Early risk stratification in patients with cardiogenic shock irrespective of the underlying cause - the Cardiogenic Shock Score

Aims Early risk stratification is essential to guide treatment in cardiogenic shock (CS). Existing CS risk scores were derived in selected cohorts, without accounting for the heterogeneity of CS. The aim of this study was to develop a universal risk score (the Cardiogenic Shock Score, CSS) for all CS patients, irrespective of the underlying cause. Methods and results Within a registry of 1308 CS unselected patients admitted to a tertiary care hospital between 2009 and 2019, a Cox regression model was fitted to derive the CSS, with 30-day mortality as main outcome. The CSS's predictive ability was compared to the IABP-SHOCK II score, the CardShock score and SCAI classification by C-indices and validated in an external cohort of 934 CS patients. Based on the Cox regression, nine predictors were included in the CSS: age, sex, acute myocardial infarction (AMI-CS), systolic blood pressure, heart rate, pH, lactate, glucose and cardiac arrest. The CSS had the highest C-index in the overall cohort (0.740 vs. 0.677/0.683 for IABP-SHOCK II score/CardShock score), in patients with AMI-CS (0.738 vs. 0.675/0.689 for IABP-SHOCK II score/CardShock score) and in patients with non-AMI-CS (0.734 vs. 0.677/0.669 for IABP-SHOCK II score/CardShock score). In the external validation cohort, the CSS had a C-index of 0.73, which was higher than all other tested scores. Conclusion The CSS provides improved information on the risk of death in unselected patients with CS compared to existing scores, irrespective of its cause. Because it is based on point-of-care variables which can be obtained even in critical situations, the CSS has the potential to guide treatment decisions in CS.

Automated summary

This study aimed to develop a universal risk score, the Cardiogenic Shock Score (CSS), for all cardiogenic shock (CS) patients. The CSS showed better predictive ability for mortality compared to existing scores, regardless of the underlying cause. It has the potential to guide treatment decisions in CS.