Pocock, Stuart J2; Ariti, Cono A2; McMurray, John J V2; Maggioni, Aldo2; Køber, Lars4; Squire, Iain B2; Swedberg, Karl2; Dobson, Joanna2; Poppe, Katrina K2; Whalley, Gillian A2; Doughty, Rob N2
1 Section of Surgery and Internal Medicine, Department of Clinical Medicine, Faculty of Health and Medical Sciences, Københavns Universitet2 unknown3 Department of Clinical Medicine, Department of Clinical Medicine, Faculty of Health and Medical Sciences, Københavns Universitet4 Department of Clinical Medicine, Department of Clinical Medicine, Faculty of Health and Medical Sciences, Københavns Universitet
a risk score based on 39 372 patients from 30 studies
AimsUsing a large international database from multiple cohort studies, the aim is to create a generalizable easily used risk score for mortality in patients with heart failure (HF).Methods and resultsThe MAGGIC meta-analysis includes individual data on 39 372 patients with HF, both reduced and preserved left-ventricular ejection fraction (EF), from 30 cohort studies, six of which were clinical trials. 40.2% of patients died during a median follow-up of 2.5 years. Using multivariable piecewise Poisson regression methods with stepwise variable selection, a final model included 13 highly significant independent predictors of mortality in the following order of predictive strength: age, lower EF, NYHA class, serum creatinine, diabetes, not prescribed beta-blocker, lower systolic BP, lower body mass, time since diagnosis, current smoker, chronic obstructive pulmonary disease, male gender, and not prescribed ACE-inhibitor or angiotensin-receptor blockers. In preserved EF, age was more predictive and systolic BP was less predictive of mortality than in reduced EF. Conversion into an easy-to-use integer risk score identified a very marked gradient in risk, with 3-year mortality rates of 10 and 70% in the bottom quintile and top decile of risk, respectively.ConclusionIn patients with HF of both reduced and preserved EF, the influences of readily available predictors of mortality can be quantified in an integer score accessible by an easy-to-use website www.heartfailurerisk.org. The score has the potential for widespread implementation in a clinical setting.