Novel scoring system based on clinical examination for prediction of in-hospital mortality in acute coronary syndrome patients: a retrospective cohort study

BACKGROUND: This study aims to develop PADjadjaran Mortality in Acute coronary syndrome (PADMA) Score to predict in-hospital mortality in acute coronary syndrome (ACS) patients based on clinical examination only. Additionally, we also compared the predictive value of the PADMA Score with the Global Registry of Acute Coronary Events (GRACE), Canada Acute Coronary Syndrome (C-ACS), and The Portuguese Registry of Acute Coronary Syndromes (ProACS) risk scores. METHODS: This retrospective cohort study included all ACS patients aged≥18 years who were admitted to Dr. Hasan Sadikin Central General Hospital from January 2018 to January 2022. Patients’ demographic, comorbidities and clinical presentation data were collected and analysed using multivariate logistic regression to create two models of scoring system (probability and cut-off model) to predict in-hospital all-cause mortality. The area under the curve (AUC) among PADMA, GRACE, C-ACS and ProACS risk scores was compared using the fisher Z test. RESULTS: Multivariate regression analysis of 1359 patients showed that older age, history of cerebrovascular disease, tachycardia, high Shock Index and Killip class III and IV were independent mortality predictors and included in the PADMA Score. PADMA Score ranged from 0 to 20, with a score≥5 that can predict all-cause mortality with 82.78% sensitivity and 72.35% specificity. The difference in AUC between PADMA and GRACE scores was insignificant (p=0.126). Moreover, the AUC of the PADMA Score was significantly higher compared with the C-ACS (p=0.002) and ProACS risk scores (p<0.001). CONCLUSION: PADMA Score is a simple scoring system to predict in-hospital mortality in ACS patients. PADMA Score≥5 showed an accurate discriminative capability to predict in-hospital mortality, comparable with the GRACE Score and superior to C-ACS and ProACS scores.