A novel score to predict in-hospital mortality for patients with acute coronary syndrome and out-of-hospital cardiac arrest: the FACTOR study

Author:

Schweiger Victor,Hiller Pauline,Utters Rahel,Fenice Angela,Cammann Victoria Lucia,Di Vece Davide,Rajman Katja,Candreva Alessandro,Gotschy Alexander,Gilhofer Thomas,Würdinger Michael,Stähli Barbara E.,Seifert Burkhardt,Müller Stefan M.,Templin ChristianORCID,Stehli Julia

Abstract

Abstract Introduction Acute coronary syndromes (ACS) represent a substantial global healthcare challenge. In its most severe form, it can lead to out-of-hospital cardiac arrest (OHCA). Despite medical advancements, survival rates in OHCA patients remain low. Further, the prediction of outcomes in these patients poses a challenge to all health care providers involved. This study aims at developing a score with variables available on admission to assess in-hospital mortality of patients with OHCA undergoing coronary angiography. Method All patients with OHCA due to ACS admitted to a tertiary care center were included. A multivariate logistic regression analysis was conducted to explore the association between clinical variables and in-hospital all-cause mortality. A scoring system incorporating variables available upon admission to assess individual patients' risk of in-hospital mortality was developed (FACTOR score). The score was then validated. Results A total of 291 patients were included in the study, with a median age of 65 [56–73] years, including 47 women (16.2%). The in-hospital mortality rate was 41.2%. A prognostic model was developed in the derivation cohort (n = 138) and included the following variables: age, downtime, first detected rhythm, and administration of epinephrine. The area under the curve for the FACTOR score was 0.823 (95% CI 0.737–0.894) in the derivation cohort and 0.828 (0.760–0.891) in the validation cohort (n = 153). Conclusion The FACTOR score demonstrated a reliable prognostic tool for health care providers in assessing in-hospital mortality of OHCA patients. Early acknowledgement of a poor prognosis may help in patient management and allocation of resources. Graphical abstract

Publisher

Springer Science and Business Media LLC

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