Comparison of Risk Models in the Prediction of 30-Day Mortality in Acute Myocardial Infarction-Associated Cardiogenic Shock

Lauren S Ranard; Kenneth Guber; Justin Fried; Koji Takeda; Yuji Kaku; Dimitrios Karmpaliotis; Gabriel Sayer; Leroy Rabbani; Daniel Burkhoff; Nir Uriel; Ajay J Kirtane; Amirali Masoumi

doi:10.1016/j.shj.2022.100116

Comparison of Risk Models in the Prediction of 30-Day Mortality in Acute Myocardial Infarction-Associated Cardiogenic Shock

Struct Heart. 2022 Oct 31;6(6):100116. doi: 10.1016/j.shj.2022.100116. eCollection 2022 Nov.

Authors

Lauren S Ranard¹, Kenneth Guber², Justin Fried¹, Koji Takeda¹, Yuji Kaku¹, Dimitrios Karmpaliotis^{1

3}, Gabriel Sayer¹, Leroy Rabbani¹, Daniel Burkhoff⁴, Nir Uriel¹, Ajay J Kirtane^{1

4}, Amirali Masoumi^{1

3}

Affiliations

¹ Department of Cardiology, Columbia University Irving Medical Center, New York, New York, USA.
² Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.
³ Gagnon Cardiovascular Institute, Morristown Medical Center, Morristown, New Jersey, USA.
⁴ Cardiovascular Research Foundation, New York, New York, USA.

Abstract

Background: There are numerous risk-prediction models applied to acute myocardial infarction-related cardiogenic shock (AMI-CS) patients to determine a more accurate prognosis and to assist in patient triage. There is wide heterogeneity among the risk models including the nature of predictors evaluated and their specific outcome measures. The aim of this analysis was to evaluate the performance of 20 risk-prediction models in AMI-CS patients.

Methods: Patients included in our analysis were admitted to a tertiary care cardiac intensive care unit with AMI-CS. Twenty risk-prediction models were computed utilizing vitals assessments, laboratory investigations, hemodynamic markers, and vasopressor, inotropic and mechanical circulatory support available from within the first 24 hours of presentation. Receiver operating characteristic curves were used to assess the prediction of 30-day mortality. Calibration was assessed with a Hosmer-Lemeshow test.

Results: Seventy patients (median age 63 years, 67% male) were admitted between 2017 and 2021. The models' area under the curve (AUC) ranged from 0.49 to 0.79, with the Simplified Acute Physiology Score II score having the most optimal discrimination of 30-day mortality (AUC: 0.79, 95% confidence interval [CI]: 0.67-0.90), followed by the Acute Physiology and Chronic Health Evaluation-III score (AUC: 0.72, 95% CI: 0.59-0.84) and the Acute Physiology and Chronic Health Evaluation-II score (AUC: 0.67, 95% CI: 0.55-0.80). All 20 risk scores demonstrated adequate calibration (p > 0.05 for all).

Conclusions: Among the models tested in a data set of patients admitted with AMI-CS, the Simplified Acute Physiology Score II risk score model demonstrated the highest prognostic accuracy. Further investigations are required to improve the discriminative capabilities of these models or to establish new, more streamlined and accurate methods for mortality prognostication in AMI-CS.

Keywords: Acute myocardial infarction cardiogenic shock; Cardiogenic shock; Mortality; Risk calculator; Risk prediction.