Yang, H and Negishi, K and Otahal, P and Marwick, TH, Clinical prediction of incident heart failure risk: a systematic review and meta-analysis, Open Heart, 2 Article e000222. ISSN 2053-3624 (2015) [Refereed Article]
Licensed under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) http://creativecommons.org/licenses/by-nc/4.0/
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 (HRnbsp;= 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/m2) = 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.
|Item Type:||Refereed Article|
|Research Division:||Medical and Health Sciences|
|Research Group:||Cardiorespiratory Medicine and Haematology|
|Research Field:||Cardiology (incl. Cardiovascular Diseases)|
|Objective Group:||Clinical Health (Organs, Diseases and Abnormal Conditions)|
|Objective Field:||Cardiovascular System and Diseases|
|UTAS Author:||Yang, H (Ms Hilda Yang)|
|UTAS Author:||Negishi, K (Dr Kazuaki Negishi)|
|UTAS Author:||Otahal, P (Mr Petr Otahal)|
|UTAS Author:||Marwick, TH (Professor Tom Marwick)|
|Web of Science® Times Cited:||27|
|Deposited By:||Menzies Institute for Medical Research|
|Downloads:||271 View Download Statistics|
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