Impact of dietary component clusters identified by K-means++ on renal function decline in a Taiwanese cohort.

Shang-Feng Tsai, Wei-Ju Liu, Yu-Jung Lin, Chia-Lin Lee

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Article in Renal failure, 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 authors.

Shang-Feng TsaiDepartment of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan.ORCID 0000-0002-6119-0587

Wei-Ju LiuDepartment of Medical Research, Intelligent Data Mining Laboratory, Taichung Veterans General Hospital, Taichung, Taiwan.

Yu-Jung LinDepartment of Medical Research, Intelligent Data Mining Laboratory, Taichung Veterans General Hospital, Taichung, Taiwan.ORCID 0009-0003-9013-3252

Chia-Lin LeeDepartment of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung, Taiwan.ORCID 0000-0001-9146-5644

Funding

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6 · The paper itself

Abstract

Dietary intake influences renal health, but the impact of overall dietary patterns on renal outcomes remains unclear. The K-means++ algorithm, which improves the stability of traditional K-means clustering, may provide a robust approach for identifying real-world dietary behaviors. We analyzed 24,820 adults from the MJ Health Research Database in Taiwan. Dietary intake was assessed using a validated food frequency questionnaire, and patterns were derived with the K-means++ algorithm. Three clusters - non-healthy, normal, and healthy - were identified at baseline and follow-up. Renal outcomes were evaluated by estimated glomerular filtration rate (eGFR), with worsening defined as an annual decline >1 mL/min/1.73 m

Indexed as

Clustering AlgorithmsDietFeeding BehaviorGlomerular Filtration RateKidneyAdultCluster AnalysisCohort StudiesFemaleHumansMaleMiddle AgedTaiwandiet patternestimated glomerular filtration rate (eGFR)K-means++ algorithmPrincipal component analysis (PCA)renal function decline

Identifiers

PMID42226593

DOI10.1080/0886022X.2026.2667036

PMCPMC13231811

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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.