Jeong Daun, Tak Lee Gun, Eun Park Jong, Yeon Hwang Sung, Gun Shin Tae, Do Shin Sang, Choi Jin-Ho
Division of Critical Care Medicine, Department of Emergency Medicine, Chung- Ang University Gwangmyeong Hospital, Gwangmyeong-si, Gyeonggi-do, República de Corea. Department of Emergency Medicine, Chung-Ang University College of Medicine, Seúl, República de Corea.
Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seúl, República de Corea.
Emergencias. 2024 Dec;36(6):408-416. doi: 10.55633/s3me/093.2024.
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).
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%).
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).
The MDS we developed predicts prognosis in patients with OHCA and identifies patients who could benefit from ECLS.
基于初始检测后可得的参数制定代谢紊乱评分(MDS),并评估该评分预测院外心脏骤停(OHCA)后生存情况的能力以及体外生命支持(ECLS)的潜在效用。
纳入韩国心脏骤停研究联盟登记处的5100例病例。患者的平均年龄为67岁,69%为男性。从登记处提取初始检测结果(pH值、动脉血二氧化碳分压、动脉血氧分压以及钾、血红蛋白、乳酸和肌酐水平)。主要复合结局为30天时死亡或神经功能不良(脑功能分类量表,$ 3)。我们在一个开发队列(60%的患者)中使用自动机器学习算法建立MDS模型,并在一个验证队列(40%)中进行测试。
在测试队列中,随着MDS从0升至7,主要结局的风险增加了34%。评分在2或更低的患者,无论是否使用ECLS,结局风险均未增加。然而,基于6.5天的受限平均生存时间和0.76的受限平均时间损失比,评分在3或更高的接受ECLS的患者结局风险确实较低;P <.001,两项比较均如此)。接受或未接受ECLS的患者之间的登记测试结果一致。MDS对复合结局的预测优于OHCA、心脏骤停医院预后和NULL - PLEASE评分(P <.05)。
我们开发的MDS可预测OHCA患者的预后,并识别出可从ECLS中获益的患者。