Beer Benedikt N, Jentzer Jacob C, Weimann Jessica, Dabboura Salim, Yan Isabell, Sundermeyer Jonas, Kirchhof Paulus, Blankenberg Stefan, Schrage Benedikt, Westermann Dirk
Department of Cardiology, University Heart and Vascular Center Hamburg, Hamburg, Germany.
German Centre for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Hamburg, Germany.
Eur J Heart Fail. 2022 Apr;24(4):657-667. doi: 10.1002/ejhf.2449. Epub 2022 Feb 14.
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.
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.
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.
早期风险分层对于指导心源性休克（CS）的治疗至关重要。现有的CS风险评分是在特定队列中得出的，未考虑CS的异质性。本研究的目的是为所有CS患者开发一种通用风险评分（心源性休克评分，CSS），无论其潜在病因如何。
在2009年至2019年间入住一家三级护理医院的1308例未经选择的CS患者登记册中，采用Cox回归模型得出CSS，以30天死亡率作为主要结局。通过C指数将CSS的预测能力与IABP-SHOCK II评分、CardShock评分和SCAI分类进行比较，并在934例CS患者的外部队列中进行验证。基于Cox回归，CSS纳入了九个预测因素：年龄、性别、急性心肌梗死（AMI-CS）、收缩压、心率、pH值、乳酸、血糖和心脏骤停。CSS在总体队列中C指数最高（IABP-SHOCK II评分/CardShock评分为0.677/0.683，CSS为0.740），在AMI-CS患者中（IABP-SHOCK II评分/CardShock评分为0.675/0.689，CSS为0.738）以及在非AMI-CS患者中（IABP-SHOCK II评分/CardShock评分为0.677/0.669，CSS为0.734）。在外部验证队列中，CSS的C指数为0.73，高于所有其他测试评分。
与现有评分相比，CSS能为未经选择的CS患者提供更准确的死亡风险信息，无论其病因如何。由于它基于即时可用的变量，即使在危急情况下也能获取，因此CSS有潜力指导CS的治疗决策。
