Department of Cardiothoracic Surgery, New York Presbyterian Brooklyn Methodist Hospital, Brooklyn, NY, 11215, USA; Department of Cardiothoracic Surgery, New York Presbyterian Weil Cornell Medical Center, New York, NY, 10021, USA.
Department of Cardiothoracic Surgery, New York Presbyterian Weil Cornell Medical Center, New York, NY, 10021, USA.
Heart Lung. 2020 Sep-Oct;49(5):599-604. doi: 10.1016/j.hrtlng.2020.03.004. Epub 2020 Mar 29.
Patients undergoing consideration for venoarterial extracorporeal membrane oxygenation (VA-ECMO) require an immediate risk profile assessment in the setting of incomplete information. A number of survival prediction models for critically ill patients and patients undergoing elective cardiac surgery or institution of VA-ECMO support have been designed. We assess the ability of these models to predict outcomes in a cohort of patients undergoing institution of VA-ECMO for cardiogenic shock or cardiac arrest.
Fifty-one patients undergoing institution of VA-ECMO support were retrospectively analyzed. APACHE II, SOFA, SAPS II, Encourage, SAVE, and ACEF scores were calculated. Their ability to predict outcomes were assessed.
Indications for ECMO support included postcardiotomy shock (25%), ischemic etiologies (39%), and other etiologies (36%). Pre-ECMO arrest occurred in 73% and 41% of patients underwent cannulation during arrest. Survival to discharge was 39%. Three survival prediction model scores were significantly higher in nonsurvivors to discharge than surivors; the Encourage score (25.4 vs 20; p = .04), the APACHE II score (23.6 vs 19.2; p = .05), and the ACEF score (3.1 vs 1.8; p = .03). In ROC analysis, the ACEF score demonstrated the greatest predictive ability with an AUC of 0.7.
A variety of survival prediction model scores designed for critically ill ICU and VA-ECMO patients demonstrated modest discriminatory ability in the current cohort of patients. The ACEF score, while not designed to predict survival in critically ill patients, demonstrated the best discriminatory ability. Furthermore, it is the simplest to calculate, an advantage in the emergent setting.
接受血管外膜氧合（VA-ECMO）治疗的患者在信息不完整的情况下需要立即进行风险评估。已经设计了许多用于危重症患者和接受择期心脏手术或 VA-ECMO 支持的患者的生存预测模型。我们评估这些模型在因心源性休克或心脏骤停而接受 VA-ECMO 治疗的患者队列中预测结果的能力。
回顾性分析了 51 例接受 VA-ECMO 支持的患者。计算了 APACHE II、SOFA、SAPS II、Encourage、SAVE 和 ACEF 评分。评估了它们预测结果的能力。
接受 ECMO 支持的指征包括心脏手术后休克（25%）、缺血性病因（39%）和其他病因（36%）。73%的患者在 ECMO 前发生心搏骤停，41%的患者在心搏骤停时进行了置管。出院存活率为 39%。三个生存预测模型评分在出院死亡患者中显著高于存活患者；Encourage 评分（25.4 与 20；p=0.04）、APACHE II 评分（23.6 与 19.2；p=0.05）和 ACEF 评分（3.1 与 1.8；p=0.03）。在 ROC 分析中，ACEF 评分的 AUC 为 0.7，具有最大的预测能力。
为 ICU 危重症和 VA-ECMO 患者设计的各种生存预测模型评分在当前患者队列中表现出适度的区分能力。ACEF 评分虽然不是为预测危重症患者的生存而设计的，但表现出了最佳的区分能力。此外，它是最简单的计算方法，在紧急情况下具有优势。
