Ana Teresa Timóteo1, Sílvia Aguiar Rosa2, Marta Afonso Nogueira2, Adriana Belo3, Rui Cruz Ferreira2. 1. Cardiology Department, Santa Marta Hospital, Centro Hospitalar de Lisboa Central, Lisbon, Portugal. Electronic address: ana_timoteo@yahoo.com. 2. Cardiology Department, Santa Marta Hospital, Centro Hospitalar de Lisboa Central, Lisbon, Portugal. 3. National Center for Data Collection in Cardiology, Portuguese Society of Cardiology, Coimbra, Portugal.
Abstract
INTRODUCTION: There are barriers to proper implementation of risk stratification scores in patients with acute coronary syndromes (ACS), including their complexity. Our objective was to develop a simple score for risk stratification of all-cause in-hospital mortality in a population of patients with ACS. METHODS: The score was developed from a nationwide ACS registry. The development and internal validation cohorts were obtained from the first 31829 patients, randomly separated (60% and 40%, respectively). The external validation cohort consisted of the last 8586 patients included in the registry. This cohort is significantly different from the other cohorts in terms of baseline characteristics, treatment and mortality. Multivariate logistic regression analysis was used to select four variables with the highest predictive potential. A score was allocated to each parameter based on the regression coefficient of each variable in the logistic regression model: 1 point for systolic blood pressure ≤116 mmHg, Killip class 2 or 3, and ST-segment elevation; 2 points for age ≥72 years; and 3 points for Killip class 4. RESULTS: The new score had good discriminative ability in the development cohort (area under the curve [AUC] 0.796), and it was similar in the internal validation cohort (AUC 0.785, p=0.333). In the external validation cohort, there was also excellent discriminative ability (AUC 0.815), with an adequate fit. CONCLUSIONS: The ProACS risk score enables easy and simple risk stratification of patients with ACS for in-hospital mortality that can be used at the first medical contact, with excellent predictive ability in a contemporary population.
INTRODUCTION: There are barriers to proper implementation of risk stratification scores in patients with acute coronary syndromes (ACS), including their complexity. Our objective was to develop a simple score for risk stratification of all-cause in-hospital mortality in a population of patients with ACS. METHODS: The score was developed from a nationwide ACS registry. The development and internal validation cohorts were obtained from the first 31829 patients, randomly separated (60% and 40%, respectively). The external validation cohort consisted of the last 8586 patients included in the registry. This cohort is significantly different from the other cohorts in terms of baseline characteristics, treatment and mortality. Multivariate logistic regression analysis was used to select four variables with the highest predictive potential. A score was allocated to each parameter based on the regression coefficient of each variable in the logistic regression model: 1 point for systolic blood pressure ≤116 mmHg, Killip class 2 or 3, and ST-segment elevation; 2 points for age ≥72 years; and 3 points for Killip class 4. RESULTS: The new score had good discriminative ability in the development cohort (area under the curve [AUC] 0.796), and it was similar in the internal validation cohort (AUC 0.785, p=0.333). In the external validation cohort, there was also excellent discriminative ability (AUC 0.815), with an adequate fit. CONCLUSIONS: The ProACS risk score enables easy and simple risk stratification of patients with ACS for in-hospital mortality that can be used at the first medical contact, with excellent predictive ability in a contemporary population.