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

Peter Wohlfahrt; Dominik Jenča; Vojtěch Melenovský; Josef Stehlik; Jolana Mrázková; Marek Šramko; Martin Kotrč; Michael Želízko; Věra Adámková; Jan Piťha; Josef Kautzner

doi:10.1093/eurjpc/zwae114

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

Eur J Prev Cardiol. 2024 Mar 18:zwae114. doi: 10.1093/eurjpc/zwae114. Online ahead of print.

Authors

Peter Wohlfahrt^{1

2}, Dominik Jenča^{3

4}, Vojtěch Melenovský³, Josef Stehlik⁵, Jolana Mrázková⁶, Marek Šramko^{2

3}, Martin Kotrč³, Michael Želízko³, Věra Adámková¹, Jan Piťha³, Josef Kautzner^{3

7}

Affiliations

¹ Department of Preventive Cardiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic.
² First Medical School, Charles University, Prague, Czech Republic.
³ Department of Cardiology, Institute for Clinical and Experimental Medicine (IKEM), Prague, Czech Republic.
⁴ Third Medical School, Charles University, Prague, Czech Republic.
⁵ University of Utah School of Medicine, Salt Lake City, UT, USA.
⁶ Experimental Medicine Centre, Institute for Clinical and Experimental Medicine (IKEM), Prague, Czech Republic.
⁷ Medical and Dentistry School, Palacký University, Olomouc, Czech Republic.

PMID: 38497201
DOI: 10.1093/eurjpc/zwae114

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 GRACE score.

Methods: 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.

Results: Data from 1,135 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 (KCCQ) questionnaire and clinical variables were used as possible predictors. The best model included the following variables - age, heart failure 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 (AUC 90.1, 95% 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 heart failure symptoms and clinical variables performs better than the currently recommended GRACE score.

Keywords: heart failure; mortality; myocardial infarction; questionnaire; risk prediction; symptoms.

Plain language summary

The prognosis of patients after myocardial infarction is heterogeneous. Thus, risk stratification is needed to identify and intervene patients at increased risk. While heart failure (HF) symptoms are associated with adverse prognosis, they are not used for patients’ stratification. We have developed and internally validated the PragueMi score, which integrates clinical risk factors at the time of hospitalization and HF symptoms determined remotely by a questionnaire 1 month after hospital discharge. PragueMi score was able to better stratify patients’ risk as compared to the currently recommended GRACE score.