ArticlePloS one2022
Multi-system trajectories and the incidence of heart failure in the Framingham Offspring Study.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Sex-specific longitudinal changes in resting heart rate and all-cause heart failure: insights from the HUNT study.Frontiers in cardiovascular medicine · 2026Article
- Global heart failure incidence rate: an updated systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2026Review
- Lipoprotein(a) and Heart Failure Among Black and White Participants in Atherosclerosis Risk in Communities Study, Framingham Offspring Study, and Multi-Ethnic Study of Atherosclerosis: The Pooling Project.Journal of the American Heart Association · 2025Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
backgroundHeart failure is a multi-system disease, with non-cardiac systems playing a key role in disease pathogenesis.
objectiveInvestigate whether longitudinal multi-system trajectories incrementally predict heart failure risk compared to single-occasion traits.
methodsWe evaluated 3,412 participants from the Framingham Heart Study Offspring cohort, free of heart failure, who attended examination cycle 5 and at least one examination between 1995-2008 (mean age 67 years, 54% women). We related trajectories for the following organ systems and metabolic functions to heart failure risk using Cox regression: kidney (estimated glomerular filtration rate), lung (forced vital capacity and the ratio of forced expiratory volume in one second/forced vital capacity), neuromotor (gait time), muscular (grip strength), cardiac (left ventricular mass index and heart rate), vascular function (pulse pressure), cholesterol (ratio of total/high-density lipoprotein), adiposity (body mass index), inflammation (C-reactive protein) and glucose homeostasis (hemoglobin A1c). Using traits selected via forward selection, we derived a trajectory risk score and related it to heart failure risk.
resultsWe observed 276 heart failure events during a median follow up of 10 years. Participants with the 'worst' multi-system trajectory profile had the highest heart failure risk. A one-unit increase in the trajectory risk score was associated with a 2.72-fold increase in heart failure risk (95% CI 2.21-3.34; p<0.001). The mean c-statistics for models including the trajectory risk score and single-occasion traits were 0.87 (95% CI 0.83-0.91) and 0.83 (95% CI 0.80-0.86), respectively.
conclusionIncorporating multi-system trajectories reflective of the aging process may add incremental information to heart failure risk assessment when compared to using single-occasion traits.
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