Evidence map›Paper›PMID 41802782›Full record

ArticleBMJ open2026

Trajectories of metabolic risk clusters and adverse outcomes in patients with chronic kidney disease: a prospective cohort study in Taiwan.

Wei-Cheng Lo, Mei-Yi Wu, Yi-Hsuan Roger Chen, Mai Szu Wu, Chung-Shun Wong

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Article in BMJ open, 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

5 authors.

Wei-Cheng Lo *Master Program in Applied Epidemiology, College of Public Health, Taipei Medical University, Taipei, Taiwan.ORCID http://orcid.org/0000-0002-4818-8263
Mei-Yi Wu *TMU Research Center of Urology and Kidney, Taipei Medical University, Taipei, Taiwan.
Yi-Hsuan Roger ChenDepartment of Environmental Health and Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Mai Szu WuTMU Research Center of Urology and Kidney, Taipei Medical University, Taipei, Taiwan.
Chung-Shun WongDivision of Emergency Medicine, Department of Emergency and Critical Care, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan johnson7617@tmu.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the association between longitudinal trajectories of metabolic risk clusters and the risk of progression to end-stage kidney disease (ESKD) and major adverse kidney events (MAKEs) in patients with chronic kidney disease (CKD).

designProspective registry-based cohort study.

settingSecondary and tertiary care settings in Taiwan, using data from a multidisciplinary pre-ESKD care programme.

participantsA total of 1494 adult patients with CKD stages 3b-5 enrolled in a structured pre-ESKD care programme. PRIMARY AND SECONDARY OUTCOME MEASURES: Time to initiation of dialysis (primary outcome) and time to MAKE, defined as a composite of dialysis initiation or all-cause mortality (secondary outcome). Group-based multitrajectory modelling was used to categorise longitudinal trajectories of metabolic risk clusters, including systolic blood pressure, fasting blood glucose and low-density lipoprotein (LDL) cholesterol.

resultsFour trajectory groups were identified: Group I had controlled blood pressure and glucose but elevated LDL (dialysis incidence: 19.5 per 1000 person-years); Group II had borderline-high blood pressure and elevated glucose (33.6 per 1000 person-years); Group III had controlled glucose and low LDL but borderline-high blood pressure (38.8 per 1000 person-years) and Group IV had controlled glucose but elevated blood pressure and LDL (46.7 per 1000 person-years). Compared with the other groups, Group I exhibited significantly longer dialysis-free and MAKE-free survival (log-rank test, p<0.001). With covariates adjusted for, Groups II (HR 1.02, 95% CI 0.52 to 2.00) and III (HR 1.46, 95% CI 0.85 to 2.52) showed non-significant elevations in dialysis risk, whereas Group IV (HR 1.96, 95% CI 1.01 to 3.78) exhibited a significantly higher risk compared with Group I. Similar patterns were observed for MAKE outcome, confirming the association between trajectory groups and adverse kidney events.

conclusionLongitudinal trajectories of metabolic risk cluster are associated with differential risks of CKD progression to ESKD and death. Our findings provide valuable insights into the monitoring of metabolic risk profiles over time in patients with CKD.

Indexed as

Kidney Failure, ChronicRenal Insufficiency, ChronicAgedBlood GlucoseBlood PressureCholesterol, LDLDisease ProgressionFemaleHumansHypertensionMaleMiddle AgedProspective StudiesRegistriesRenal DialysisRisk FactorsBlood GlucoseCholesterol, LDLBlood PressureChronic renal failureDiabetes Mellitus, Type 2Lipid disordersNephrology

Identifiers

PMID41802782
PMCPMC12983679

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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.