Cardiogenic Shock Classification to Predict Mortality in the Cardiac Intensive Care Unit.

Cardiogenic Shock Classification to Predict Mortality in the Cardiac Intensive Care Unit.

Jentzer, Jacob C;van Diepen, Sean;Barsness, Gregory W;Henry, Timothy D;Menon, Venu;Rihal, Charanjit S;Naidu, Srihari S;Baran, David A;
Journal of the American College of Cardiology 2019
298
jentzer2019cardiogenicjournal

Abstract

A new 5-stage cardiogenic shock (CS) classification scheme was recently proposed by the Society for Cardiovascular Angiography and Intervention (SCAI) for the purpose of risk stratification.This study sought to apply the SCAI shock classification in a cardiac intensive care unit (CICU) population.The study retrospectively analyzed Mayo Clinic CICU patients admitted between 2007 and 2015. SCAI CS stages A through E were classified retrospectively using CICU admission data based on the presence of hypotension or tachycardia, hypoperfusion, deterioration, and refractory shock. Hospital mortality in each SCAI shock stage was stratified by cardiac arrest (CA).Among the 10,004 unique patients, 43.1% had acute coronary syndrome, 46.1% had heart failure, and 12.1% had CA. The proportion of patients in SCAI CS stages A through E was 46.0%, 30.0%, 15.7%, 7.3%, and 1.0% and unadjusted hospital mortality in these stages was 3.0%, 7.1%, 12.4%, 40.4%, and 67.0% (p < 0.001), respectively. After multivariable adjustment, each higher SCAI shock stage was associated with increased hospital mortality (adjusted odds ratio: 1.53 to 6.80; all p < 0.001) compared with SCAI shock stage A, as was CA (adjusted odds ratio: 3.99; 95% confidence interval: 3.27 to 4.86; p < 0.001). Results were consistent in the subset of patients with acute coronary syndrome or heart failure.When assessed at the time of CICU admission, the SCAI CS classification, including presence or absence of CA, provided robust hospital mortality risk stratification. This classification system could be implemented as a clinical and research tool to identify, communicate, and predict the risk of death in patients with, and at risk for, CS.

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