Severity of metabolic derangement predicts survival after out-of-hospital cardiac arrest and the likelihood of benefiting from extracorporeal life support.

Daun Jeong, Gun Tak Lee, Jong Eun Park, Sung Yeon Hwang, Tae Gun Shin, Sang Do Shin, Jin-Ho Choi
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Abstract

Objective: To develop a Metabolic Derangement Score (MDS) based on parameters available after initial testing and assess the score's ability to predict survival after out-of hospital cardiac arrest (OHCA) and the likely usefulness of extracorporeal life support (ECLS).

Methods: A total of 5100 cases in the Korean Cardiac Arrest Research Consortium registry were included. Patients' mean age was 67 years, and 69% were men. Findings from initial tests (pH; PaCO2; PaO2; and potassium, hemoglobin, lactate, and creatinine levels) were extracted from the registry. The primary composite outcome was death or poor neurologic outcome (Cerebral Performance Category Scale, $ 3) at 30 days. We developed the model for the MDS using automated machine learning algorithms in a development cohort (60% of the patients) and tested it in a validation cohort (40%).

Results: Risk for the primary outcome increased by 34% as the MDS rose from 0 to 7 in the test cohort. Patients with scores of 2 or lower had no increased risk for the outcome according to whether ECLS had been used or not. However, ECLS patients with a score of 3 or more did have lower risk for the outcome, based on a restricted mean survival time of 6.5 days and a ratio of restricted mean time lost of 0.76; P .001, both comparisons). Registered test results were consistent between patients who did or did not receive ECLS. The MDS predicted the composite outcome better than the OHCA, Cardiac Arrest Hospital Prognosis, and NULL-PLEASE scores (P .05).

Conclusions: The MDS we developed predicts prognosis in patients with OHCA and identifies patients who could benefit from ECLS.

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代谢紊乱的严重程度预示着院外心脏骤停后的生存以及从体外生命支持中获益的可能性。
目的:基于初始测试后可获得的参数开发代谢紊乱评分(MDS),并评估该评分预测院外心脏骤停(OHCA)后生存的能力和体外生命支持(ECLS)的可能用途。方法:韩国心脏骤停研究协会登记的5100例病例被纳入研究。患者平均年龄为67岁,69%为男性。初步测试结果(pH值;PaCO2;PaO2;钾、血红蛋白、乳酸和肌酐水平)从注册表中提取。30天的主要综合结局是死亡或神经系统预后差(脑功能分类量表,3美元)。我们在开发队列(60%的患者)中使用自动机器学习算法开发了MDS模型,并在验证队列(40%)中对其进行了测试。结果:在测试队列中,随着MDS从0上升到7,主要结局的风险增加了34%。无论是否使用ECLS,评分为2分或更低的患者的预后风险均未增加。然而,基于6.5天的限制平均生存时间和0.76的限制平均时间损失比,评分为3分或以上的ECLS患者的结局风险较低;P .001,两个比较)。注册的测试结果在接受或未接受ECLS的患者之间是一致的。MDS对综合预后的预测优于OHCA、心脏骤停医院预后和NULL-PLEASE评分(P < 0.05)。结论:我们开发的MDS可以预测OHCA患者的预后,并确定可以从ECLS中获益的患者。
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