Predictive Model and Risk Score for In-Hospital Mortality in Patients with All-Cause Cardiogenic Shock

Cardiogenic shock (CS) is a condition associated with high morbidity and mortality. Our study aimed to perform a risk score for in-hospital mortality that allows for stratifying the risk of death in patients with CS.This is a retrospective analysis, which included 135 patients from a Spanish university hospital between 2011 and 2020. The Santiago Shock Score (S3) was created using clinical, analytical, and echocardiographic variables obtained at the time of admission.The in-hospital mortality rate was 41.5%, and acute coronary syndrome (ACS) was the responsible cause of shock in 60.7% of patients. Mitral regurgitation grade III-IV, age, ACS etiology, NT-proBNP, blood hemoglobin, and lactate at admission were included in the score. The S3 had good accuracy for predicting in-hospital mortality area under the receiver operating characteristic curve (AUC) 0.85 (95% confidence interval (CI) 0.78-0.90), higher than the AUC of the CardShock score, which was 0.74 (95% CI 0.66-0.83). Predictive power in a cohort of 131 patients with profound CS was similar to that of CardShock with an AUC of 0.601 (95% CI 0.496-0.706) versus an AUC of 0.558 (95% CI 0.453-0.664). Three risk categories were created according to the S3: low (scores 0-6), intermediate (scores 7-10), and high (scores 11-16) risks, with an observed mortality of 12.9%, 49.1%, and 87.5% respectively (P < 0.001).The S3 score had excellent predictive power for in-hospital mortality in patients with nonprofound CS. It could aid the initial risk stratification of patients and thus, guide treatment and clinical decision making in patients with CS.