Development and validation of a prognostic score integrating remote heart failure symptoms and clinical variables in mortality risk prediction after myocardial infarction: the PragueMi score

Abstract Aims While heart failure (HF) symptoms are associated with adverse prognosis after myocardial infarction (MI), they are not routinely used for patients’ stratification. The primary objective of this study was to develop and validate a score to predict mortality risk after MI, combining remotely recorded HF symptoms and clinical risk factors, and to compare it against the guideline-recommended Global Registry of Acute Coronary Events (GRACE) score. Methods and results A cohort study design using prospectively collected data from consecutive patients hospitalized for MI at a large tertiary heart centre between June 2017 and September 2022 was used. Data from 1135 patients (aged 64 ± 12 years, 26.7% women), were split into derivation (70%) and validation cohort (30%). Components of the 23-item Kansas City Cardiomyopathy Questionnaire and clinical variables were used as possible predictors. The best model included the following variables: age, HF history, admission creatinine and heart rate, ejection fraction at hospital discharge, and HF symptoms 1 month after discharge including walking impairment, leg swelling, and change in HF symptoms. Based on these variables, the PragueMi score was developed. In the validation cohort, the PragueMi score showed superior discrimination to the GRACE score for 6 months [the area under the receiver operating curve (AUC) 90.1, 95% confidence interval (CI) 81.8–98.4 vs. 77.4, 95% CI 62.2–92.5, P = 0.04) and 1-year risk prediction (AUC 89.7, 95% CI 83.5–96.0 vs. 76.2, 95% CI 64.7–87.7, P = 0.004). Conclusion The PragueMi score combining HF symptoms and clinical variables performs better than the currently recommended GRACE score.