Evidence map›Paper›PMID 42393550›Full record

ArticleBMC nephrology2026

The impact of serum myokine profile on the outcome of peritoneal dialysis patients.

Lixing Xu, Jack Kit-Chung Ng, Gordon Chun-Kau Chan, Winston Wing-Shing Fung, Wing-Fai Pang, Kai-Ming Chow, Cheuk-Chun Szeto

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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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Lixing XuCarol & Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, Shatin, Hong Kong, China.
Jack Kit-Chung NgCarol & Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, Shatin, Hong Kong, China.
Gordon Chun-Kau ChanCarol & Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, Shatin, Hong Kong, China.
Winston Wing-Shing FungCarol & Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, Shatin, Hong Kong, China.
Wing-Fai PangCarol & Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, Shatin, Hong Kong, China.
Kai-Ming ChowCarol & Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, Shatin, Hong Kong, China.
Cheuk-Chun SzetoCarol & Richard Yu Peritoneal Dialysis Research Centre, Department of Medicine & Therapeutics, Prince of Wales Hospital, Shatin, Hong Kong, China. ccszeto@cuhk.edu.hk.ORCID https://orcid.org/0000-0002-8898-8505

Funding

Chinese University of Hong Kong research accounts 3134257 and 3135822
6 · The paper itself

Abstract

backgroundPeritoneal dialysis (PD) patients are at high risk for complications such as muscle loss and peritonitis. Individual myokines and functional assessment of PD patients are inconsistently reported to associate with poor prognosis, but their complex interactions for risk stratification have not been studied.

methodsIn 194 new PD patients, we measured the serum levels of a myokine panel, metabolic and inflammatory markers, together with physical function scores. We employed k-cluster analysis on the result and analyzed patient survival, technique survival, peritonitis-free survival, hospitalisation rate and duration between the patient clusters.

resultsThere are two distinct patient clusters; cluster 1 showed a higher risk profile, with higher Morse Fall Scores, lower Norton scores, lower lean tissue mass, and different myokine levels. Cluster 2 is independently associated with better patient survival (adjusted hazard ratio 0.460, 95% confidence interval [CI] 0.237 to 0.894, p = 0.022) and peritonitis-free survival rate (AHR 0.417, 95% CI 0.205 to 0.846, p = 0.015). Cluster 2 also had lower hospitalisation rate (p = 0.022) and shorter duration of hospital stay (p = 0.014). Individual parameters used for the cluster analysis, however, were not independent predictors.

conclusionA combined assessment of myokine profile and functional status of new PD patients is independently associated with patient survival, peritonitis-free survival, and hospitalization rates. Our results underscore the importance of a comprehensive, integrated approach to patient assessment, which can improve the risk stratification for this vulnerable population.

Indexed as

Kidney Failure, ChronicMyokinesPeritoneal DialysisAgedBiomarkersCluster AnalysisFemaleHospitalizationHumansMaleMiddle AgedPeritonitisPrognosisTreatment OutcomeBiomarkersMyokinesChronic kidney diseaseDialysisEnd stage kidney failureFrailtyInflammationMalnutritionSarcopenia

Identifiers

PMID42393550
PMCPMC13602474

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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.