MAGGIC (Meta-Analysis Global Group In Chronic Heart Failure) — explanation and clinical context The MAGGIC prognostic model (Pocock et al., Eur Heart J 2013) was developed from individual-patient data pooled from 39,372 patients across 30 cohorts to predict mortality in chronic heart failure. It uses 13 routinely available clinical variables (age, sex, body mass index, systolic blood pressure, LVEF, serum creatinine, current smoking, diabetes, COPD, time since diagnosis, NYHA class, and use of beta-blocker and ACE inhibitor/ARB) to produce an integer score; higher scores correspond to higher mortality risk at 1 and 3 years. The model has been externally validated in multiple cohorts and frequently compared with other HF risk tools (e.g., Seattle Heart Failure Model); validation studies show modest discrimination (typical c-statistics ~0.7–0.75) and improved performance when biomarkers (NT-proBNP) are added.
Clinical significance:
MAGGIC is a pragmatic clinical risk index useful for population-level prognosis, trial stratification, and bedside risk-communication. It complements biomarkers and more complex models; however, calibration may vary by setting and patient mix and updated local calibration or addition of natriuretic peptides can improve performance.
Reference:
Pocock SJ, Ariti CA, McMurray JJV, et al. Predicting survival in heart failure: a risk score based on 39,372 patients from 30 studies. European Heart Journal. 2013;34:1404–1413.
Additional validations and discussion: Canepa M et al. Performance of prognostic risk scores in chronic heart failure patients enrolled in the ESC Heart Failure Long-Term Registry. JACC Heart Fail. 2018;6:452–462. MDCalc: MAGGIC Risk Calculator (web tool).