Rahmatinejad Zahra, Hoseini Benyamin, Reihani Hamidreza, Hanna Ameen Abu, Pourmand Ali, Tabatabaei Seyyed Mohammad, Rahmatinejad Fatemeh, Eslami Saeid
Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Pharmaceutical Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran.
Indian J Crit Care Med. 2023 Jun;27(6):416-425. doi: 10.5005/jp-journals-10071-24463.
The study aimed to compare the prognostic accuracy of six different severity-of-illness scoring systems for predicting in-hospital mortality among patients with confirmed SARS-COV2 who presented to the emergency department (ED). The scoring systems assessed were worthing physiological score (WPS), early warning score (EWS), rapid acute physiology score (RAPS), rapid emergency medicine score (REMS), national early warning score (NEWS), and quick sequential organ failure assessment (qSOFA).
A cohort study was conducted using data obtained from electronic medical records of 6,429 confirmed SARS-COV2 patients presenting to the ED. Logistic regression models were fitted on the original severity-of-illness scores to assess the models' performance using the Area Under the Curve for ROC (AUC-ROC) and Precision-Recall curves (AUC-PR), Brier Score (BS), and calibration plots were used to assess the models' performance. Bootstrap samples with multiple imputations were used for internal validation.
The mean age of the patients was 64 years (IQR:50-76) and 57.5% were male. The WPS, REMS, and NEWS models had AUROC of 0.714, 0.705, and 0.701, respectively. The poorest performance was observed in the RAPS model, with an AUROC of 0.601. The BS for the NEWS, qSOFA, EWS, WPS, RAPS, and REMS was 0.18, 0.09, 0.03, 0.14, 0.15, and 0.11 respectively. Excellent calibration was obtained for the NEWS, while the other models had proper calibration.
The WPS, REMS, and NEWS have a fair discriminatory performance and may assist in risk stratification for SARS-COV2 patients presenting to the ED. Generally, underlying diseases and most vital signs are positively associated with mortality and were different between the survivors and non-survivors.
Rahmatinejad Z, Hoseini B, Reihani H, Hanna AA, Pourmand A, Tabatabaei SM, . Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department. Indian J Crit Care Med 2023;27(6):416-425.
本研究旨在比较六种不同的疾病严重程度评分系统对急诊科确诊的新型冠状病毒肺炎患者院内死亡率的预测准确性。评估的评分系统包括沃辛生理评分（WPS）、早期预警评分（EWS）、快速急性生理学评分（RAPS）、快速急诊医学评分（REMS）、国家早期预警评分（NEWS）和快速序贯器官衰竭评估（qSOFA）。
采用队列研究，数据来源于6429例急诊科确诊的新型冠状病毒肺炎患者的电子病历。对原始疾病严重程度评分进行逻辑回归模型拟合，使用ROC曲线下面积（AUC-ROC）和精确召回曲线（AUC-PR）评估模型性能，采用布里尔评分（BS）和校准图评估模型性能。使用多次插补的自助抽样进行内部验证。
患者的平均年龄为64岁（四分位间距：50-76），57.5%为男性。WPS、REMS和NEWS模型的AUC-ROC分别为0.714、0.705和0.701。RAPS模型表现最差，AUC-ROC为0.601。NEWS、qSOFA、EWS、WPS、RAPS和REMS的BS分别为0.18、0.09、0.03、0.14、0.15和0.11。NEWS获得了良好的校准，而其他模型校准良好。
WPS、REMS和NEWS具有较好的鉴别性能，可能有助于对急诊科的新型冠状病毒肺炎患者进行风险分层。一般来说，基础疾病和大多数生命体征与死亡率呈正相关，幸存者和非幸存者之间存在差异。
Rahmatinejad Z, Hoseini B, Reihani H, Hanna AA, Pourmand A, Tabatabaei SM, . 六种评分系统对急诊科新型冠状病毒肺炎患者院内死亡率预测的比较。《印度重症监护医学杂志》2023；27(6):416-425。
