Division of Cardiovascular Medicine, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA.
Cardiovascular intensive care unit (CVICU), University of Utah School of Medicine, Salt Lake City, Utah, USA.
Catheter Cardiovasc Interv. 2021 Dec 1;98(7):1275-1284. doi: 10.1002/ccd.29581. Epub 2021 Mar 7.
To identify predictors of 30-day all-cause mortality for patients with cardiogenic shock secondary to acute coronary syndrome (ACS-CS) who require short-term mechanical circulatory support (ST-MCS).
ACS-CS mortality is high. ST-MCS is an attractive treatment option for hemodynamic support and stabilization of deteriorating patients. Mortality prediction modeling for ACS-CS patients requiring ST-MCS has not been well-defined.
The Utah Cardiac Recovery (UCAR) Shock database was used to identify patients admitted with ACS-CS requiring ST-MCS devices between May 2008 and August 2018. Pre-ST-MCS clinical, laboratory, echocardiographic, and angiographic data were collected. The primary endpoint was 30-day all-cause mortality. A weighted score comprising of pre-ST-MCS variables independently associated with 30-day all-cause mortality was derived and internally validated.
A total of 159 patients (mean age, 61 years; 78% male) were included. Thirty-day all-cause mortality was 49%. Multivariable analysis resulted in four independent predictors of 30-day all-cause mortality: age, lactate, SCAI CS classification, and acute kidney injury. The model had good calibration and discrimination (area under the receiver operating characteristics curve 0.80). A predictive score (ranging 0-4) comprised of age ≥ 60 years, pre-ST-MCS lactate ≥2.5 mmol/L, AKI at time of ST-MCS implementation, and SCAI CS stage E effectively risk stratified our patient population.
The ACS-MCS score is a simple and practical predictive score to risk-stratify CS secondary to ACS patients based on their mortality risk. Effective mortality risk assessment for ACS-CS patients could have implications on patient selection for available therapeutic strategy options.
确定需要短期机械循环支持(ST-MCS)的急性冠状动脉综合征(ACS-CS)继发心源性休克患者 30 天全因死亡率的预测因素。
ACS-CS 的死亡率很高。ST-MCS 是一种有吸引力的治疗选择,可用于支持血液动力学和稳定病情恶化的患者。对于需要 ST-MCS 的 ACS-CS 患者,尚未对其死亡率预测模型进行很好的定义。
使用犹他州心脏复苏(UCAR)休克数据库,确定 2008 年 5 月至 2018 年 8 月期间因 ACS-CS 需要 ST-MCS 设备的住院患者。收集 ST-MCS 前的临床、实验室、超声心动图和血管造影数据。主要终点为 30 天全因死亡率。得出一个由与 30 天全因死亡率独立相关的 ST-MCS 前变量组成的加权评分,并进行内部验证。
共纳入 159 例患者(平均年龄 61 岁,78%为男性)。30 天全因死亡率为 49%。多变量分析得出 30 天全因死亡率的四个独立预测因素:年龄、乳酸、SCAI CS 分类和急性肾损伤。该模型具有良好的校准和区分度(接受者操作特征曲线下面积 0.80)。一个预测评分(范围 0-4)由年龄≥60 岁、ST-MCS 前乳酸≥2.5mmol/L、ST-MCS 实施时 AKI 和 SCAI CS 阶段 E 组成,可有效对患者人群进行风险分层。
ACS-MCS 评分是一种简单实用的预测评分,可根据死亡率风险对 ACS 继发 CS 患者进行风险分层。对 ACS-CS 患者进行有效的死亡率风险评估可能对选择可用治疗策略的患者产生影响。