Baloglu Orkun, Kormos Kristopher, Worley Sarah, Latifi Samir Q
Department of Pediatric Critical Care Medicine, Cleveland Clinic Children's, Cleveland, Ohio, United States.
Cleveland Clinic Children's Center for Artificial Intelligence, Cleveland, Ohio, United States.
J Pediatr Intensive Care. 2022 Feb 18;13(4):352-355. doi: 10.1055/s-0042-1742675. eCollection 2024 Dec.
The aim of this study was to describe the performance of a novel Situational Awareness Scoring System (SASS) in discriminating between patients who had cardiac arrest (CA), and those who did not, in a pediatric cardiac intensive care unit (PCICU). This is a retrospective, observational-cohort study in a quaternary-care PCICU. Patients who had CA in the PCICU between January 2014 and December 2018, and patients admitted to the PCICU in 2018 who did not have CA were included. Patients with do not resuscitate or do not intubate orders, extracorporeal membrane oxygenation, ventricular assist device, and PCICU stay < 2 hours were excluded. SASS score statistics were calculated within 2-, 4-, 6-, and 8-hour time intervals counting backward from the time of CA, or end of PCICU stay in patients who did not have CA. Cross-validated discrete time logistic regression models were used to calculate area under the receiver operating characteristic (AUC) curves. Odds ratios (ORs) for CA were calculated per unit increase of the SASS score. Twenty-eight CA events were analyzed in 462 PCICU admissions from 267 patients. Maximum SASS score within 4-hour time interval before CA achieved the highest AUC of 0.91 (95% confidence interval [CI]: 0.86-0.96) compared with maximum SASS score within 2-, 6-, and 8-hour time intervals before CA of 0.88 (0.79-96), 0.90 (0.85-0.95), and 0.89 (0.83-0.95), respectively. A cutoff value of 60 for maximum SASS score within 4-hour time interval before CA resulted in 82.1 and 83.2% of sensitivity and specificity, respectively. OR for CA was 1.32 (95% CI: 1.26-1.39) for every 10 units increase in the maximum SASS score within each 4-hour time interval before CA. The maximum SASS score within various time intervals before CA achieved promising performance in discriminating patients regarding occurrence of CA.
本研究旨在描述一种新型情景意识评分系统（SASS）在区分儿科心脏重症监护病房（PCICU）中发生心脏骤停（CA）的患者与未发生心脏骤停的患者方面的表现。这是一项在四级护理PCICU中进行的回顾性观察队列研究。纳入了2014年1月至2018年12月期间在PCICU发生CA的患者，以及2018年入住PCICU但未发生CA的患者。排除有不进行心肺复苏或不插管医嘱、体外膜肺氧合、心室辅助装置以及PCICU住院时间<2小时的患者。SASS评分统计是在从CA发生时间或未发生CA患者的PCICU住院结束时间开始倒推的2小时、4小时、6小时和8小时间隔内计算的。使用交叉验证的离散时间逻辑回归模型来计算受试者操作特征（AUC）曲线下的面积。每增加一个单位的SASS评分，计算CA的比值比（OR）。对来自267例患者的462次PCICU入院中的28次CA事件进行了分析。与CA发生前2小时、6小时和8小时间隔内的最大SASS评分分别为0.88（0.79 - 0.96）、0.90（0.85 - 0.95）和0.89（0.83 - 0.95）相比，CA发生前4小时间隔内的最大SASS评分达到了最高的AUC为0.91（95%置信区间[CI]：0.86 - 0.96）。CA发生前4小时间隔内最大SASS评分的截断值为60时，敏感性和特异性分别为82.1%和83.2%。在CA发生前的每个4小时间隔内，最大SASS评分每增加10个单位，CA的OR为1.32（95% CI：1.26 - 1.39）。CA发生前不同时间间隔内的最大SASS评分在区分患者是否发生CA方面表现出良好的性能。
