Key result
Adding SHARC classification to clinical variables improves 30-day mortality prediction over SCAI alone.
Why the study?
Cardiogenic shock remains a leading cause of ICU mortality, and this study evaluated the association between SHARC etiological classes and 30-day mortality while comparing their prognostic value with SCAI classification.
Does the SHARC classification improve prognostic prediction of 30-day mortality compared to the SCAI classification in adults with cardiogenic shock?
Cohort (n=1,366)
Yes
Does the SHARC classification improve prognostic prediction of 30-day mortality compared to the SCAI classification in adults with cardiogenic shock?
Integrating the SHARC etiological classification with SCAI staging and hemodynamic parameters significantly improves 30-day mortality risk stratification in ICU patients with cardiogenic shock.
May refine cardiogenic shock risk stratification; extends SCAI staging but leaves open prospective validation before practice change.
Background: Cardiogenic shock (CS) remains a leading cause of mortality in intensive care units (ICU) despite advances in management. The Shock Academic Research Consortium (SHARC) classification provides an etiological framework complementing severity-based systems such as the Society for Cardiovascular Angiography and Interventions (SCAI) classification. This study evaluated the association between SHARC classes and 30-day mortality in a contemporary ICU population and compared their prognostic value with SCAI classification. Methods: This bicentric retrospective cohort study included 1366 consecutive adults admitted with CS. Patients were classified according to SHARC criteria: acute myocardial infarction (AMI)-CS (n = 303, 22.5%), heart failure (HF)-CS (n = 56, 5.0%), secondary-CS (n = 433, 29.9%), and post-cardiotomy-CS (n = 574, 42.7%). The primary outcome was 30-day all-cause mortality. Multivariable logistic regression models assessed independent predictors of mortality and comparative prognostic performance using Akaike Information Criterion, Bayesian Information Criterion, and discrimination indices. Results: Thirty-day mortality varied significantly across SHARC classes: AMI-CS (48.7%), HF-CS (45.6%), secondary-CS (39.0%), and post cardiotomy-CS (17.3%) (p < 0.001). Multivariable analysis identified age, epinephrine use, vasopressin use, arterial lactate, right ventricular dysfunction, and SHARC classification as independent mortality predictors (all P < 0.05). Adding SHARC classification to clinical variables provided greater incremental prognostic value (ΔAIC = −48.3; AUC=0.734; R2 = 0.198) than SCAI classification alone (ΔAIC = −20.0; AUC = 0.723; R2 = 0.172). The combined model integrating SHARC, SCAI, and hemodynamic parameters demonstrated the best performance (AUC = 0.819; R2 = 0.355). Conclusions: SHARC etiological classification provides complementary discrimination for 30-day mortality compared with SCAI staging alone, suggesting that shock pathophysiology influences patient outcomes. Integration of both classifications may improve risk stratification and enable more personalized therapeutic approaches in cardiogenic shock management.
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Pierre-Grégoire et al. (2026) conducted a cohort in Cardiogenic shock (n=1,366). SHARC classification vs. SCAI classification was evaluated on 30-day all-cause mortality. Adding SHARC classification to clinical variables provided greater incremental prognostic value for 30-day mortality (AUC 0.734) than SCAI classification alone (AUC 0.723).
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