Abstract 12780: Clinical Prediction of Heart Failure Risk: A Meta-Analysis of 475,000 Subjects
Background: Pts with clinical evidence of Heart Failure (HF) continue to have an adverse outcome. Echo can identify pts with structural heart disease (stage B HF), where early treatment may alter progression to overt HF. A process of identifying pts at highest risk would be necessary for screening, but existing risk scores (FHS, Health ABC, ARIC) are contradictory. We sought to perform a meta-analysis of risk factors for incident HF to identify suitable pts for screening.
Methods: Electronic databases were systematically searched using key terms "incident heart failure" and "risk factors", "risk assessment", "risk impact", "risk prediction", "risk score". The search was limited to human studies, published in English, relating to unselected community population. When multiple articles were identified from the same study, we included the largest data sets. Relative risk (RR) and Hazard Ratio (HR) of each risk variable were extracted from the studies. Crude and adjusted RR, HR and 95% confidence intervals (CI) were computed using random-effects model weighted by inverse variance for each variables. Statistical analysis was performed using standard software package (RevMan5.2).
Results: 21 studies (475,587 subjects) were included with a total of and mean follow up time of 4-40 years. After adjustment of the competing variables, LVH was independently associated with HF (HR2.84; 95%CI 1.98-4.07), followed by CAD (2.66; 0.79-8.96),T2DM (1.87; 1.62-2.16), male gender (1.58; 0.95-2.63), smoking (1.57; 1.41-1.75), age (1.56;1.35-1.80), abnormal ECG (1.52; 1.34-1.72), valve disease (1.46; 1.17-1.82), hypertension (1.30; 1.05-1.61), heart rate (1.20; 0.98-1.47) and obesity (1.16; 0.95-1.42). (see Figure)
Conclusion: Risk of incident HF can be calculated from 10 cardiovascular and non-cardiovascular comorbidities.
- © 2013 by American Heart Association, Inc.