Risk Stratification in Predicting Cardiogenic Shock 30-Day Mortality admitted to ICU: beyond the Prognostic Performance of SHARC and SCAI Classifications.

IF 6.9 1区 医学 Q1 CRITICAL CARE MEDICINE
Annals of Intensive Care Pub Date : 2026-05-20 eCollection Date: 2026-01-01 DOI:10.1016/j.aicoj.2026.100090
Pierre-Grégoire Guinot, Thomas Hanquiez, Maxime Nguyen, Osama Abou-Ara, Laurent Leborgne, Yazine Mahjoub, Bélaïd Bouhemad, Christophe Beyls
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引用次数: 0

Abstract

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.

预测ICU住院心源性休克30天死亡率的风险分层:超越SHARC和SCAI分类的预后表现
背景:心源性休克(CS)仍然是重症监护病房(ICU)死亡的主要原因,尽管管理有所进步。休克学术研究联盟(SHARC)分类提供了一个病因学框架,补充了基于严重程度的系统,如心血管血管造影和干预学会(SCAI)分类。本研究评估了当代ICU人群中SHARC分级与30天死亡率之间的关系,并将其与SCAI分级的预后价值进行了比较。方法:这项双中心回顾性队列研究包括1366名连续入院的成人CS。根据SHARC标准对患者进行分类:急性心肌梗死(AMI)-CS (n = 303, 22.5%)、心力衰竭(HF)-CS (n = 56, 5.0%)、继发性cs (n = 433, 29.9%)和心切术后-CS (n = 574,42.7%)。主要终点为30天全因死亡率。多变量logistic回归模型使用赤池信息标准、贝叶斯信息标准和判别指数评估死亡率和比较预后表现的独立预测因子。结果:与单独的SCAI分类(ΔAIC = -20.0; AUC = 0.723; R2 = 0.172)相比,SHARC分类的30天死亡率差异显著:AMI-CS(48.7%)、HF-CS(45.6%)、继发性cs(39.0%)和心切术后cs (17.3%) (p 2 = 0.198)。综合SHARC、SCAI和血流动力学参数的联合模型表现最佳(AUC = 0.819, R2 = 0.355)。结论:与单独的SCAI分期相比,SHARC病因分类对30天死亡率提供了互补的区分,表明休克病理生理影响患者的预后。两种分类的整合可以改善风险分层,并在心源性休克管理中实现更个性化的治疗方法。
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来源期刊
Annals of Intensive Care
Annals of Intensive Care CRITICAL CARE MEDICINE-
CiteScore
14.20
自引率
3.70%
发文量
107
审稿时长
13 weeks
期刊介绍: Annals of Intensive Care is an online peer-reviewed journal that publishes high-quality review articles and original research papers in the field of intensive care medicine. It targets critical care providers including attending physicians, fellows, residents, nurses, and physiotherapists, who aim to enhance their knowledge and provide optimal care for their patients. The journal's articles are included in various prestigious databases such as CAS, Current contents, DOAJ, Embase, Journal Citation Reports/Science Edition, OCLC, PubMed, PubMed Central, Science Citation Index Expanded, SCOPUS, and Summon by Serial Solutions.
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