital, Shaoxing University), Shaoxing, Zhejiang, 312000, P.R. China. ssj72@163.com.

Funding

Shaoxing Health Science and Technology Project 2023SKY038Zhejiang Medical and Health Science and Technology Project 2023KY1244
6 · The paper itself

Abstract

backgroundInflammation and malnutrition collectively constitute the dual challenge that predominantly shapes the prognosis of peritoneal dialysis (PD) patients. As a composite biomarker, the red cell distribution width-to-albumin ratio (RAR) integrates these two pathological dimensions into a single numerical value. Although RAR has demonstrated superior prognostic value across multiple diseases, the association with mortality in the PD population remains unexplored.

methodsThis single-institution retrospective cohort investigation enrolled 394 individuals initiating peritoneal dialysis from January 2015 to December 2022 at Shaoxing People’s Hospital and followed them until May 2025. The optimal RAR cutoff for predicting mortality was established via ROC curve analysis, with discriminative performance evaluated based on the AUC value. Kaplan-Meier survival curves were plotted to compare survival rates between groups, with differences assessed using the log-rank test. Hazard ratios (HR) were calculated after adjusting for potential confounders via multivariate Cox proportional hazards regression models, supplemented by subgroup analyses and interaction analyses.

resultsOver the study period, 97 patients (24.6%) died. ROC analysis established 4.619 as the optimal RAR cutoff for mortality prediction, demonstrating significant discriminatory value with an AUC of 0.819 (P < 0.001). Compared with the C-reactive protein-to-albumin ratio and the prognostic nutritional index, RAR showed a better prognostic ability. When applying the cutoff of 4.619, patients with high RAR exhibited significantly worse survival (log-rank P < 0.001). The adjusted hazard ratio for all-cause mortality associated with high RAR was 2.498 (95% CI 1.887–3.306; P < 0.001), confirming a stable and significant association after controlling for multiple covariates. This association showed no significant heterogeneity across subgroups defined by different clinical characteristics, confirming the robustness of the finding.

conclusionBased on its significant association with all-cause mortality in peritoneal dialysis patients, RAR demonstrates potential as a practical tool for clinical risk stratification.

Indexed as

Kidney Failure, ChronicPeritoneal DialysisSerum AlbuminAdultAgedBiomarkersCohort StudiesC-Reactive ProteinFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesROC CurveBiomarkersC-Reactive ProteinSerum AlbuminAll-cause mortalityPeritoneal dialysisPrognosisRed cell distribution width-to-albumin ratio

Identifiers

PMID41742052
PMCPMC13003726

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