葡萄牙重症监护评分协会用于预测肺炎住院患者的SARS-CoV-2感染:一个可靠的工具?

A. Alfaiate, D. Noivo, V. Clérigo, V. Durão, F. Durão, M. Castanho, S. Sousa, L. Fernandes, Paula Duarte
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引用次数: 0

摘要

目的:早期识别2019年新型冠状病毒诱发疾病(新冠肺炎)和肺炎患者目前具有挑战性。关于严重急性呼吸综合征冠状病毒2型(严重急性呼吸系统综合征冠状病毒-2型)感染的有效预测分数,几乎没有可用的数据。葡萄牙重症监护学会(PSIC)提出了一种风险评分,其主要目标是预测新冠肺炎的更高概率,并优化医院资源,调整患者的干预措施。本研究旨在验证应用于肺炎住院患者的PSIC风险评分。方法:对2020年3月20日至5月20日入住疑似/确诊严重急性呼吸系统综合征冠状病毒2型感染专科病房的207名肺炎患者进行回顾性分析。分析评分变量,以确定独立预测变量对严重急性呼吸系统综合征冠状病毒2型rRT PCR检测阳性概率的意义。选择了二元逻辑回归建模方法。最佳截止值由受试者工作特性(ROC)曲线以及通过曲线下面积(AUC)的判别力评估获得。结果:验证队列包括145名患者。典型的胸部计算机断层扫描特征(OR,12.16;95%CI,3.32-44.50)和与严重急性呼吸系统综合征冠状病毒2型阳性患者的接触(OR,6.56;95%CI,1.33-32.30)是最显著的独立预测变量。评分≥10增加了对严重急性呼吸系统综合征冠状病毒2型肺炎的怀疑。AUC为0.82(95%CI,0.73-0.91),表明肺炎住院患者对新冠肺炎概率分层具有良好的辨别能力。结论:PSIC评分在肺炎住院患者中的应用可能对预测新冠肺炎的风险有价值。需要其他中心的进一步研究来广泛验证这一分数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Portuguese Society of Intensive Care Score for Predicting SARS-CoV-2 Infection Applied to Inpatients with Pneumonia: A Reliable Tool?
Objectives: Early identification of patients with the novel coronavirus induced-disease 2019 (COVID-19) and pneumonia is currently challenging. Few data are available on validated scores predictive of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection. The Portuguese Society of Intensive Care (PSIC) proposed a risk score whose main goals were to predict a higher probability of COVID-19 and optimize hospital resources, adjusting patients’ intervention. This study aimed to validate the PSIC risk score applied to inpatients with pneumonia. Methods: A retrospective analysis of 207 patients with pneumonia admitted to a suspected/confirmed SARS-CoV-2 infection specialized ward (20/03 to 20/05/2020) was performed. Score variables were analyzed to determine the significance of the independent predictive variables on the probability of a positive SARS-CoV-2 rRT-PCR test. The binary logistic regression modeling approach was selected. The best cut-off value was obtained with the Receiver Operating Characteristic (ROC) curve together with the evaluation of the discriminatory power through the Area Under the Curve (AUC). Results: The validation cohort included 145 patients. Typical chest computed-tomography features (OR, 12.16; 95% CI, 3.32 - 44.50) and contact with a positive SARS-CoV-2 patient (OR, 6.56; 95% CI, 1.33 - 32.30) were the most significant independent predictive variables. A score ≥ 10 increased suspicion for SARS-CoV-2 pneumonia. The AUC was 0.82 (95% CI, 0.73 - 0.91) demonstrating the good discriminating power for COVID-19 probability stratification in inpatients with pneumonia. Conclusions: The application of the PSIC score to inpatients with pneumonia may be of value in predicting the risk of COVID-19. Further studies from other centers are needed to validate this score widely.
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