Predicting survival in heart failure : validation of the MAGGIC heart failure risk score in 51 043 patients from the Swedish Heart Failure Registry

• AIMS:The aim of this study was to evaluate the performance of a recently developed risk score for mortality in heart failure by external validation in a national heart failure registry.METHODS AND RESULTS:From 13 routinely available patient characteristics, the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) constructed a risk score for prediction of mortality in heart failure. We included 51 043 patients from the national Swedish Heart Failure Registry and calculated the MAGGIC risk score for each patient. The outcome measure was 3-year mortality. The predicted probability of death obtained from the calculated risk score was compared with the observed 3-year mortality, and model discrimination and calibration were assessed by formal tests and graphical means. The overall 3-year mortality in the study population was 39.4% and the MAGGIC project heart failure risk score predicted mortality was 36.4% (observed to expected ratio: 1.08). Discrimination was excellent overall (C index = 0.741). The difference between the model-predicted and the observed 3-year mortality in the six risk groups varied between 5% and -12%. Calibration plots demonstrated slight overprediction for the lowest risk patients, and underprediction in high risk patients.CONCLUSION:The MAGGIC project heart failure risk score demonstrated an excellent ability to categorize patients in separate risk strata. Although the predicted 3-year mortality risk was higher in low risk groups and lower in high risk groups compared with the observed 3-year mortality in the Swedish Heart Failure Registry, the MAGGIC project heart failure risk score performed well in a large nationwide contemporary external validation cohort.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine (hsv//eng)

Nyckelord

Heart failure; Survival; Prognostic risk models; External validation

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