Evidence map›Paper›PMID 42693449›Full record

ArticleCardiovascular diabetology2026

Longitudinal inflammatory-metabolic-adiposity burden and incident heart failure across cardiovascular-kidney-metabolic stages: a prospective cohort study.

Fangyi Dai, Yong Dai

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Article in Cardiovascular diabetology, 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

2 authors.

Fangyi DaiDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China.
Yong DaiDepartment of Hepatobiliary Surgery, The Affiliated Hospital of Qinghai University, Xining, 810006, Qinghai, China. qhdaiyong@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHeart failure remains a major health burden among older adults. Although systemic inflammation, metabolic dysregulation, and central adiposity are individually recognized as heart failure risk factors, composite biomarkers capturing their longitudinal convergence and interaction with cardiovascular-kidney-metabolic (CKM) staging remain unexplored.

objectivesTo investigate the association of longitudinal CTGW composite index (C-reactive protein × triglyceride-glucose index × waist-to-height ratio) trajectories and cumulative burden with incident heart failure, and to examine effect modification by baseline CKM stage.

methodsThis prospective cohort study included 1946 participants aged 50 years and older from the English Longitudinal Study of Ageing, free of heart failure at Wave 2 (2004-2005), followed through Wave 8 (2016-2017). Group-based multi-trajectory modeling jointly classified longitudinal CRP, triglycerides, glucose, and WHtR across three waves. Cumulative CTGW burden was quantified using the trapezoidal rule. Cox proportional hazards regression with sequential adjustment and restricted cubic spline analyses were employed.

resultsOver a median follow-up spanning 12 years, 113 participants (5.8%) developed incident heart failure. Three distinct trajectories were identified: low-stable (n = 697, 35.8%), moderate-metabolic (n = 943, 48.5%), and high-inflammatory (n = 306, 15.7%). In fully adjusted models, the high-inflammatory trajectory conferred the greatest risk (HR = 2.69, 95% CI 1.46-4.93, P = 0.001), followed by the moderate-metabolic trajectory (HR = 1.96, 95% CI 1.17-3.29, P = 0.011). For cumulative burden, the highest quartile was significantly associated with incident heart failure (HR = 2.35, 95% CI 1.31-4.24, P = 0.004; P for trend < 0.001), with each standard deviation increase corresponding to 19% higher risk (HR = 1.19, 95% CI 1.04-1.36, P = 0.014). A nonlinear dose-response relationship was confirmed (P for nonlinearity = 0.032), with the risk threshold identified at approximately 8.2. Stratified analyses revealed significant effect modification by CKM stage (P for interaction = 0.031), with the strongest association observed in Stage 3-4 (HR = 2.37, 95% CI 1.24-4.53, P = 0.009). Subgroup analyses demonstrated consistent effect directions across age, sex, BMI, and comorbidity strata without significant interactions.

conclusionsLongitudinal CTGW trajectories and cumulative burden are independently associated with incident heart failure in a nonlinear dose-response manner, with the association amplified across advancing CKM stages, supporting the CTGW composite index as a potential integrative biomarker for heart failure risk stratification.

Indexed as

AdiposityHeart FailureInflammationInflammation MediatorsKidney DiseasesMetabolic SyndromeAgedBiomarkersBlood GlucoseC-Reactive ProteinEnglandFemaleHumansIncidenceLongitudinal StudiesMaleBiomarkersBlood GlucoseC-Reactive ProteinInflammation MediatorsTriglyceridesCardiovascular-kidney-metabolic syndromeCTGW composite indexGroup-based multi-trajectory modelingHeart failureLongitudinal cohort study

Identifiers

PMID42693449
PMCPMC13540904

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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.