Predicting mortality in cardiogenic shock secondary to <scp>ACS</scp> requiring <scp>short‐term</scp> mechanical circulatory support: The <scp>ACS‐MCS</scp> score

Objective To identify predictors of 30-day all-cause mortality for patients with cardiogenic shock secondary to acute coronary syndrome (ACS-CS) who require short-term mechanical circulatory support (ST-MCS). Background ACS-CS mortality is high. ST-MCS is an attractive treatment option for hemodynamic support and stabilization of deteriorating patients. Mortality prediction modeling for ACS-CS patients requiring ST-MCS has not been well-defined. Methods The Utah Cardiac Recovery (UCAR) Shock database was used to identify patients admitted with ACS-CS requiring ST-MCS devices between May 2008 and August 2018. Pre-ST-MCS clinical, laboratory, echocardiographic, and angiographic data were collected. The primary endpoint was 30-day all-cause mortality. A weighted score comprising of pre-ST-MCS variables independently associated with 30-day all-cause mortality was derived and internally validated. Results A total of 159 patients (mean age, 61 years; 78% male) were included. Thirty-day all-cause mortality was 49%. Multivariable analysis resulted in four independent predictors of 30-day all-cause mortality: age, lactate, SCAI CS classification, and acute kidney injury. The model had good calibration and discrimination (area under the receiver operating characteristics curve 0.80). A predictive score (ranging 0-4) comprised of age ≥ 60 years, pre-ST-MCS lactate ≥2.5 mmol/L, AKI at time of ST-MCS implementation, and SCAI CS stage E effectively risk stratified our patient population. Conclusion The ACS-MCS score is a simple and practical predictive score to risk-stratify CS secondary to ACS patients based on their mortality risk. Effective mortality risk assessment for ACS-CS patients could have implications on patient selection for available therapeutic strategy options.