Self-Rated Smell Ability Enables Highly Specific Predictors of COVID-19 Status: A Case-Control Study in Israel.
Self-Rated Smell Ability Enables Highly Specific Predictors of COVID-19 Status: A Case-Control Study in Israel.
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自我评估嗅觉能力使新冠肺炎状态的高度特异性预测因素成为可能：以色列的一项病例对照研究。
DOI：
10.1093/ofid/ofaa589
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发表时间：
2021-03
影响因子：
4.2
通讯作者：
Niv MY
中科院分区：
文献类型：
--
作者：
Karni N;Klein H;Asseo K;Benjamini Y;Israel S;Nammary M;Olshtain-Pops K;Nir-Paz R;Hershko A;Muszkat M;Niv MY
2019 年冠状病毒病 (COVID-19) 的临床诊断对于检测和预防 COVID-19 至关重要。突然丧失味觉和嗅觉是 COVID-19 的一个标志，应建立将这些症状纳入患者筛查并将 COVID-19 与其他急性病毒性疾病区分开来的最佳方法。我们对在以色列 COVID-19 大流行第一波（2020 年 3 月至 2020 年 5 月）期间招募的接受聚合酶链反应检测 COVID-19 的患者（112 名阳性参与者和 112 名阴性参与者）进行了病例对照研究。患者通过电话报告他们的症状和病史，并按 1-10 分的等级对患病前和患病期间的嗅觉和味觉能力进行评分。 68%（95% CI，60%–76%）和 72%（95% CI，64%–80%）的阳性患者出现嗅觉和味觉变化，比值比分别为 24（范围，11–53）和 12（范围，6–23）。阴性者的嗅觉能力下降了 0.5 ± 1.5，阳性者的嗅觉能力下降了 4.5 ± 3.6。基于 5 种症状的惩罚逻辑回归分类器的敏感性为 66%，特异性为 97%，在坚持组上受试者操作特征曲线下面积 (AUC) 为 0.83。基于气味变化程度的分类器几乎同样好，灵敏度为 66%，特异性为 97%，AUC 为 0.81。该分类器的阳性预测值为0.68，阴性预测值为0.97。自我报告的定量嗅觉变化，无论是单独的还是与其他症状相结合，都为 COVID-19 的临床诊断提供了特定的工具。此处提供了一个用于优先考虑 COVID-19 实验室检测的简单计算器。
Clinical diagnosis of coronavirus disease 2019 (COVID-19) is essential to the detection and prevention of COVID-19. Sudden onset of loss of taste and smell is a hallmark of COVID-19, and optimal ways for including these symptoms in the screening of patients and distinguishing COVID-19 from other acute viral diseases should be established. We performed a case–control study of patients who were polymerase chain reaction–tested for COVID-19 (112 positive and 112 negative participants), recruited during the first wave (March 2020–May 2020) of the COVID-19 pandemic in Israel. Patients reported their symptoms and medical history by phone and rated their olfactory and gustatory abilities before and during their illness on a 1–10 scale. Changes in smell and taste occurred in 68% (95% CI, 60%–76%) and 72% (95% CI, 64%–80%) of positive patients, with odds ratios of 24 (range, 11–53) and 12 (range, 6–23), respectively. The ability to smell was decreased by 0.5 ± 1.5 in negatives and by 4.5 ± 3.6 in positives. A penalized logistic regression classifier based on 5 symptoms had 66% sensitivity, 97% specificity, and an area under the receiver operating characteristics curve (AUC) of 0.83 on a holdout set. A classifier based on degree of smell change was almost as good, with 66% sensitivity, 97% specificity, and 0.81 AUC. The predictive positive value of this classifier was 0.68, and the negative predictive value was 0.97. Self-reported quantitative olfactory changes, either alone or combined with other symptoms, provide a specific tool for clinical diagnosis of COVID-19. A simple calculator for prioritizing COVID-19 laboratory testing is presented here.