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COVID-MATCH65:一种用于严重急性呼吸综合征冠状病毒 2 的前瞻性临床决策规则。

COVID-MATCH65-A prospectively derived clinical decision rule for severe acute respiratory syndrome coronavirus 2.

机构信息

Department of Infectious Diseases, Austin Health, Heidelberg, Australia.

Department of Medicine, Austin Health, University of Melbourne, Heidelberg, Australia.

出版信息

PLoS One. 2020 Dec 9;15(12):e0243414. doi: 10.1371/journal.pone.0243414. eCollection 2020.

Abstract

OBJECTIVES

We report on the key clinical predictors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and present a clinical decision rule that can risk stratify patients for COVID-19.

DESIGN, PARTICIPANTS AND SETTING: A prospective cohort of patients assessed for COVID-19 at a screening clinic in Melbourne, Australia. The primary outcome was a positive COVID-19 test from nasopharyngeal swab. A backwards stepwise logistic regression was used to derive a model of clinical variables predictive of a positive COVID-19 test. Internal validation of the final model was performed using bootstrapped samples and the model scoring derived from the coefficients, with modelling performed for increasing prevalence.

RESULTS

Of 4226 patients with suspected COVID-19 who were assessed, 2976 patients underwent SARS-CoV-2 testing (n = 108 SARS-CoV-2 positive) and were used to determine factors associated with a positive COVID-19 test. The 7 features associated with a positive COVID-19 test on multivariable analysis were: COVID-19 patient exposure or international travel, Myalgia/malaise, Anosmia or ageusia, Temperature, Coryza/sore throat, Hypoxia-oxygen saturation < 97%, 65 years or older-summarized in the mnemonic COVID-MATCH65. Internal validation showed an AUC of 0.836. A cut-off of ≥ 1.5 points was associated with a 92.6% sensitivity and 99.5% negative predictive value (NPV) for COVID-19.

CONCLUSIONS

From the largest prospective outpatient cohort of suspected COVID-19 we define the clinical factors predictive of a positive SARS-CoV-2 test. The subsequent clinical decision rule, COVID-MATCH65, has a high sensitivity and NPV for SARS-CoV-2 and can be employed in the pandemic, adjusted for disease prevalence, to aid COVID-19 risk-assessment and vital testing resource allocation.

摘要

目的

我们报告了严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 感染的关键临床预测因素,并提出了一种临床决策规则,可以对 COVID-19 患者进行风险分层。

设计、参与者和地点:在澳大利亚墨尔本的一个筛查诊所评估 COVID-19 的前瞻性队列。主要结局是鼻咽拭子 COVID-19 检测阳性。采用向后逐步逻辑回归方法,从预测 COVID-19 检测阳性的临床变量中得出模型。使用bootstrap 样本和模型评分系数对内验证最终模型,然后针对不同的流行率进行建模。

结果

在 4226 名疑似 COVID-19 的患者中,有 2976 名患者接受了 SARS-CoV-2 检测(n = 108 例 SARS-CoV-2 阳性),并用于确定与 COVID-19 检测阳性相关的因素。多变量分析中与 COVID-19 检测阳性相关的 7 个特征是:COVID-19 患者接触或国际旅行、肌肉痛/不适、嗅觉丧失或味觉丧失、体温、鼻塞/咽痛、低氧-氧饱和度<97%、年龄≥65 岁-概括为 COVID-MATCH65 记忆法。内部验证显示 AUC 为 0.836。截断值≥1.5 分与 COVID-19 的 92.6%敏感性和 99.5%阴性预测值(NPV)相关。

结论

从最大的前瞻性门诊疑似 COVID-19 队列中,我们确定了预测 SARS-CoV-2 检测阳性的临床因素。随后的 COVID-MATCH65 临床决策规则对 SARS-CoV-2 具有高敏感性和 NPV,可以在大流行期间使用,根据疾病流行率进行调整,以帮助 COVID-19 风险评估和重要检测资源分配。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74fc/7725390/f7c6c50b58bb/pone.0243414.g001.jpg

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