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Published on: June 10, 2025
Clinical prediction of incident heart failure risk: a systematic review and meta-analysis
Hong Yang1, Kazuaki Negishi1, Petr Otahal1
1Menzies Institute for Medical Research , Hobart, Tasmania , Australia.
Insights
Identifying individuals with stage B heart failure (SBHF) is crucial for early intervention. This review highlights key clinical factors like coronary artery disease and diabetes that predict heart failure risk.
Area of Science:
- Cardiology
- Public Health
Background:
- Early intervention in asymptomatic stage B heart failure (SBHF) may prevent progression to overt heart failure (HF).
- Identifying patients with SBHF is challenging, necessitating improved screening strategies.
Purpose of the Study:
- To systematically review and quantify the association of clinical factors with incident heart failure (HF).
- To facilitate the selection of individuals for HF screening by identifying strong predictors of HF risk.
Main Methods:
- A systematic search of electronic databases was conducted for studies reporting risk factors for incident HF.
- Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were computed using a random-effects model.
Main Results:
- Fifteen observational studies with 456,850 participants identified 27 clinical factors associated with incident HF.
- Strongest predictors included coronary artery disease (HR=2.94), diabetes mellitus (HR=2.00), age (HR per 10 years=1.80), hypertension (HR=1.61), smoking (HR=1.60), male gender (HR=1.52), and body mass index (HR per 5 kg/m²=1.15).
- Atrial fibrillation, left ventricular hypertrophy, and valvular heart disease were also strongly associated but lacked sufficient data for pooled estimates.
Conclusions:
- Incident HF risk can be predicted using seven common clinical variables.
- These risk factors can guide strategies for identifying high-risk individuals who may benefit from further evaluation and intervention.
Background:
Early treatment may alter progression to overt heart failure (HF) in asymptomatic individuals with stage B HF (SBHF). However, the identification of patients with SBHF is difficult. This systematic review sought to examine the strength of association of clinical factors with incident HF, with the intention of facilitating selection for HF screening.
Methods:
Electronic databases were systematically searched for studies reporting risk factors for incident HF. Effect sizes, typically HRs, of each risk variable were extracted. Pooled crude and adjusted HRs with 95% CIs were computed for each risk variable using a random-effects model weighted by inverse variance.
Results:
Twenty-seven clinical factors were identified to be associated with risk of incident HF in 15 observational studies in unselected community populations which followed 456 850 participants over 4-29 years. The strongest independent associations for incident HF were coronary artery disease (HR=2.94; 95% CI 1.36 to 6.33), diabetes mellitus (HR=2.00; 95% CI 1.68 to 2.38), age (HR (per 10 years)=1.80; 95% CI 1.13 to 2.87) followed by hypertension (HR=1.61; 95% CI 1.33 to 1.96), smoking (HR=1.60; 95% CI 1.45 to 1.77), male gender (HR=1.52; 95% CI 1.24 to 1.87) and body mass index (HR (per 5 kg/m(2))=1.15; 95% CI 1.06 to 1.25). Atrial fibrillation (HR=1.88; 95% CI 1.60 to 2.21), left ventricular hypertrophy (HR=2.46; 95% CI 1.71 to 3.53) and valvular heart disease (HR=1.74; 95% CI 1.07 to 2.84) were also strongly associated with incident HF but were not examined in sufficient papers to provide pooled hazard estimates.
Conclusions:
Prediction of incident HF can be calculated from seven common clinical variables. The risk associated with these may guide strategies for the identification of high-risk people who may benefit from further evaluation and intervention.
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