Annals of intensive care · 2026
Risk Stratification in Predicting Cardiogenic Shock 30-Day Mortality admitted to ICU: beyond the Prognostic Performance of SHARC and SCAI Classifications.
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Guinot Pierre-Grégoire, Hanquiez Thomas, Nguyen Maxime, Abou-Ara Osama, Leborgne Laurent, Mahjoub Yazine, Bouhemad Bélaïd, Beyls Christophe, PROMIX study group
Аннотация
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.
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.