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基于患者自我报告临床特征的 SARS-CoV-2 感染新型筛查工具:COV-ID 评分。

A new screening tool for SARS-CoV-2 infection based on self-reported patient clinical characteristics: the COV-ID score.

机构信息

Department of Emergency Medicine, La Tour Hospital, 1217, Geneva, Switzerland.

Research Department, La Tour Hospital, 1217, Geneva, Switzerland.

出版信息

BMC Infect Dis. 2022 Feb 24;22(1):187. doi: 10.1186/s12879-022-07164-1.

Abstract

BACKGROUND

While several studies aimed to identify risk factors for severe COVID-19 cases to better anticipate intensive care unit admissions, very few have been conducted on self-reported patient symptoms and characteristics, predictive of RT-PCR test positivity. We therefore aimed to identify those predictive factors and construct a predictive score for the screening of patients at admission.

METHODS

This was a monocentric retrospective analysis of clinical data from 9081 patients tested for SARS-CoV-2 infection from August 1 to November 30 2020. A multivariable logistic regression using least absolute shrinkage and selection operator (LASSO) was performed on a training dataset (60% of the data) to determine associations between self-reported patient characteristics and COVID-19 diagnosis. Regression coefficients were used to construct the Coronavirus 2019 Identification score (COV-ID) and the optimal threshold calculated on the validation dataset (20%). Its predictive performance was finally evaluated on a test dataset (20%).

RESULTS

A total of 2084 (22.9%) patients were tested positive to SARS-CoV-2 infection. Using the LASSO model, COVID-19 was independently associated with loss of smell (Odds Ratio, 6.4), fever (OR, 2.7), history of contact with an infected person (OR, 1.7), loss of taste (OR, 1.5), muscle stiffness (OR, 1.5), cough (OR, 1.5), back pain (OR, 1.4), loss of appetite (OR, 1.3), as well as male sex (OR, 1.05). Conversely, COVID-19 was less likely associated with smoking (OR, 0.5), sore throat (OR, 0.9) and ear pain (OR, 0.9). All aforementioned variables were included in the COV-ID score, which demonstrated on the test dataset an area under the receiver-operating characteristic curve of 82.9% (95% CI 80.6%-84.9%), and an accuracy of 74.2% (95% CI 74.1%-74.3%) with a high sensitivity (80.4%, 95% CI [80.3%-80.6%]) and specificity (72.2%, 95% CI [72.2%-72.4%]).

CONCLUSIONS

The COV-ID score could be useful in early triage of patients needing RT-PCR testing thus alleviating the burden on laboratories, emergency rooms, and wards.

摘要

背景

虽然有几项研究旨在确定 COVID-19 重症病例的危险因素,以便更好地预测入住重症监护病房的情况,但很少有研究针对自我报告的患者症状和特征进行预测,以确定 RT-PCR 检测呈阳性的可能性。因此,我们旨在确定这些预测因素,并构建一个预测评分,用于筛查入院患者。

方法

这是一项针对 2020 年 8 月 1 日至 11 月 30 日期间接受 SARS-CoV-2 感染检测的 9081 例患者的单中心回顾性分析。使用最小绝对值收缩和选择算子(LASSO)对训练数据集(数据的 60%)进行多变量逻辑回归,以确定自我报告的患者特征与 COVID-19 诊断之间的关联。使用回归系数构建冠状病毒 2019 识别评分(COV-ID),并在验证数据集(20%)上计算最佳阈值。最后在测试数据集(20%)上评估其预测性能。

结果

共有 2084 例(22.9%)患者 SARS-CoV-2 感染检测呈阳性。使用 LASSO 模型,COVID-19 与嗅觉丧失(优势比,6.4)、发热(OR,2.7)、与感染者接触史(OR,1.7)、味觉丧失(OR,1.5)、肌肉僵硬(OR,1.5)、咳嗽(OR,1.5)、背痛(OR,1.4)、食欲不振(OR,1.3)以及男性(OR,1.05)独立相关。相反,COVID-19 与吸烟(OR,0.5)、咽痛(OR,0.9)和耳痛(OR,0.9)的相关性较低。所有上述变量均包含在 COV-ID 评分中,该评分在测试数据集上的受试者工作特征曲线下面积为 82.9%(95%CI 80.6%-84.9%),准确性为 74.2%(95%CI 74.1%-74.3%),具有较高的灵敏度(80.4%,95%CI [80.3%-80.6%])和特异性(72.2%,95%CI [72.2%-72.4%])。

结论

COV-ID 评分可用于对需要 RT-PCR 检测的患者进行早期分诊,从而减轻实验室、急诊室和病房的负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1f/8867858/46de7f75343c/12879_2022_7164_Fig1_HTML.jpg

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