Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium.
Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK.
Cochrane Database Syst Rev. 2021 Feb 23;2(2):CD013665. doi: 10.1002/14651858.CD013665.pub2.
The clinical implications of SARS-CoV-2 infection are highly variable. Some people with SARS-CoV-2 infection remain asymptomatic, whilst the infection can cause mild to moderate COVID-19 and COVID-19 pneumonia in others. This can lead to some people requiring intensive care support and, in some cases, to death, especially in older adults. Symptoms such as fever, cough, or loss of smell or taste, and signs such as oxygen saturation are the first and most readily available diagnostic information. Such information could be used to either rule out COVID-19, or select patients for further testing. This is an update of this review, the first version of which published in July 2020.
To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID-19 clinics, has COVID-19.
For this review iteration we undertook electronic searches up to 15 July 2020 in the Cochrane COVID-19 Study Register and the University of Bern living search database. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions.
Studies were eligible if they included patients with clinically suspected COVID-19, or if they recruited known cases with COVID-19 and controls without COVID-19. Studies were eligible when they recruited patients presenting to primary care or hospital outpatient settings. Studies in hospitalised patients were only included if symptoms and signs were recorded on admission or at presentation. Studies including patients who contracted SARS-CoV-2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards.
Pairs of review authors independently selected all studies, at both title and abstract stage and full-text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and resolved disagreements by discussion with a third review author. Two review authors independently assessed risk of bias using the Quality Assessment tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic space and in dumbbell plots. We estimated summary parameters using a bivariate random-effects meta-analysis whenever five or more primary studies were available, and whenever heterogeneity across studies was deemed acceptable.
We identified 44 studies including 26,884 participants in total. Prevalence of COVID-19 varied from 3% to 71% with a median of 21%. There were three studies from primary care settings (1824 participants), nine studies from outpatient testing centres (10,717 participants), 12 studies performed in hospital outpatient wards (5061 participants), seven studies in hospitalised patients (1048 participants), 10 studies in the emergency department (3173 participants), and three studies in which the setting was not specified (5061 participants). The studies did not clearly distinguish mild from severe COVID-19, so we present the results for all disease severities together. Fifteen studies had a high risk of bias for selection of participants because inclusion in the studies depended on the applicable testing and referral protocols, which included many of the signs and symptoms under study in this review. This may have especially influenced the sensitivity of those features used in referral protocols, such as fever and cough. Five studies only included participants with pneumonia on imaging, suggesting that this is a highly selected population. In an additional 12 studies, we were unable to assess the risk for selection bias. This makes it very difficult to judge the validity of the diagnostic accuracy of the signs and symptoms from these included studies. The applicability of the results of this review update improved in comparison with the original review. A greater proportion of studies included participants who presented to outpatient settings, which is where the majority of clinical assessments for COVID-19 take place. However, still none of the studies presented any data on children separately, and only one focused specifically on older adults. We found data on 84 signs and symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. Only cough (25 studies) and fever (7 studies) had a pooled sensitivity of at least 50% but specificities were moderate to low. Cough had a sensitivity of 67.4% (95% confidence interval (CI) 59.8% to 74.1%) and specificity of 35.0% (95% CI 28.7% to 41.9%). Fever had a sensitivity of 53.8% (95% CI 35.0% to 71.7%) and a specificity of 67.4% (95% CI 53.3% to 78.9%). The pooled positive likelihood ratio of cough was only 1.04 (95% CI 0.97 to 1.11) and that of fever 1.65 (95% CI 1.41 to 1.93). Anosmia alone (11 studies), ageusia alone (6 studies), and anosmia or ageusia (6 studies) had sensitivities below 50% but specificities over 90%. Anosmia had a pooled sensitivity of 28.0% (95% CI 17.7% to 41.3%) and a specificity of 93.4% (95% CI 88.3% to 96.4%). Ageusia had a pooled sensitivity of 24.8% (95% CI 12.4% to 43.5%) and a specificity of 91.4% (95% CI 81.3% to 96.3%). Anosmia or ageusia had a pooled sensitivity of 41.0% (95% CI 27.0% to 56.6%) and a specificity of 90.5% (95% CI 81.2% to 95.4%). The pooled positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.25 (95% CI 3.17 to 5.71) and 4.31 (95% CI 3.00 to 6.18) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The pooled positive likelihood ratio of ageusia alone was only 2.88 (95% CI 2.02 to 4.09). Only two studies assessed combinations of different signs and symptoms, mostly combining fever and cough with other symptoms. These combinations had a specificity above 80%, but at the cost of very low sensitivity (< 30%).
AUTHORS' CONCLUSIONS: The majority of individual signs and symptoms included in this review appear to have very poor diagnostic accuracy, although this should be interpreted in the context of selection bias and heterogeneity between studies. Based on currently available data, neither absence nor presence of signs or symptoms are accurate enough to rule in or rule out COVID-19. The presence of anosmia or ageusia may be useful as a red flag for COVID-19. The presence of fever or cough, given their high sensitivities, may also be useful to identify people for further testing. Prospective studies in an unselected population presenting to primary care or hospital outpatient settings, examining combinations of signs and symptoms to evaluate the syndromic presentation of COVID-19, are still urgently needed. Results from such studies could inform subsequent management decisions.
严重急性呼吸综合征冠状病毒 2 型（SARS-CoV-2）感染的临床意义差异很大。有些人感染 SARS-CoV-2 后无症状，而有些人则感染轻度至中度 COVID-19 和 COVID-19 肺炎。这可能导致一些人需要重症监护支持，在某些情况下会导致死亡，尤其是老年人。发烧、咳嗽、丧失嗅觉或味觉，以及血氧饱和度等症状以及其他体征，是最初且最容易获得的诊断信息。这些信息可以用来排除 COVID-19，或者选择患者进行进一步检测。这是对本综述的更新，第一版发表于 2020 年 7 月。
评估症状和体征的诊断准确性，以确定在初级保健或医院门诊环境（如急诊科或专门的 COVID-19 诊所）就诊的患者是否患有 COVID-19。
为了进行本次综述迭代，我们在 2020 年 7 月 15 日之前，在 Cochrane COVID-19 研究注册库和伯尔尼大学实时搜索数据库中进行了电子检索。此外，我们还检查了 COVID-19 出版物的资料库。我们没有对语言进行任何限制。
如果研究包括临床疑似 COVID-19 的患者，或者如果研究招募了已知的 COVID-19 病例和对照非 COVID-19 病例，并且招募了在初级保健或医院门诊就诊的患者，则研究可以纳入。如果在入院或就诊时记录了症状和体征，则仅在住院患者中进行的研究可以纳入。如果患者是在住院期间感染 SARS-CoV-2 而不符合纳入条件的，则不包括在研究中。研究的最低合格样本量为 10 名参与者。所有症状和体征均符合本综述的条件，包括单个症状和体征或组合。我们接受了一系列参考标准。
两名综述作者独立地对所有研究进行了标题和摘要阶段以及全文阶段的筛选。对于存在分歧的研究，他们通过与第三名综述作者讨论来解决分歧。两名综述作者独立地提取数据，并通过与第三名综述作者讨论来解决分歧。两名综述作者使用 QUADAS-2 检查表独立地评估了偏倚风险。如果有五个或更多的初级研究可用，并且研究之间的异质性被认为是可以接受的，我们将以成对的森林图、接收器操作特征空间图和哑铃图的形式展示敏感性和特异性。我们使用二元随机效应荟萃分析来估计汇总参数。
我们共确定了 44 项研究，共计 26884 名参与者。COVID-19 的患病率从 3%到 71%不等，中位数为 21%。有三项研究来自初级保健机构（1824 名参与者），九项研究来自门诊检测中心（10717 名参与者），十二项研究在医院门诊病房进行（5061 名参与者），七项研究在住院患者中进行（1048 名参与者），十项研究在急诊科进行（3173 名参与者），三项研究未明确说明地点（5061 名参与者）。这些研究并没有明确区分轻症和重症 COVID-19，因此我们将所有疾病严重程度的结果一起呈现。15 项研究的参与者选择偏倚风险较高，因为纳入研究取决于适用的检测和转诊方案，这些方案包括本综述中许多纳入的症状和体征。这可能会特别影响那些在转诊方案中使用的特征的敏感性，例如发热和咳嗽。五项研究仅包括影像学上有肺炎的患者，这表明这是一个高度选择的人群。在另外 12 项研究中，我们无法评估选择偏倚的风险。这使得很难判断这些纳入研究中症状和体征的诊断准确性的有效性。与原始综述相比，本综述更新后的结果的适用性有所提高。更多的研究纳入了在门诊就诊的参与者，这是大多数 COVID-19 临床评估的地方。然而，仍然没有一项研究分别提供了儿童的数据，只有一项专门针对老年人。我们发现了 84 个症状和体征的数据。研究结果在各研究之间差异很大。大多数的敏感性和特异性都很低。只有咳嗽（25 项研究）和发热（7 项研究）的敏感性至少为 50%，但特异性为中等至低等。咳嗽的敏感性为 67.4%（95%置信区间（CI）59.8%至 74.1%），特异性为 35.0%（95% CI 28.7%至 41.9%）。发热的敏感性为 53.8%（95% CI 35.0%至 71.7%），特异性为 67.4%（95% CI 53.3%至 78.9%）。咳嗽的阳性似然比仅为 1.04（95% CI 0.97 至 1.11），发热的阳性似然比为 1.65（95% CI 1.41 至 1.93）。单独的嗅觉丧失（11 项研究）、味觉丧失（6 项研究）以及嗅觉丧失或味觉丧失（6 项研究）的敏感性低于 50%，但特异性高于 90%。嗅觉丧失的敏感性为 28.0%（95% CI 17.7%至 41.3%），特异性为 93.4%（95% CI 88.3%至 96.4%）。味觉丧失的敏感性为 24.8%（95% CI 12.4%至 43.5%），特异性为 91.4%（95% CI 81.3%至 96.3%）。嗅觉丧失或味觉丧失的敏感性为 41.0%（95% CI 27.0%至 56.6%），特异性为 90.5%（95% CI 81.2%至 95.4%）。嗅觉丧失和嗅觉丧失或味觉丧失的阳性似然比分别为 4.25（95% CI 3.17 至 5.71）和 4.31（95% CI 3.00 至 6.18），这略低于我们定义的“警示症状”的阳性似然比，即至少 5。味觉丧失的阳性似然比仅为 2.88（95% CI 2.02 至 4.09）。只有两项研究评估了不同症状和体征的组合，主要是将发热和咳嗽与其他症状相结合。这些组合的特异性超过 80%，但代价是敏感性非常低（<30%）。
本综述中包括的大多数单一症状和体征似乎具有很差的诊断准确性，尽管这应该结合选择偏倚和研究之间的异质性来解释。根据目前可用的数据，既不存在症状也不存在体征不足以准确排除或确诊 COVID-19。嗅觉丧失或味觉丧失可能是 COVID-19 的一个有用的警示症状。发热或咳嗽的存在，由于其较高的敏感性，也可能有助于识别需要进一步检测的人群。仍迫切需要在初级保健或医院门诊环境中就诊的未选择人群中进行前瞻性研究，以评估 COVID-19 的症状组合，以评估 COVID-19 的综合征表现。这些研究的结果可以为后续的管理决策提供信息。
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