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COVID-19 住院患者的临床预测模型:一项多中心队列研究。

Clinical prediction models in hospitalized patients with COVID-19: A multicenter cohort study.

机构信息

Internal, Vascular and Emergency Medicine - Stroke Unit, University of Perugia, Perugia, Italy.

Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, Italy; Emergency Medicine Unit, Pisa University Hospital, Italy.

出版信息

Respir Med. 2022 Oct;202:106954. doi: 10.1016/j.rmed.2022.106954. Epub 2022 Aug 21.

DOI:10.1016/j.rmed.2022.106954
PMID:36057141
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9392655/
Abstract

BACKGROUND

Clinical spectrum of novel coronavirus disease (COVID-19) ranges from asymptomatic infection to severe respiratory failure that may result in death. We aimed at validating and potentially improve existing clinical models to predict prognosis in hospitalized patients with acute COVID-19.

METHODS

Consecutive patients with acute confirmed COVID-19 pneumonia hospitalized at 5 Italian non-intensive care unit centers during the 2020 outbreak were included in the study. Twelve validated prognostic scores for pneumonia and/or sepsis and specific COVID-19 scores were calculated for each study patient and their accuracy was compared in predicting in-hospital death at 30 days and the composite of death and orotracheal intubation.

RESULTS

During hospital stay, 302 of 1044 included patients presented critical illness (28.9%), and 226 died (21.6%). Nine out of 34 items included in different prognostic scores were independent predictors of all-cause-death. The discrimination was acceptable for the majority of scores (APACHE II, COVID-GRAM, REMS, CURB-65, NEWS II, ROX-index, 4C, SOFA) to predict in-hospital death at 30 days and poor for the rest. A high negative predictive value was observed for REMS (100.0%) and 4C (98.7%) scores; the positive predictive value was poor overall, ROX-index having the best value (75.0%).

CONCLUSIONS

Despite the growing interest in prognostic models, their performance in patients with COVID-19 is modest. The 4C, REMS and ROX-index may have a role to select high and low risk patients at admission. However, simple predictors as age and PaO2/FiO2 ratio can also be useful as standalone predictors to inform decision making.

摘要

背景

新型冠状病毒病(COVID-19)的临床谱从无症状感染到可能导致死亡的严重呼吸衰竭不等。我们旨在验证并可能改进现有的临床模型,以预测住院 COVID-19 患者的预后。

方法

本研究纳入了 2020 年意大利 5 家非重症监护病房中心住院的急性确诊 COVID-19 肺炎连续患者。计算了 12 种经过验证的肺炎和/或脓毒症预后评分以及特定的 COVID-19 评分,并比较了它们在预测 30 天内院内死亡和死亡或经口气管插管复合终点的准确性。

结果

在住院期间,1044 例患者中有 302 例出现危重症(28.9%),226 例死亡(21.6%)。不同预后评分中包含的 34 项指标中的 9 项是全因死亡的独立预测因素。大多数评分(APACHE II、COVID-GRAM、REMS、CURB-65、NEWS II、ROX-index、4C、SOFA)对预测 30 天内院内死亡的区分度尚可,其余评分则较差。REMS(100.0%)和 4C(98.7%)评分的阴性预测值较高;阳性预测值总体较差,ROX-index 的值最佳(75.0%)。

结论

尽管人们对预后模型的兴趣日益浓厚,但它们在 COVID-19 患者中的表现并不理想。4C、REMS 和 ROX-index 可能在入院时对高危和低危患者具有一定的选择作用。然而,年龄和 PaO2/FiO2 比值等简单预测因素也可作为独立预测因素,用于辅助决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ffd/9392655/a3e710084b69/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ffd/9392655/2ccd7d6078d6/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ffd/9392655/a3e710084b69/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ffd/9392655/2ccd7d6078d6/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ffd/9392655/a3e710084b69/gr2_lrg.jpg

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本文引用的文献

1
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Arch Virol. 2022 Feb;167(2):327-344. doi: 10.1007/s00705-022-05365-2. Epub 2022 Jan 28.
2
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MMWR Morb Mortal Wkly Rep. 2022 Jan 28;71(4):146-152. doi: 10.15585/mmwr.mm7104e4.
3
Efficacy and safety of current treatment interventions for patients with severe COVID-19 infection: A network meta-analysis of randomized controlled trials.
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Ann Med. 2024 Dec;56(1):2407954. doi: 10.1080/07853890.2024.2407954. Epub 2024 Sep 25.
4
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5
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6
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9
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10
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