PMC:7386785 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/7386785","sourcedb":"PMC","sourceid":"7386785","source_url":"https://www.ncbi.nlm.nih.gov/pmc/7386785","text":"Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID‐19 disease\n\nAbstract\nAbstract\n\nBackground\nSome people with SARS‐CoV‐2 infection remain asymptomatic, whilst in others the infection can cause mild to moderate COVID‐19 disease and COVID‐19 pneumonia, leading some patients to require intensive care support and, in some cases, to death, especially in older adults. Symptoms such as fever or cough, and signs such as oxygen saturation or lung auscultation findings, are the first and most readily available diagnostic information. Such information could be used to either rule out COVID‐19 disease, or select patients for further diagnostic testing.\n\nObjectives\nTo 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 disease or COVID‐19 pneumonia.\n\nSearch methods\nOn 27 April 2020, we undertook electronic searches in the Cochrane COVID‐19 Study Register and the University of Bern living search database, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID‐19 publications. We did not apply any language restrictions.\n\nSelection criteria\nStudies were eligible if they included patients with suspected COVID‐19 disease, or if they recruited known cases with COVID‐19 disease and controls without COVID‐19. Studies were eligible when they recruited patients presenting to primary care or hospital outpatient settings. 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 including reverse transcription polymerase chain reaction (RT‐PCR), clinical expertise, imaging, serology tests and World Health Organization (WHO) or other definitions of COVID‐19.\n\nData collection and analysis\nPairs 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 QUADAS‐2 checklist. Analyses were descriptive, presenting sensitivity and specificity in paired forest plots, in ROC (receiver operating characteristic) space and in dumbbell plots. We did not attempt meta‐analysis due to the small number of studies, heterogeneity across studies and the high risk of bias.\n\nMain results\nWe identified 16 studies including 7706 participants in total. Prevalence of COVID‐19 disease varied from 5% to 38% with a median of 17%. There were no studies from primary care settings, although we did find seven studies in outpatient clinics (2172 participants), and four studies in the emergency department (1401 participants). We found data on 27 signs and symptoms, which fall into four different categories: systemic, respiratory, gastrointestinal and cardiovascular. No studies assessed combinations of different signs and symptoms and results were highly variable across studies. Most had very low sensitivity and high specificity; only six symptoms had a sensitivity of at least 50% in at least one study: cough, sore throat, fever, myalgia or arthralgia, fatigue, and headache. Of these, fever, myalgia or arthralgia, fatigue, and headache could be considered red flags (defined as having a positive likelihood ratio of at least 5) for COVID‐19 as their specificity was above 90%, meaning that they substantially increase the likelihood of COVID‐19 disease when present.\nSeven studies carried 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. Five studies only included participants with pneumonia on imaging, suggesting that this is a highly selected population. In an additional four studies, we were unable to assess the risk for selection bias. These factors make it very difficult to determine the diagnostic properties of these signs and symptoms from the included studies.\nWe also had concerns about the applicability of these results, since most studies included participants who were already admitted to hospital or presenting to hospital settings. This makes these findings less applicable to people presenting to primary care, who may have less severe illness and a lower prevalence of COVID‐19 disease. None of the studies included any data on children, and only one focused specifically on older adults. We hope that future updates of this review will be able to provide more information about the diagnostic properties of signs and symptoms in different settings and age groups.\n\nAuthors' conclusions\nThe individual signs and symptoms included in this review appear to have very poor diagnostic properties, 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 disease. 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 disease, are urgently needed. Results from such studies could inform subsequent management decisions such as self‐isolation or selecting patients for further diagnostic testing. We also need data on potentially more specific symptoms such as loss of sense of smell. Studies in older adults are especially important.\n\nPlain language summary\nCan symptoms and medical examination accurately diagnose COVID‐19 disease?\nCOVID‐19 is an infectious disease caused by the SARS‐CoV‐2 virus. Most people with COVID‐19 have a mild to moderate respiratory illness; others experience severe illness, such as COVID‐19 pneumonia. Formal diagnosis requires laboratory analysis of nose and throat samples, or imaging tests like CT scans. However, the first and most accessible diagnostic information is from symptoms and signs from clinical examination. If initial diagnosis by symptoms and signs were accurate, the need for time‐consuming, specialist diagnostic tests would be reduced.\nSymptoms are experienced by patients. People with mild COVID‐19 might experience cough, sore throat, high temperature, diarrhoea, headache, muscle or joint pain, fatigue, and loss of sense of smell and taste. Symptoms of COVID‐19 pneumonia include breathlessness, loss of appetite, confusion, pain or pressure in the chest, and high temperature (above 38 °C).\nSigns are evaluated by clinical examination, and include lung sounds, blood pressure and heart rate.\nOften, people with mild symptoms visit their doctor (primary care physician) for an initial diagnosis. People with more severe symptoms might visit a hospital outpatient or emergency department. Depending on their symptoms and signs, patients may be sent home to isolate, may receive further tests or be hospitalised.\nWhy is accurate diagnosis important?\nAccurate diagnosis ensures that people receive the correct treatment quickly; are not tested, treated or isolated unnecessarily; and do not risk spreading COVID‐19. This is important for individuals and saves time and resources.\nWhat did we want to find out?\nWe wanted to know how accurate diagnosis of COVID‐19 and COVID‐19 pneumonia is in a primary care or hospital setting, based on symptoms and signs from medical examination.\nWhat did we do?\nWe searched for studies that assessed the accuracy of symptoms and signs to diagnose mild COVID‐19 and COVID‐19 pneumonia. Studies could include people with possible COVID‐19, or people known to have – and not to have – COVID‐19. Studies had to be in primary care or hospital outpatient settings only and include at least 10 participants with any symptom or sign that might be COVID‐19.\nThe included studies\nWe found 16 relevant studies with 7706 participants. The studies assessed 27 separate signs and symptoms, but none assessed combinations of signs and symptoms. Seven were set in hospital outpatient clinics (2172 participants), four in emergency departments (1401 participants), but none in primary care settings. No studies included children, and only one focused on older adults. All the studies confirmed COVID‐19 diagnosis by the most accurate tests available.\nMain results\nThe studies did not clearly distinguish mild to moderate COVID‐19 from COVID‐19 pneumonia, so we present the results for both conditions together.\nThe results indicate that at least half of participants with COVID‐19 disease had a cough, sore throat, high temperature, muscle or joint pain, fatigue, or headache. However, cough and sore throat were also common in people without COVID‐19, so these symptoms alone are less helpful for diagnosing COVID‐19. High temperature, muscle or joint pain, fatigue, and headache substantially increase the likelihood of COVID‐19 disease when they are present.\nHow reliable are the results?\nThe accuracy of individual symptoms and signs varied widely across studies. Moreover, the studies selected participants in a way that meant the accuracy of tests based on symptoms and signs may be uncertain.\nConclusions\nAll studies were conducted in hospital outpatient settings, so the results are not representative of primary care settings. The results do not apply to children or older adults specifically, and do not clearly differentiate between milder COVID‐19 disease and COVID‐19 pneumonia.\nThe results suggest that a single symptom or sign included in this review cannot accurately diagnose COVID‐19. Doctors base diagnosis on multiple symptoms and signs, but the studies did not reflect this aspect of clinical practice.\nFurther research is needed to investigate combinations of symptoms and signs; symptoms that are likely to be more specific, such as loss of sense of smell; and testing unselected populations, in primary care settings and in children and older adults.\nHow up to date is this review?\nThe review authors searched for studies published from January to April 2020.\n\nSummary of findings\nSummary of findings 1 Signs and symptoms to determine if a patient presenting in primary care or outpatient hospital setting has COVID‐19 disease\nSign or symptom Study design Setting Number of studies/number of participants Sensitivity (ranges) Specificity (ranges) Strength of evidence Number of studies with high risk of bias per QUADAS‐2 domain: participant selection/index test/reference standard/flow and timing\nCough Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 7/2554 0.43 to 0.71 0.14 to 0.54 3/7/1/2\nHospital inpatientsa 1/53 0.55 0.42 1/1/0/0\nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/262 0.36 0.49 0/1/0/0\nHospital inpatientsa 2/170 0.47 to 0.69 0.15 to 0.20 2/1/0/0\nSputum production Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 6/2467 0.16 to 0.33 0.50 to 0.86 3/6/1/2\nHospital inpatientsa ‐ ‐ ‐  \nDyspnoea Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 7/2554 0.00 to 0.25 0.82 to 0.98 3/7/1/2\nHospital inpatientsa ‐ ‐ ‐  \nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/262 0.12 0.77 0/1/0/0\nHospital inpatientsa ‐ ‐ ‐  \nHypoxia Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/2929b 0.15 0.83 0/0/0/0\nHospital inpatientsa ‐ ‐ ‐  \nHaemoptysis Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/116 0.00 0.99 0/1/0/0\nHospital inpatientsa ‐ ‐ ‐  \nPositive auscultation findings Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/788 0.11 0.95 1/1/0/0\nHospital inpatientsa ‐ ‐ ‐  \nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics ‐ ‐ ‐  \nHospital inpatientsa 1/34 0.11 0.67 1/1/0/0\nRespiratory symptoms (not otherwise specified) Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/788 0.04 0.95 1/1/0/0\nHospital inpatientsa ‐ ‐ ‐  \nSore throat Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 6/2438 0.05 to 0.71 0.55 to 0.80 3/6/1/2\nHospital inpatientsa ‐ ‐ ‐  \nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/262 0.17 0.55 0/1/0/0\nHospital inpatientsa 2/170 0.13 to 0.21 0.73 to 0.91 2/1/0/0\nNasal symptoms Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 5/2405 0.00 to 0.22 0.69 to 0.92 2/5/1/2\nHospital inpatientsa ‐ ‐ ‐  \nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/262 0.19 0.79 0/1/0/0\nHospital inpatientsa 1/136 0.03 for nasal obstruction0.04 for rhinorrhoea 0.94 for nasal obstruction0.95 for rhinorrhoea 1/0/0/0\nLoss of sense of smell or taste Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/870 0.23 0.99 0/1/0/0\nHospital inpatientsa ‐ ‐ ‐  \nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/262 0.22 for smell0.20 for taste 0.96 for smell0.95 for taste 0/1/0/0\nHospital inpatientsa ‐ ‐ ‐  \nFever Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 8/5315 0.07 to 0.93 0.16 to 0.94 2/7/1/2\nHospital inpatientsa 1/53 0.80 0.48 1/1/0/0\nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/262 0.54 0.74 0/1/0/0\nHospital inpatientsa 1/34 0.79 0.07 1/1/0/0\nLow body temperature Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/2929b 0.37 0.32 0/0/0/0\nHospital inpatientsa ‐ ‐ ‐  \nShivers Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/132 0.14 0.86 0/1/1/1\nHospital inpatientsa ‐ ‐ ‐  \nChills Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 2/1443 0.07 to 0.29 0.72 to 0.91 0/2/1/1\nHospital inpatientsa ‐ ‐ ‐  \nMyalgia or arthralgia Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 4/339 0.19 to 0.86 0.45 to 0.91 2/4/1/2\nHospital inpatientsa ‐ ‐ ‐  \nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/262 0.34 0.81 0/1/0/0\nHospital inpatientsa ‐ ‐ ‐  \nMyalgia or fatigue Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 2/1427 0.16 to 0.31 0.82 to 0.93 0/2/0/0\nHospital inpatientsa ‐ ‐ ‐  \nFatigue Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 2/220 0.43 to 0.57 0.60 to 0.67 1/2/1/2\nHospital inpatientsa 1/53 0.10 0.94 1/1/0/0\nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/262 0.42 0.69 0/1/0/0\nHospital inpatientsa 2/170 0.11 to 0.31 0.88 to 1.00 2/1/0/0\nHeadache Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 4/1647 0.03 to 0.71 0.78 to 0.98 1/4/1/2\nHospital inpatientsa 1/53 0.15 0.97 1/1/0/0\nNausea/vomiting Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 2/436 0.00 to 0.04 0.97 to 0.97 0/2/1/1\nHospital inpatientsa 1/53 0.05 1.00 1/1/0/0\nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 2/778 0.05 to 0.23 0.81 to 0.96 0/2/0/0\nHospital inpatientsa ‐ ‐ ‐  \nDiarrhoea Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 5/1680 0.00 to 0.14 0.86 to 0.99 2/5/1/2\nHospital inpatientsa 1/53 0.15 0.88 1/1/0/0\nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 2/778 0.08 to 0.20 0.85 to 0.92 0/2/0/0\nHospital inpatientsa 1/34 0.05 0.93 1/1/0/0\nAbdominal pain Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/132 0.00 0.96 0/1/1/1\nHospital inpatientsa 1/53 0.05 1.00 1/1/0/0\nGastrointestinal symptoms Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/788 0.37 0.68 1/1/0/0\nHospital inpatientsa ‐ ‐ ‐  \nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/516 0.35 0.74 0/1/0/0\nHospital inpatientsa ‐ ‐ ‐  \nLow systolic blood pressure Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/3341b 0.11 0.90 0/0/0/0\nHospital inpatientsa ‐ ‐ ‐  \nHigh systolic blood pressure Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/3341 0.39 0.57 0/0/0/0\nHospital inpatientsa ‐ ‐ ‐  \nTachycardia Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/3373 0.47 0.62 0/0/0/0\nHospital inpatientsa ‐ ‐ ‐  \nPalpitations Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics 1/132 0.00 0.98 0/1/1/1\nHospital inpatientsa ‐ ‐ ‐  \nChest tightness Cross‐sectional Primary care ‐ ‐ ‐  \nHospital outpatient clinics ‐ ‐ ‐  \nHospital inpatientsa ‐ ‐ ‐  \nCase‐control Primary care ‐ ‐ ‐  \nHospital outpatient clinics ‐ ‐ ‐  \nHospital inpatientsa 1/34 0.05 1.00 1/1/0/0\na'Hospital inpatients' refers to studies that recruited patients admitted to hospital with COVID‐19 disease and in whom the signs and symptoms were assessed on admission.\u2028bSetting not specified; assumed hospital outpatients considering the timing in the epidemic and sparse testing capacity outside hospitals at the time (Rentsch 2020).\n\nBackground\nThe severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and resulting COVID‐19 pandemic present important diagnostic evaluation challenges. These range from, on the one hand, understanding the value of signs and symptoms in predicting possible infection, assessing whether existing biochemical and imaging tests can identify infection and recognise patients needing critical care, and on the other hand, evaluating whether new diagnostic tests can allow accurate rapid and point‐of‐care testing. Also, the diagnostic aims are diverse, including identifying current infection, ruling out infection, identifying people in need of care escalation, or testing for past infection.\nThis review is part of a cluster of reviews on the diagnosis of SARS‐CoV‐2 infection and COVID‐19 disease, and deals solely with the diagnostic accuracy of presenting clinical signs and symptoms for diagnosing COVID‐19 disease.\n\nTarget condition being diagnosed\nCOVID‐19 is the disease caused by infection with the SARS‐CoV‐2 virus. SARS‐CoV‐2 infection is diagnosed with reverse transcription polymerase chain reaction (RT‐PCR), which is a test that detects the virus' genetic material, with imaging to identify lung abnormalities and with clinical signs and symptoms.\nSARS‐CoV‐2 infection can be asymptomatic (no symptoms); mild or moderate; severe (causing breathlessness and increased respiratory rate indicative of pneumonia and oxygen need); or critical (requiring intensive support due to severe acute respiratory syndrome (SARS) or acute respiratory distress syndrome (ARDS), shock or other organ dysfunction). People with COVID‐19 pneumonia (severe or critical disease), require different patient management, which makes it important to distinguish between mild or moderate COVID‐19 disease and COVID‐19 pneumonia.\nIn this review, we will examine the diagnostic value of signs and symptoms for symptomatic SARS‐CoV‐2 infection, which includes mild or moderate COVID‐19 disease and COVID‐19 pneumonia.\nIn planning review updates, we will consider the potential addition of another grouping, which is a subset of the above:\nwhether tests exist that identify people requiring respiratory support (SARS or ARDS) or intensive care.\n\nIndex test(s)\n\nSigns and symptoms\nSigns and symptoms are used in the initial diagnosis of suspected COVID‐19 disease, and to identify people with COVID‐19 pneumonia. Symptoms are what is experienced by patients, for example cough or nausea. Signs are what can be evaluated by clinical assessment, for example lung auscultation findings, blood pressure or heart rate.\nKey symptoms that have been associated with mild to moderate COVID‐19 disease include: troublesome dry cough (for example, coughing more than usual over a one‐hour period, or three or more coughing episodes in 24 hours), fever greater than 37.8 °C, diarrhoea, headache, breathlessness on light exertion, muscle pain, fatigue, and loss of sense of smell and taste. Red flags indicating possible pneumonia include breathlessness at rest, loss of appetite, confusion, pain or pressure in the chest, and temperature above 38 °C.\n\nClinical pathway\nImportant in the context of COVID‐19 is that the pathway is multifaceted because it is designed to care for the diseased individual and to protect the community from further spread. Decisions about patient and isolation pathways for COVID‐19 vary according to health services and settings, available resources, and stages of the epidemic. They will change over time, if and when effective treatments and vaccines are identified. The decision points between these pathways vary, but all include points at which knowledge of the accuracy of diagnostic information is needed to be able to inform rational decision making.\n\nPrior test(s)\nIn this review on signs and symptoms, no prior tests are required because signs and symptoms are used in the initial diagnosis of suspected COVID‐19 disease. Patients can, however, self‐assess before presenting to healthcare services based on their symptoms. This is in contrast to contact tracing, in which patients or participants are tested based on a documented contact with a SARS‐CoV‐2‐positive person and may themselves be asymptomatic.\n\nRole of index test(s)\nSigns and symptoms are used as triage tests, that is, to rule out COVID‐19 disease, but also to identify patients with possible COVID‐19 who may require further testing, care escalation or isolation.\n\nAlternative test(s)\nChest X‐ray, ultrasound, and computed tomography (CT) are widely used diagnostic imaging tests to diagnose COVID‐19 pneumonia. Availability and usage varies between settings. We address these radiological tests in a separate review.\n\nRationale\nIt is essential to understand the accuracy of diagnostic tests including signs and symptoms to identify the best way they can be used in different settings to develop effective diagnostic and management pathways. We are producing a suite of Cochrane 'living systematic reviews', which will summarise evidence on the clinical accuracy of different tests and diagnostic features, grouped according to present research questions and settings, in the diagnosis of SARS‐CoV‐2 infection and COVID‐19 disease. Summary estimates of accuracy from these reviews will help inform diagnostic, screening, isolation, and patient management decisions.\nNew tests are being developed and evidence is emerging at an unprecedented rate during the COVID‐19 pandemic. We will aim to update these reviews as often as is feasible to ensure that they provide the most up‐to‐date evidence about test accuracy.\nThese reviews are being produced rapidly to assist in providing a central resource of evidence to assist in the COVID‐19 pandemic, summarising available evidence on the accuracy of the tests and presenting characteristics.\n\nObjectives\nTo 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 disease or COVID‐19 pneumonia.\n\nSecondary objectives\nWhere data are available, we will investigate diagnostic accuracy (either by stratified analysis or meta‐regression) according to:\ndays since symptom onset, population (children; older adults), reference standard, study design, setting, severity of COVID‐19 pneumonia (severe COVID‐19 pneumonia/ARDS requiring intensive care support).\n\nMethods\n\nCriteria for considering studies for this review\n\nTypes of studies\nWe kept the eligibility criteria purposely broad to include all patient groups and all variations of a test at this initial stage of reviewing the evidence (that is, if the patient population was unclear, we included the study).\nWe included studies of all designs that produce estimates of test accuracy or provide data from which estimates can be computed. We included both single‐gate (studies that recruit from a patient pathway before disease status has been ascertained) and multi‐gate (where people with and without the target condition are recruited separately) designs. This means that we included studies that were cross‐sectional or diagnostic case‐control type studies.\nWhen interpreting the results, we made sure that the limitations of different study designs were carefully considered, using quality assessment and analysis.\n\nParticipants\nStudies recruiting people presenting to primary care or outpatient hospital settings with suspicion of COVID‐19 disease were eligible.\nFor the initial version of this review, we included studies that recruited symptomatic people either known to have SARS‐CoV‐2 infection or known not to have SARS‐CoV‐2 infection.\nStudies had to have a sample size of a minimum of 10 participants.\n\nIndex tests\nAll signs and symptoms, including:\nsigns such as oxygen saturation, measured by oximetry or blood pressure;\nclassic symptoms, such as fever or cough.\nWe included combinations of signs and symptoms, but not when they were combined with laboratory, imaging, or other types of index tests as these will be covered in the other reviews.\n\nTarget conditions\nTo be eligible studies had to identify at least one of:\nmild or moderate COVID‐19 disease;\nCOVID‐19 pneumonia.\nAsymptomatic infection with SARS‐CoV‐2 infection is out of scope for this review, considering it is by definition not possible to detect this based on signs and symptoms.\n\nReference standards\nWe anticipated that studies would use a range of reference standards. Although RT‐PCR is considered the best available test, due to rapidly evolving knowledge about the target conditions, multiple reference standards on their own as well as in combination have emerged.\nWe expected to encounter cases defined by:\nRT‐PCR alone;\nRT‐PCR, clinical expertise, and imaging (for example, CT thorax);\nrepeated RT‐PCR several days apart or from different samples;\nplaque reduction neutralisation test (PRNT) or enzyme‐linked immunosorbent assay(ELISA) tests;\ninformation available at a subsequent time point;\nWorld Health Organization (WHO) and other case definitions (see Appendix 1).\nThis list is not exhaustive, and we recorded all reference standards encountered. With a group of methodological and clinical experts, we are producing a ranking of reference standards according to their ability to correctly classify participants using a consensus process. We will use the ranking for informing the assessment of methodological quality in the next update of this review.\n\nSearch methods for identification of studies\nThe final search date for this version of the review is 27 April 2020.\n\nElectronic searches\nWe conducted a single literature search to cover our suite of Cochrane COVID‐19 diagnostic test accuracy (DTA) reviews (Deeks 2020; McInnes 2020).\nWe conducted electronic searches using two primary sources. Both of these searches aimed to identify all published articles and preprints related to COVID‐19, and were not restricted to those evaluating biomarkers or tests. Thus, there are no test terms, diagnosis terms, or methodological terms in the searches. Searches were limited to 2019 and 2020, and for this version of the review have been conducted to 27 April 2020.\n\nCochrane COVID‐19 Study Register searches\nWe used the Cochrane COVID‐19 Study Register (covid-19.cochrane.org/), for searches conducted to 28 March 2020. At that time, the register was populated by searches of PubMed, as well as trials registers at ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP).\nSearch strategies were designed for maximum sensitivity, to retrieve all human studies on COVID‐19 and with no language limits. See Appendix 2.\n\nCOVID‐19 Living Evidence Database from the University of Bern\nFrom 28 March 2020, we used the COVID‐19 Living Evidence database from the Institute of Social and Preventive Medicine (ISPM) at the University of Bern (www.ispm.unibe.ch), as the primary source of records for the Cochrane COVID‐19 DTA reviews. This search includes PubMed, Embase, and preprints indexed in bioRxiv and medRxiv databases. The strategies as described on the ISPM website are described here (ispmbern.github.io/covid-19/). See Appendix 3.\nThe decision to focus primarily on the 'Bern' feed was due to the exceptionally large numbers of COVID‐19 studies available only as preprints. The Cochrane COVID‐19 Study Register has undergone a number of iterations since the end of March 2020 and we anticipate moving back to the Cochrane COVID‐19 Study Register as the primary source of records for subsequent review updates.\n\nSearching other resources\nWe obtained Embase records through Martha Knuth for the Centers for Disease Control and Prevention (CDC), Stephen B Thacker CDC Library, COVID‐19 Research Articles Downloadable Database and de‐duplicated them against the Cochrane COVID‐19 Study Register up to 1 April 2020. See Appendix 4.\nWe also checked our search results against two additional repositories of COVID‐19 publications including:\nthe Evidence for Policy and Practice Information and Co‐ordinating Centre (EPPI‐Centre) 'COVID‐19: Living map of the evidence' (eppi.ioe.ac.uk/COVID19_MAP/covid_map_v4.html);\nthe Norwegian Institute of Public Health 'NIPH systematic and living map on COVID‐19 evidence' (www.nornesk.no/forskningskart/NIPH_diagnosisMap.html)\nBoth of these repositories allow their contents to be filtered according to studies potentially relating to diagnosis, and both have agreed to provide us with updates of new diagnosis studies added. For this iteration of the review, we examined all diagnosis studies from both sources up to 16 April 2020.\nWe did not apply any language restrictions.\n\nData collection and analysis\n\nSelection of studies\nPairs of review authors independently screened studies. We resolved disagreements by discussion with a third, experienced review author for initial title and abstract screening, and through discussion between three review authors for eligibility assessments.\n\nData extraction and management\nPairs of review authors independently performed data extraction. We resolved disagreements by discussion between three review authors.\nWe intended to contact study authors where we needed to clarify details or obtain missing information.\n\nAssessment of methodological quality\nPairs of review authors independently assessed risk of bias and applicability concerns using the QUADAS‐2 (Quality Assessment tool for Diagnostic Accuracy Studies) checklist, which was common to the suite of reviews but tailored to each particular review (Whiting 2011; Table 2). For this review, we excluded the questions on the nature of the samples as these were not relevant, and we added a question on who assessed the signs. We resolved disagreements by discussion between three review authors.\n1 QUADAS‐2 checklist\nIndex test(s) Signs and symptoms\nPatients (setting, intended use of index test, presentation, prior testing) Primary care, hospital outpatient settings including emergency departmentsInpatients presenting with suspected COVID‐19No prior testingSigns and symptoms often used for triage or referral\nReference standard and target condition The focus will be on the diagnosis of COVID‐19 disease and COVID‐19 pneumonia. For this review, the focus will not be on prognosis.\nParticipant selection\nWas a consecutive or random sample of patients enrolled? This will be similar for all index tests, target conditions, and populations.YES: if a study explicitly stated that all participants within a certain time frame were included; that this was done consecutively; or that a random selection was done.NO: if it was clear that a different selection procedure was employed; for example, selection based on clinician's preference, or based on institutions.UNCLEAR: if the selection procedure was not clear or not reported.\nWas a case‐control design avoided? This will be similar for all index tests, target conditions, and populations.YES: if a study explicitly stated that all participants came from the same group of (suspected) patients.NO: if it was clear that a different selection procedure was employed for the participants depending on their COVID‐19 (pneumonia) status or SARS‐CoV‐2 infection status.UNCLEAR: if the selection procedure was not clear or not reported.\nDid the study avoid inappropriate exclusions? Studies may have excluded participants, or selected participants in such a way that they avoided including those who were difficult to diagnose or likely to be borderline. Although the inclusion and exclusion criteria will be different for the different index tests, inappropriate exclusions and inclusions will be similar for all index tests: for example, only elderly patients excluded, or children (as sampling may be more difficult). This needs to be addressed on a case‐by‐case basis.YES: if a high proportion of eligible patients was included without clear selection.NO: if a high proportion of eligible patients was excluded without providing a reason; if, in a retrospective study, participants without index test or reference standard results were excluded; if exclusion was based on severity assessment post‐factum or comorbidities (cardiovascular disease, diabetes, immunosuppression).UNCLEAR: if the exclusion criteria were not reported.\nDid the study avoid inappropriate inclusions? YES: if samples included were likely to be representative of the spectrum of disease.NO: if the study oversampled patients with particular characteristics likely to affect estimates of accuracy.UNCLEAR: if the exclusion criteria were not reported.\nCould the selection of patients have introduced bias? HIGH: if one or more signalling questions were answered with NO, as any deviation from the selection process may lead to bias.LOW: if all signalling questions were answered with YES.UNCLEAR: all other instances.\nIs there concern that the included patients do not match the review question? HIGH: if accuracy of signs and symptoms were assessed in a case‐control design, or in an already highly selected group of participants, or the study was able to only estimate sensitivity or specificity.LOW: any situation where signs and symptoms were the first assessment/test to be done on the included participants.UNCLEAR: if a description about the participants was lacking.\nIndex tests\nWere the index test results interpreted without knowledge of the results of the reference standard? This will be similar for all index tests, target conditions, and populations.YES: if blinding was explicitly stated or index test was recorded before the results from the reference standard were available.NO: if it was explicitly stated that the index test results were interpreted with knowledge of the results of the reference standard.UNCLEAR: if blinding was unclearly reported.\nIf a threshold was used, was it prespecified? This will be similar for all index tests, target conditions, and populations.YES: if the test was dichotomous by nature, or if the threshold was stated in the methods section, or if authors stated that the threshold as recommended by the manufacturer was used.NO: if a receiver operating characteristic curve was drawn or multiple threshold reported in the results section; and the final result was based on one of these thresholds; if fever was not defined beforehand.UNCLEAR: if threshold selection was not clearly reported.\nCould the conduct or interpretation of the index test have introduced bias? HIGH: if one or more signalling questions were answered with NO, as even in a laboratory situation knowledge of the reference standard may lead to bias.LOW: if all signalling questions were answered with YES.UNCLEAR: all other instances.\nIs there concern that the index test, its conduct, or interpretation differ from the review question? This will probably be answered 'LOW' in all cases except when assessments were made in a different setting, or using personnel not available in practice.\nReference standard\nIs the reference standard likely to correctly classify the target condition? We will define acceptable reference standards using a consensus process once the list of reference standards that have been used has been obtained from the eligible studies.For severe pneumonia, we will consider how well processes adhered to the WHO case definition in Appendix 1.\nWere the reference standard results interpreted without knowledge of the results of the index test? YES: if it was explicitly stated that the reference standard results were interpreted without knowledge of the results of the index test, or if the result of the index test was obtained after the reference standard.NO: if it was explicitly stated that the reference standard results were interpreted with knowledge of the results of the index test or if the index test was used to make the final diagnosis.UNCLEAR: if blinding was unclearly reported.\nDid the definition of the reference standard incorporate results from the index test(s)? YES: if results from the index test were a component of the reference standard definition.NO: if the reference standard did not incorporate the index standard test.UNCLEAR: if it was unclear whether the results of the index test formed part of the reference standard.\nCould the conduct or interpretation of the reference standard have introduced bias? HIGH: if one or more signalling questions were answered with NO.LOW: if all signalling questions were answered with YES.UNCLEAR: all other instances.\nIs there concern that the target condition as defined by the reference standard does not match the review question? HIGH: if the target condition was COVID‐19 pneumonia, but only RT‐PCR was used; if alternative diagnosis was highly likely and not excluded (will happen in paediatric cases, where exclusion of other respiratory pathogens is also necessary); if tests used to follow up viral load in known test‐positives.LOW: if above situations were not present.UNCLEAR: if intention for testing was not reported in the study.\nFlow and timing\nWas there an appropriate interval between index test(s) and reference standard? YES: this will be similar for all index tests, populations for the current infection target conditions: as the situation of a patient, including clinical presentation and disease progress, evolves rapidly and new/ongoing exposure can result in case status change, an appropriate time interval will be within 24 hours.NO: if there was more than 24 hours between the index test and the reference standard or if participants were otherwise reported to be assessed with the index versus reference standard test at moments of different severity.UNCLEAR: if the time interval was not reported.\nDid all patients receive a reference standard? YES: if all participants received a reference standard (clearly no partial verification).NO: if only (part of) the index test‐positives or index test‐negatives received the complete reference standard.UNCLEAR: if it was not reported.\nDid all patients receive the same reference standard? YES: if all participants received the same reference standard (clearly no differential verification).NO: if (part of) the index test‐positives or index test‐negatives received a different reference standard.UNCLEAR: if it was not reported.\nWere all patients included in the analysis? YES: if all included participants were included in the analyses.NO: if after the inclusion/exclusion process, participants were removed from the analyses for different reasons: no reference standard done, no index test done, intermediate results of both index test or reference standard, indeterminate results of both index test or reference standard, samples unusable.UNCLEAR: if this was not clear from the reported numbers.\nCould the patient flow have introduced bias? HIGH: if one or more signalling questions were answered with NO.LOW: if all signalling questions were answered with YES.UNCLEAR: all other instances.\nICU: intensive care unit; RT‐PCR: reverse transcription polymerase chain reaction; SARS‐CoV‐2: severe acute respiratory syndrome coronavirus 2; WHO: World Health Organization\n\nStatistical analysis and data synthesis\nWe present results of estimated sensitivity and specificity using paired forest plots and summarised in tables as appropriate.\nWe present the results without meta‐analysis, due to the small numbers of studies currently available, considerable heterogeneity across studies and the high risk of bias that we identified, as we felt doing so would otherwise produce a seemingly more accurate estimate than the underlying evidence is able to provide at this moment in time.\nWe present results of estimated sensitivity and specificity using paired forest plots in Review Manager 2014, and dumbbell plots to display the change in disease probability after a positive or negative result.\nWe disaggregated data by study design and organised by target condition, reporting results from cross‐sectional studies separately from studies that used a diagnostic case‐control or other design that we assessed as prone to high risk of bias.\nWhen pooling does become possible in a future update of this review, we will estimate mean sensitivity and specificity using hierarchical models where tests either report binary results or at commonly reported thresholds. Where data are sparse, we will use methods described by Takwoingi 2017 for obtaining estimates from simplified models. We anticipate that over time sufficient data will accumulate to provide clear estimates of test accuracy for some tests. We will undertake meta‐analysis in STATA version 16.0 (STATA), or SAS (SAS 2015), as detailed in the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy (Chapter 10; Macaskill 2013).\n\nInvestigations of heterogeneity\nWe have listed sources of heterogeneity that we investigated if adequate data were available in the Secondary objectives. In this version of the review, we used stratification to investigate heterogeneity as we considered it was inappropriate to combine studies. In future updates, if meta‐analysis becomes possible, we will investigate heterogeneity through meta‐regression.\nWe will stratify by reference standard and study design. In this version of the review we have stratified by study design only, as stratification by reference standard was not yet possible.\n\nSensitivity analyses\nWe aimed to undertake sensitivity analyses considering the impact of:\nunpublished studies;\nstudies with inadequate reference standards.\nHowever, neither were possible in this version of the review.\n\nAssessment of reporting bias\nWe aimed to publish lists of studies that we know exist but for which we have not managed to locate reports, and request information to include in updates of these reviews. However, at the time of writing this version of the review, we are unaware of unpublished studies.\n\nSummary of findings\nWe have listed our key findings in a 'Summary of findings' table to determine the strength of evidence for each test and findings, and to highlight important gaps in the evidence.\n\nUpdating\nWe will undertake the searches of published literature and preprints bi‐weekly, and, dependent on the number of new and important studies found, we will consider updating each review with each search if resources allow.\n\nResults\n\nResults of the search\nThe search yielded 10,965 records after removing duplicates. The first selection resulted in 658 records that were potentially eligible for this review on signs and symptoms. After screening on title and abstract, we excluded 457 records, leaving 201 to be assessed on full text. Of these, we included 16 studies in this review. The reasons for excluding 185 records are listed in the PRISMA flow chart (see Figure 1; Moher 2009).\n1 Flow diagram Two studies reported on the same cases while using a different control group (Chen X 2020; Yang 2020d). Chen X 2020 used a concurrent control group of pneumonia cases negative for SARS‐CoV‐2 on PCR testing but Yang 2020d used a historic control group of influenza pneumonia patients. For this reason we only included the Chen X 2020 results in the analyses.\nOne study reported a study that included a derivation and validation part for the development of a prediction rule (Song 2020b). The two parts are identical in set‐up and only differ in respect to the time of data collection, that is, the derivation part recruited participants up to 5 February 2020 and the validation part recruited participants from 6 February 2020 onwards. As a result, we consider this to be one study and have entered all data on signs and symptoms as such.\nFour studies were conducted in the USA, all other studies were from China. A summary of the main study characteristics can be found in Table 3.\n2 Summary of study characteristics\nStudy ID Target condition Sample size Prevalence Setting Population Design Reference standard\nAi 2020a COVID‐19 pneumonia 53 38% Hospital inpatientsa Patients hospitalised with pneumonia diagnosed by imaging Cross‐sectional PCR on nasopharyngeal swabs\nChen X 2020 COVID‐19 pneumonia 136 Not applicable Hospital inpatientsa Patients admitted with pneumonia Cases selected cross‐sectionally in 5 hospitals, non‐cases from 1 hospital only PCR, samples not specified\nCheng 2020a COVID‐19 pneumonia 33 33% Hospital outpatients Patients presenting to a fever observation department with pneumonia Cross‐sectional PCR on throat swabs\nFeng 2020a COVID‐19 pneumonia 132 5% Emergency department Patients presenting to fever clinic of emergency department Cross‐sectional PCR on throat swabs\nLiang 2020 COVID‐19 pneumonia 88 24% Hospital outpatients Patients with pneumonia and presenting to fever clinic Cross‐sectional PCR, sample not specified; conducted after panel discussion\nNobel 2020 COVID‐19 disease 516 Not applicable Hospital outpatients Patients who underwent SARS‐CoV‐2 testing with intent to hospitalise or in essential personnel Case‐control PCR on nasopharyngeal swabs\nPeng 2020a COVID‐19 disease 86 13% Hospital outpatients Patients clinically suspected and referred for testing Cross‐sectional PCR on nasopharyngeal swabs\nRentsch 2020 COVID‐19 disease 3789 15% Unclear Patients tested for SARS‐CoV‐2 in the Veterans Affairs Cohort born between 1945 and 1965 Cross‐sectional PCR on nasopharyngeal swabs\nSong 2020b COVID‐19 disease 399 7% Hospital outpatients Patients tested for SARS‐CoV‐2 Cross‐sectional PCR on sputum samples\nSun 2020a COVID‐19 disease 788 7% Hospital outpatients Patients presenting to testing centre, either self‐referred, referred from primary care or at‐risk cases identified by national contact tracing Cross‐sectional PCR on sputum, endotracheal aspirate, nasopharyngeal swabs or throat swabs\nTolia 2020 COVID‐19 disease 283 10% Emergency department Patients presenting with symptoms, travel history, risk factors or healthcare workers Cross‐sectional PCR on nasopharyngeal swabs\nWee 2020 COVID‐19 disease 870 18% Emergency department Patients presenting with respiratory symptoms or travel history Cross‐sectional PCR on oropharyngeal swabs\nYan 2020a COVID‐19 disease 262 23% Hospital outpatient Patients presenting hospital for SARS‐CoV‐2 testing, not otherwise specified Internet survey after presentation PCR, samples not specified\nYang 2020d COVID‐19 pneumonia 121 Not applicable Hospital inpatientsa Patient with pneumonia from SARS‐CoV‐2 and patients with pneumonia from influenza in 2015‐2019 Case‐control PCR, samples not specified\nZhao 2020a COVID‐19 pneumonia 34 Not applicable Hospital inpatientsa Patients with pneumonia and admitted to hospital Case‐control PCR on throat or sputum swabs\nZhu 2020b COVID‐19 disease 116 28% Emergency department Patients suspected of SARS‐CoV‐2 and presenting to the emergency department Cross‐sectional PCR, samples not specified\nPCR: polymerase chain reaction; SARS‐CoV‐2: severe acute respiratory syndrome coronavirus 2\na'Hospital inpatients' refers to studies that recruited patients admitted to hospital with COVID‐19 disease and in whom the signs and symptoms were assessed on admission.\n\nMethodological quality of included studies\nThe results of the quality assessment are summarised in Figure 2 and Figure 3. We rated participant selection as introducing high risk of bias in seven studies. In five studies this was because a CT scan or other imaging was used to diagnose patients with pneumonia prior to inclusion in the study, leading to a highly selected patient population (Ai 2020a; Chen X 2020; Cheng 2020a; Liang 2020; Yang 2020d); RT‐PCR results were subsequently used to distinguish between COVID‐19 pneumonia and pneumonia from other causes. For all studies, testing was highly dependent on the local case definition and testing criteria that were in effect at the time of the study, meaning all patients that were included in studies had already gone through a referral/selection filter, which was not always described. The most extreme example of this is the study by Liang 2020, in which patients with radiological evidence of pneumonia and a clinical presentation compatible with COVID‐19 were only tested for SARS‐CoV‐2 after a panel discussion.\n2 Risk of bias and applicability concerns graph: review authors' judgements about each domain presented as percentages across included studies\n3 Risk of bias and applicability concerns summary: review authors' judgements about each domain for each included study Of the 16 studies included in this first version of the review, five studies did not use a cross‐sectional design. Three studies were diagnostic case‐control studies (Nobel 2020; Yang 2020d; Zhao 2020a), one study selected cases cross‐sectionally in five hospitals but only selected cases in one hospital (Chen X 2020), and one study emailed patients who had undergone testing for SARS‐CoV‐2 about olfactory symptoms prior to the SARS‐CoV‐2 test, with a response rate of 58% in SARS‐CoV‐2 positive cases and 15% in negative cases (Yan 2020a).\nWe rated all studies except two as carrying a high risk of bias for the index tests because there was little to no detail on how, by whom, and when the signs and symptoms were measured. In addition, there is considerable uncertainty around the reference standard, with some studies providing little detail on the RT‐PCR tests that they used or lack of clarity on blinding.\nParticipant flow was unclear in four studies (Yan 2020a; Yang 2020d; Zhao 2020a; Zhu 2020b), either because the timing of recording signs and symptoms and conduct of the reference standard was unclear, or because some tests received a second or third reference standard at unclear time points during hospital admission.\nWe rated applicability for participant selection as high risk when there was a risk of selection bias or studies did not describe selection. As for the applicability of the index tests and reference standard, we always scored this as low risk except for Chen X 2020, because blinding of the index tests was unclear, and Yang 2020d, because blinding and sample of the reference standard were unclear.\n\nFindings\nThe main characteristics of all included studies are listed in Table 3. There were four studies in hospital inpatients (Ai 2020a; Chen X 2020; Yang 2020d; Zhao 2020a), seven studies in hospital outpatients (Cheng 2020a; Liang 2020; Nobel 2020; Peng 2020a; Song 2020b; Sun 2020a; Yan 2020a), and four studies in emergency departments (Feng 2020a; Tolia 2020; Wee 2020; Zhu 2020b). The setting was not specified in one study (Rentsch 2020); in the 'Summary of findings' table, we classified this study setting as being hospital outpatient under the assumption that at that time in the pandemic (February 2020 to March 2020) tests were not commonly available outside hospital clinics. There were no studies conducted in community primary care services.\nSeven studies assessed the accuracy of signs and symptoms for the diagnosis of COVID‐19 pneumonia (Ai 2020a; Chen X 2020; Cheng 2020a; Feng 2020a; Liang 2020; Yang 2020d; Zhao 2020a); the remaining studies had COVID‐19 disease as the target condition, with no further description of the severity, meaning some patients could have suffered from mild or moderate COVID‐19 disease and others from COVID‐19 pneumonia. The distinction between these two target conditions was not always very clear, and a degree of overlap is to be assumed. All studies used RT‐PCR testing as the reference standard, with some variation in the samples that were used.\nIn all, 7706 patients were included, the median number of participants was 134. Prevalence of infection varied from 5% to 38% with a median of 17%. There were no studies in children or elderly populations, except for Rentsch 2020, which included a cohort of a median age of 65.7 years old from the Veterans Affairs Healthcare System database.\nWe found data on 27 signs and symptoms, which fall into four different categories: systemic, respiratory, gastrointestinal and cardiovascular signs and symptoms. There were no analyses for combinations of tests, only for individual signs and symptoms. The results are summarised in Table 3. Results for the cross‐sectional studies are presented in forest plots (Figure 4; Figure 5; Figure 6; Figure 7), and are plotted in ROC (receiver operating characteristic) space (Figure 8; Figure 9; Figure 10; Figure 11), results for the other studies are only listed in forest plots (Figure 12; Figure 13; Figure 14; Figure 15).\n4 Forest plot of respiratory signs and symptoms (cross‐sectional studies)\n5 Forest plot of systemic signs and symptoms (cross‐sectional studies)\n6 Forest plot of gastrointestinal signs and symptoms (cross‐sectional studies)\n7 Forest plot of cardiovascular signs and symptoms (cross‐sectional studies)\n8 Summary ROC plot of respiratory signs and symptoms (cross‐sectional studies)\n9 Summary ROC plot of systemic signs and symptoms (cross‐sectional studies)\n10 Summary ROC Plot of gastrointestinal signs and symptoms (cross‐sectional studies)\n11 Summary ROC plot of cardiovascular signs and symptoms (cross‐sectional studies)\n12 Forest plot of tests: 27 cough (non‐cross‐sectional study), 28 sore throat (non‐cross‐sectional study), 29 rhinorrhoea (non‐cross‐sectional study), 30 nasal obstruction (non‐cross‐sectional study), 34 dyspnoea (non‐cross‐sectional study), 31 loss of sense of smell (non‐cross‐sectional study), 32 loss of taste (non‐cross‐sectional study), 33 positive auscultation findings (non‐cross‐sectional study)\n13 Forest plot of tests: 37 fatigue (non‐cross‐sectional study), 36 fever (non‐cross‐sectional study), 39 headache (non‐cross‐sectional study), 38 myalgia or arthralgia (non‐cross‐sectional study)\n14 Forest plot of tests: 40 diarrhoea (non‐cross‐sectional study), 41 nausea/vomiting (non‐cross‐sectional study), 42 gastrointestinal symptoms, not specified (non‐cross‐sectional study)\n15 Forest plot of 35 chest tightness (non‐cross‐sectional study) Overall, diagnostic accuracy of individual signs and symptoms is low, especially sensitivity. In addition, results were highly variable across studies, making it difficult to draw firm conclusions.\nSigns and symptoms for which sensitivity was reported above 50% in at least one cross‐sectional study are the following.\nCough: sensitivity between 43% and 71%, specificity between 14% and 54%\nSore throat: sensitivity between 5% and 71%, specificity between 55% and 80%\nFever: sensitivity between 7% and 91%, specificity between 16% and 94%\nMyalgia or arthralgia: sensitivity between 19% and 86%, specificity between 45% and 91%\nFatigue: sensitivity between 10% and 57%, specificity between 60% and 94%\nHeadache: sensitivity between 3% and 71%, specificity between 78% and 98%\nFor fever, six of nine studies report a sensitivity of at least 80%, which is unsurprising considering fever was a key feature of COVID‐19 that was used in selecting patients for further testing. As a result, most participants in these studies would have fever, both cases and non‐cases. The same applies to cough, which was also listed as one of the main criteria for SARS‐CoV‐2 testing and may have contributed to inflated sensitivity estimates.\nSpecificity of at least 90% was achieved for 19 signs and symptoms. In only four signs and symptoms did this go along with sensitivity of at least 50% which would correspond to a positive likelihood ratio of at least 5, a commonly used arbitrary definition of a red flag. Using this definition, fever, myalgia or arthralgia, fatigue, or headache are to be considered red flags.\nStrikingly, most of the respiratory symptoms such as cough, sore throat and sputum production are below the diagonal in ROC space (Figure 8). The diagonal line in ROC space is where sensitivity equals 1‐specificity, meaning a test that is on the diagonal line has a positive likelihood ratio of 1 and is therefore not diagnostic because disease probability is left unchanged after conducting the test. Tests that lie below the diagonal line have a positive likelihood ratio that is smaller than 1, meaning the probability of COVID‐19 disease decreases when this test is positive. For example, in Sun 2020a, pretest probability of COVID‐19 is 6.9%; probability decreases to 6.4% when the patient has a cough and increases to 8.0% when the patient does not have a cough. We hypothesise on the reason for this counterintuitive finding in the discussion section. In contrast to respiratory features, systemic features are mostly above the diagonal line (Figure 9), suggesting that they do increase the probability of COVID‐19 when present. Gastrointestinal symptoms and cardiovascular features are clustered in the bottom left corner or on the diagonal line suggesting that they have very little diagnostic value (Figure 10; Figure 11).\nTo further illustrate the systemic features' ability to either rule in or rule out COVID‐19 disease or COVID‐19 pneumonia, we constructed dumbbell plots showing pre‐ and post‐test probabilities for each feature in each study (Figure 16). For each test, we have plotted the pre‐test probability, which is the prevalence of COVID‐19 disease (blue dot). Probability then changes depending on a positive test result (red dot marked +) or a negative test result (green dot marked ‐). The plot shows that fever, for example, increases the probability of COVID‐19 in two studies (Ai 2020a; Rentsch 2020), makes little to no difference in five studies (Feng 2020; Liang 2020; Peng 2020; Song 2020; Zhu 2020), and decreases the probability of COVID‐19 in two studies (Cheng 2020a; Tolia 2020).\n16 Dumbbell plot: this plot shows how disease probability changes after a positive test result (red dot with plus sign) or after a negative test (green dot with minus sign). Pre‐test probability or prevalence is the blue dot\n\nDiscussion\n\nSummary of main results\nIndividual signs and symptoms appear to have very poor diagnostic properties for COVID‐19, although this has to be interpreted in the presence of a limited number of studies, heterogeneity between the studies precluding any firm conclusions and in a context of selection bias. Most features had very low sensitivity, while specificity was moderate to high.\nWe have identified four possible red flags, that is, symptoms that increased the probability of COVID‐19 when present because of a positive likelihood ratio of at least 5 in at least one study: fever, myalgia or arthralgia, fatigue, and headache. When we apply the results of sensitivity and specificity of these systemic features to disease probabilities, we assess their value to rule in and rule out disease as shown in the dumbbell plots (Figure 16). These clearly show the limited effect on disease probability from these signs and symptoms. Importantly, we did not find any studies investigating the diagnostic accuracy of combinations of signs and symptoms. There were also no studies from community primary care settings.\nSome of our findings are counterintuitive, for example that the majority of the studies that investigated cough found that cough decreases the probability of COVID‐19 despite the fact that it is part of the case definition of COVID‐19 in most countries. This is also the case for fever in two studies and myalgia in one study ‐ even though these features were also red flags in at least one other study. We believe this may be caused by selection bias. Selection bias is present when selective and non‐random inclusion and exclusion of participants apply and the resulting association between exposure and outcome (here the accuracy of the test) differs in the selected study population compared to the eligible study population, and it has been shown that this may decrease estimates of diagnostic accuracy (Rutjes 2006). For the diagnosis of COVID‐19, rapidly and constantly changing, and widely variable test criteria have influenced who was referred for testing and who was not. Inclusion in the study of only a selective fraction of eligible patients can give a biased estimate of the real accuracy of the index test when measured against the reference standard and real disease status. Griffith 2020 reported on the problematic presence of collider stratification bias in the published studies on COVID‐19. Appropriate sampling strategies need to be applied to avoid conclusions of spurious relationships, more specifically in our case, the biased accuracy estimates of signs and symptoms for the diagnosis of COVID‐19 disease. Selection of patients based on the presence of specific pre‐set symptoms, such as fever and cough, lead to biased associations between these symptoms and disease, and sensitivity and specificity estimates that differ from their true values. The example of collider bias for cough is illustrated in Figure 17. Grouping studies by diagnostic criteria for selection might clarify this issue, but studies do not clearly describe them, with study authors referring to the guidelines in general that were applicable at the time.\n17 Directed acyclic graph on cough Another form of selection bias is spectrum bias, where the patients included in the studies do not reflect the patient spectrum to which the index test will be applied. The inclusion of hospitalised patients can lead to such a bias, when in these patients both the distribution of signs and symptoms differ and assessment with the reference standard is differential. In addition, the distribution and severity of alternative diagnoses may be different in hospitalised populations than in patients presenting to ambulatory care settings.\n\nStrengths and weaknesses of the review\nStrengths of our review are the systematic and broad search performed to include all possible studies, including those prior to peer‐review, to gather the largest number of studies available at this point. Exclusion of cases‐only studies, the largest number of the published cohorts of patients with COVID‐19, limits the available data but also improves the quality of the evidence and the possibility to present both sensitivity and specificity (cases only cannot provide both accuracy measures). Because this is a living systematic review, future updates may offer the possibility to do a meta‐analysis, which was not possible at this stage. In addition, further insights into this novel disease may lead to new evidence on signs and symptoms that are more diagnostic, which we will incorporate in future updates.\nThe lack of data on combinations of signs and symptoms is an important evidence gap. Consequently, there is no evidence on syndromic presentation and the value of composite signs and symptoms on the diagnostic accuracy measures. In addition, subgroup analyses by the pre‐defined variables were not feasible due to lack of reporting.\nWe need to assess multiple variables for their possible confounding effect on the summary estimates. Possible confounders include the presence of other respiratory pathogens (seasonality), the phase of the epidemic, exposure to high versus low prevalence setting, high or low exposure risk, comorbidity of the participants, or time since infection. Seasonality may influence specificity, because alternative diagnoses such as influenza or other respiratory viruses are more prevalent in winter, leading to more non‐COVID‐19 patients displaying symptoms such as cough or fever, decreasing specificity. In this version of the review, all studies were conducted in Winter or early Spring, suggesting this may still have been at play. However, social distancing policies have shortened this year's influenza season in several countries (www.who.int/influenza/surveillance_monitoring/updates/en/), which may have led to higher specificity for signs and symptoms than what we may expect in the next influenza season. In future updates of the review, we will explore seasonality effects if data allow. As for time since onset, given that the moment of infection is more likely than not an unrecognisable and unmeasurable variable, time since onset of symptoms can be used as a proxy. Reporting of studies, with presentation of the 2x2 table stratified by time since onset of disease, is informative and might have the potential to increase accuracy of the signs and symptoms and their diagnostic differential potential.\n\nApplicability of findings to the review question\nThe high risk of selection bias, with many studies including patients who had already been admitted to hospital or who presented to hospital settings with the intent to hospitalise, leads to findings that are less applicable to people presenting in primary care, who on average experience a shorter illness duration, less severe symptoms and have a lower probability of the target condition.\nOur search did not find any articles providing data on children. Children have been underrepresented in the studies on diagnosing SARS‐CoV‐2 infection. Their absence seems related to the general mild presentation of the disease in the paediatric population, and the even more frequent asymptomatic course of COVID‐19 in children. The full scope of disease presentation in children is therefore not known. It is important to identify signs and symptoms that can be used to clinically assess children with suspected COVID‐19, especially because aspecific presentations and fever without a source are already common in this age group, and acute infection in children is a common cause for families to self‐isolate or get tested. Misclassification of children, where children will be asked to remain in quarantine when they present with predefined, but not yet evidence‐based symptoms needs to be avoided to decrease the possible damage done to children's health and education. Having separate data for neonates, young infants, toddlers, school‐aged children and adolescents is therefore of value.\nAnother important patient group is older adults. They are most at risk of an adverse outcome of SARS‐CoV‐2 infection, including an increased risk of requiring intensive care support and and increased risk of mortality. In this version of the review, only one study focused on adults aged 55 to 75 years. All other studies included adults of all ages and did not present results separately for older age groups. The lack of a solid evidence base for the diagnosis of COVID‐19 in older adults adds to the difficulty in diagnosing serious infections in this age group, as other serious infections such as bacterial pneumonia or urinary sepsis also tend to lead to aspecific presentations.\nThe association of a single sign or symptom with COVID‐19 is highly uncertain, and we do not have data on combinations of signs and symptoms. Additionally, potentially more diagnostic symptoms such as loss of sense of smell have not yet been studied widely and remain to be assessed in well designed studies. Moreover, the nature of the signs and symptoms that are used to guide self‐isolation decisions are such that people may end up being quarantined on a regular basis, leading to missed days at school or work, isolation and anxiety.\nIn future updates of this review, we intend to organise findings by age group, settings (in particular primary care settings versus hospital settings), and target condition, when evidence allows.\n\nAuthors' conclusions\nImplications for practice\n\nThe results were highly variable across studies, making it difficult to draw firm conclusions. Selection bias further hinders interpretability. Until results of further studies become available, broad investigation of patients with suspected SARS‐Cov‐2 infection remains necessary. Neither absence nor presence of the individual signs and symptoms included in this review are accurate enough to rule in or rule out disease.\nImplications for research\n\nOur review reflects the need for improved study methodology in COVID‐19 diagnostic accuracy research: appropriate patient sampling strategies; prospective one‐gate design; and investigating the presence or absence of clinical signs and symptoms in all suspected patients. In addition, we urgently need studies in community primary care settings, and studies investigating combinations of signs and symptoms. Evidence on signs and symptoms that are used for testing or referral decisions, such as loss of sense of smell, heart rate, breathing rate and oxygen saturation, should be included in future studies using clearly stated definitions and cut‐offs. In order to inform self‐isolation policies, studies in community settings, where prevalence is lower than in the included studies, will be needed to better determine the balance of risks arising from false positives and false negatives.\nWe also need improved reporting with studies clearly describing how they assessed signs and symptoms, when and by whom, and providing clearer definitions of what constitutes an abnormal sign or symptom. Studies also need to report reference standards more clearly.\nIn addition, more data on specific patient groups with comorbidities at higher risk of complications or severe disease are needed, especially older adults, as missing COVID‐19 disease may have more serious consequences in these patients. We also need to have more studies in children.\nWe would like to recommend authors to adhere to the STARD guidelines when reporting new studies on this topic (Bossuyt 2015).\n\nWhat's new\nDate Event Description\n7 July 2020 Amended Resolution of two figures improved\n\nHistory\nReview first published: Issue 7, 2020\n\nAcknowledgements\nMembers of the Cochrane COVID‐19 Diagnostic Test Accuracy Review Group include:\nthe project team (Deeks JJ, Dinnes J, Takwoingi Y, Davenport C, Leeflang MMG, Spijker R, Hooft L, Van den Bruel A, McInnes MDF, Emperador D, Dittrich S);\nthe systematic review teams for each review:\nMolecular, antigen, and antibody tests (Adriano A, Beese S, Dretzke J, Ferrante di Ruffano L, Harris I, Price M, Taylor‐Phillips S)\nSigns and symptoms (Stuyf T, Domen J, Horn S)\nRoutine laboratory markers (Yang B, Langendam M, Ochodo E, Guleid F, Holtman G, Verbakel J, Wang J, Stegeman I)\nImaging tests (Salameh JP, McGrath TA, van der Pol CB, Frank RA, Prager R, Hare SS, Dennie C, Jenniskens K, Korevaar DA, Cohen JF, van de Wijgert J, Damen JAAG, Wang J)\nthe wider team of systematic reviewers from University of Birmingham, UK who assisted with title and abstract screening across the entire suite of reviews for the diagnosis of COVID‐19 (Agarwal R, Baldwin S, Berhane S, Herd C, Kristunas C, Quinn L, Scholefield B).\nWe thank Dr Jane Cunningham (World Health Organization) for participation in technical discussions and comments on the manuscript.\nWe would like to acknowledge Joanne Merckx for her contribution to the data extraction of nine papers in the initial stages of this review. Due to conflict of interest, a decision was taken to have a systematic reviewer, Nicholas Henschke, independently check all data extracted by her before publication.\nThe editorial process for this review was managed by Cochrane's EMD Editorial Service in collaboration with Cochrane Infectious Diseases. We thank Helen Wakeford, Anne‐Marie Stephani and Deirdre Walshe for their comments and editorial management. We thank Robin Featherstone for comments on the search and Mike Brown and Paul Garner for sign‐off comments. We thank Denise Mitchell for her efforts in copy‐editing this review.\nThank you also to peer referees Trish Greenhalgh, Robert Walton, Chris Cates and Lynda Ware, consumer referee Jenny Negus, and methodological referees Gianni Virgili and Marta Roqué, for their insights.\nThe editorial base of Cochrane Infectious Diseases is funded by UK aid from the UK Government for the benefit of low‐ and middle‐income countries (project number 300342‐104). The views expressed do not necessarily reflect the UK Government’s official policies.\nJonathan Deeks is a UK National Institute for Health Research (NIHR) Senior Investigator Emeritus. Yemisi Takwoingi is supported by a NIHR Postdoctoral Fellowship. Jonathan Deeks, Jacqueline Dinnes, Yemisi Takwoingi, Clare Davenport and Malcolm Price are supported by the NIHR Birmingham Biomedical Research Centre. This paper presents independent research supported by the NIHR Birmingham Biomedical Research Centre at the University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.\n\nAppendices\n\nAppendix 1. World Health Organization case definitions\n\nSevere pneumonia\nAdolescent or adult: fever or suspected respiratory infection, plus one of the following: respiratory rate \u003e 30 breaths/minute; severe respiratory distress; or oxygen saturation (SpO2) ≤ 93% on room air. Child with cough or difficulty in breathing, plus at least one of the following: central cyanosis or SpO2 \u003c 90%; severe respiratory distress (for example, grunting, very severe chest indrawing); signs of pneumonia with a general danger sign: inability to breastfeed or drink, lethargy or unconsciousness, or convulsions.\nOther signs of pneumonia may be present: chest indrawing, fast breathing (in breaths/minute): aged \u003c 2 months: ≥ 60; aged 2 to 11 months: ≥ 50; aged 1 to 5 years: ≥ 40. While the diagnosis is made on clinical grounds; chest imaging may identify or exclude some pulmonary complications.\n\nAcute respiratory distress syndrome (ARDS)\nOnset within one week of a known clinical insult or new or worsening respiratory symptoms.\nChest imaging (that is, X‐ray, computed tomography scan, or lung ultrasound): bilateral opacities, not fully explained by volume overload, lobar or lung collapse, or nodules.\nOrigin of pulmonary infiltrates: respiratory failure not fully explained by cardiac failure or fluid overload. Need objective assessment (for example, echocardiography) to exclude hydrostatic cause of infiltrates/oedema if no risk factor present.\nOxygenation impairment in adults:\nmild acute respiratory distress syndrome (ARDS): 200 mmHg \u003c ratio of arterial oxygen partial pressure/fractional inspired oxygen (PaO2/FiO2) ≤ 300 mmHg (with positive end‐expiratory pressure (PEEP) or continuous positive airway pressure (CPAP) ≥ 5 cmH2O, or non‐ventilated);\nmoderate ARDS: 100 mmHg \u003c PaO2/FiO2 ≤ 200 mmHg (with PEEP ≥ 5 cmH2O, or non‐ventilated);\nsevere ARDS: PaO2/FiO2 ≤ 100 mmHg (with PEEP ≥ 5 cmH2O, or non‐ventilated);\nwhen PaO2 is not available, SpO2/FiO2 ≤ 315 mmHg suggests ARDS (including in non‐ventilated patients).\nOxygenation impairment in children: note OI = Oxygenation Index and OSI = Oxygenation Index using SpO2. Use PaO2‐based metric when available. If PaO2 not available, wean FiO2 to maintain SpO2 ≤ 97% to calculate OSI or SpO2/FiO2 ratio:\nbilevel (non‐invasive ventilation or CPAP) ≥ 5 cmH2O via full‐face mask: PaO2/FiO2 ≤ 300 mmHg or SpO2/FiO2 ≤ 264;\nmild ARDS (invasively ventilated): 4 ≤ OI \u003c 8 or 5 ≤ OSI \u003c 7.5;\nmoderate ARDS (invasively ventilated): 8 ≤ OI \u003c 16 or 7.5 ≤ OSI \u003c 12.3;\nsevere ARDS (invasively ventilated): OI ≥ 16 or OSI ≥ 12.3.\n\nAppendix 2. Cochrane COVID‐19 Study Register searches\nSource Strategy\nClinicalTrials.gov COVID‐19a\nWHO ICTRP Health topic: 2019‐nCov / COVID‐19\nPubMed ((\"2019 nCoV\"[tiab] OR 2019nCoV[tiab] OR \"2019 novel coronavirus\"[tiab] OR \"COVID 19\"[tiab] OR COVID19[tiab] OR \"new coronavirus\"[tiab] OR \"novel coronavirus\"[tiab] OR \"novel corona virus\"[tiab] OR \"SARS CoV‐2\"[tiab] OR (Wuhan[tiab] AND (coronavirus[tiab] OR \"corona virus\"[tiab])) OR \"COVID‐19\"[Supplementary Concept] OR \"severe acute respiratory syndrome coronavirus 2\"[Supplementary Concept]) NOT (\"animals\"[MeSH Terms] NOT \"humans\"[MeSH Terms])) NOT (editorial[pt] OR comment[pt] OR letter[pt] OR newspaper article[pt])\naAutomatic term mapping links results for 2019‐nCoV, 2019 novel coronavirus, SARS‐CoV‐2, severe acute respiratory syndrome coronavirus 2.\n\nAppendix 3. Living search from the University of Bern\nWe took the following information from the university of Bern website (see: ispmbern.github.io/covid-19/living-review/collectingdata.html).\nThe register is updated daily and CSV file downloads are made available.\n\n1 April 2020\nFrom 1 April 2020, we will retriev the curated BioRxiv/MedRxiv dataset (connect.medrxiv.org/relate/content/181).\n\n26 to 31 March 2020\nMEDLINE: (\\\"Wuhan coronavirus\\\" [Supplementary Concept] OR \\\"COVID‐19\\\" OR \\\"2019 ncov\\\"[tiab] OR ((\\\"novel coronavirus\\\"[tiab] OR \\\"new coronavirus\\\"[tiab]) AND (wuhan[tiab] OR 2019[tiab])) OR 2019‐nCoV[All Fields] OR (wuhan[tiab] AND coronavirus[tiab])))))\nEmbase: (nCoV or 2019‐nCoV or ((new or novel or wuhan) adj3 coronavirus) or covid19 or covid‐19 or SARS‐CoV‐2).mp.\nBioRxiv/MedRxiv: ncov or corona or wuhan or COVID or SARS‐CoV‐2\nWith the kind support of the Public Health \u0026 Primary Care Library PHC (www.unibe.ch/university/services/university_library/faculty_libraries/medicine/public_health_amp_primary_care_library_phc/index_eng.html), and following guidance of the Medical Library Association (www.mlanet.org/p/cm/ld/fid=1713).\n\n1 January 2020 to 25 March 2020\nMEDLINE: (\"Wuhan coronavirus\" [Supplementary Concept] OR \"COVID‐19\" OR \"2019 ncov\"[tiab] OR ((\"novel coronavirus\"[tiab] OR \"new coronavirus\"[tiab]) AND (wuhan[tiab] OR 2019[tiab])) OR 2019‐nCoV[All Fields] OR (wuhan[tiab] AND coronavirus[tiab])))))\nEmbase: ncov OR (wuhan AND corona) OR COVID\nBioRxiv/MedRxiv: ncov or corona or wuhan or COVID\n\nAppendix 4. CDC Library, COVID‐19 Research Articles Downloadable Database\nEmbase records from the Stephen B. Thacker CDC Library, COVID‐19 Research Articles Downloadable Database.\nRecords were obtained by the CDC library by searching Embase through Ovid using the following search strategy.\nSource Strategy\nEmbase (coronavir* OR corona virus* OR betacoronavir* OR covid19 OR covid 19 OR nCoV OR novel CoV OR CoV 2 OR CoV2 OR sarscov2 OR 2019nCoV OR wuhan virus*).mp. OR ((wuhan OR hubei OR huanan) AND (severe acute respiratory OR pneumonia*) AND outbreak*).mp. OR Coronavirus infection/ OR coronavirinae/ OR exp betacoronavirus/Limits: 2020‐OR(novel coronavir* OR novel corona virus* OR covid19 OR covid 19 OR nCoV OR novel CoV OR CoV 2 OR CoV2 OR sarscov2 OR 2019nCoV OR wuhan virus*).mp. OR ((wuhan OR hubei OR huanan) AND (severe acute respiratory OR pneumonia*) AND outbreak*).mp. OR ((wuhan OR hubei OR huanan) AND (coronavir* OR betacoronavir*)).mp.Limits: 2019‐\n\nData\nPresented below are all the data for all of the tests entered into the review.\nTests Data tables by test\nTest No. of studies No. of participants\n1 Cough 8 2607\n2 Sputum production 6 2467\n3 Dyspnoea 7 2554\n4 Hypoxia 1 2929\n5 Haemoptysis 1 116\n6 Positive auscultation findings 1 788\n7 Respiratory symptoms (not specified)) 1 788\n8 Sore throat 6 2438\n9 Nasal symptoms 5 2405\n10 Loss of smell (anosmia) or loss of taste (ageusia) 1 870\n11 Fever 9 5484\n12 Low body temperature 1 3384\n13 Shivers 1 132\n14 Chills 2 1443\n15 Myalgia or arthralgia 4 339\n16 Myalgia or fatigue 2 1427\n17 Fatigue 3 273\n18 Headache 5 1700\n19 Nausea/vomiting 3 489\n20 Diarrhoea 6 1733\n21 Abdominal pain 2 185\n22 Gastrointestinal symptoms (not specified) 1 788\n23 Low systolic blood pressure 1 3341\n24 High systolic blood pressure 1 3341\n25 Tachycardia 1 3373\n26 Palpitations 1 132\n27 Cough (non‐cross‐sectional study) 3 432\n28 Sore throat (non‐cross‐sectional study) 3 432\n29 Rhinorrhoea (non‐cross‐sectional study) 1 136\n30 Nasal obstruction (non‐cross‐sectional study) 2 398\n31 Loss of smell (anosmia) (non‐cross‐sectional study) 1 262\n32 Loss of taste (ageusia) (non‐cross‐sectional study) 1 262\n33 Positive auscultation findings (non‐cross‐sectional study) 1 34\n34 Dyspnoea (non‐cross‐sectional study) 1 262\n35 Chest tightness (non‐cross‐sectional study) 1 34\n36 Fever (non‐cross‐sectional study) 2 296\n37 Fatigue (non‐cross‐sectional study) 3 432\n38 Myalgia or arthralgia (non‐cross‐sectional study) 1 262\n39 Headache (non‐cross‐sectional study) 2 296\n40 Diarrhoea (non‐cross‐sectional study) 3 812\n41 Nausea/vomiting (non‐cross‐sectional study) 2 778\n42 Gastrointestinal symptoms, not specified (non‐cross‐sectional study) 1 516\n1 Test\nCough\n2 Test\nSputum production\n3 Test\nDyspnoea\n4 Test\nHypoxia\n5 Test\nHaemoptysis\n6 Test\nPositive auscultation findings\n7 Test\nRespiratory symptoms (not specified))\n8 Test\nSore throat\n9 Test\nNasal symptoms\n10 Test\nLoss of smell (anosmia) or loss of taste (ageusia)\n11 Test\nFever\n12 Test\nLow body temperature\n13 Test\nShivers\n14 Test\nChills\n15 Test\nMyalgia or arthralgia\n16 Test\nMyalgia or fatigue\n17 Test\nFatigue\n18 Test\nHeadache\n19 Test\nNausea/vomiting\n20 Test\nDiarrhoea\n21 Test\nAbdominal pain\n22 Test\nGastrointestinal symptoms (not specified)\n23 Test\nLow systolic blood pressure\n24 Test\nHigh systolic blood pressure\n25 Test\nTachycardia\n26 Test\nPalpitations\n27 Test\nCough (non‐cross‐sectional study)\n28 Test\nSore throat (non‐cross‐sectional study)\n29 Test\nRhinorrhoea (non‐cross‐sectional study)\n30 Test\nNasal obstruction (non‐cross‐sectional study)\n31 Test\nLoss of smell (anosmia) (non‐cross‐sectional study)\n32 Test\nLoss of taste (ageusia) (non‐cross‐sectional study)\n33 Test\nPositive auscultation findings (non‐cross‐sectional study)\n34 Test\nDyspnoea (non‐cross‐sectional study)\n35 Test\nChest tightness (non‐cross‐sectional study)\n36 Test\nFever (non‐cross‐sectional study)\n37 Test\nFatigue (non‐cross‐sectional study)\n38 Test\nMyalgia or arthralgia (non‐cross‐sectional study)\n39 Test\nHeadache (non‐cross‐sectional study)\n40 Test\nDiarrhoea (non‐cross‐sectional study)\n41 Test\nNausea/vomiting (non‐cross‐sectional study)\n42 Test\nGastrointestinal symptoms, not specified (non‐cross‐sectional study)\n\nCharacteristics of studies\n\nCharacteristics of included studies [ordered by study ID]\nAi 2020a\nStudy characteristics\nPatient Sampling Purpose: diagnosis of SARS‐CoV‐2 pneumoniaDesign: cross‐sectional multicentre prospective studyRecruitment: hospitalised pneumonia patientsSample size: n = 53 (20 cases)Inclusion criteria: suspected SARS‐COV‐2 pneumonia patients, defined as having pneumonia after chest CT (with 1 of the 2 following criteria met: fever or respiratory symptoms, normal or decreased WBC counts/decreasedExclusion criteria: not defined\nPatient characteristics and setting Facility cases: confirmed case: a positive SARS‐COV‐2 nucleotides result either by metagenomic sequencing or RT‐PCR assay for nasopharyngeal swab specimensFacility controls: pneumonia patients confirmed not to be infected by SARS‐Cov2 (2 PCR tests, 2 days in between)Country: ChinaDates: 22 January 2020‐19 February 2020Symptoms and severity: suspected SARS‐COV‐2 pneumonia (NCP): having pneumonia after chest CT with 1 of the 2 following criteria met: fever or respiratory symptoms, normal or decreased WBC counts/decreased lymphocyte counts, and a travel history or contact with patients with fever or respiratory symptoms from Hubei Province or confirmed cases within 2 weeksDemographics: median age cases 37 years, controls 39 years, gender distribution cases (M/F: 50/50), controls (M/F: 48.5/51.5)Exposure history: not specified\nIndex tests Fever\nDry cough\nDiarrhoea\nFatigue\nHeadache\nVomiting\nAbdominal pain\nTarget condition and reference standard(s) TC: COVID‐19 pneumonia\nRS: a positive SARS‐COV‐2 nucleotides result either by metagenomic sequencing or RT‐PCR assay for nasopharyngeal swab specimens, repeated after 2 days if negative on day 0\nFlow and timing Time interval not specified. Reference standard at day 0 and day 2, index tests from electronic medical records but stated at pneumonia onset\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Unclear    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Unclear    \nDid the study avoid inappropriate inclusions? No    \nCould the selection of patients have introduced bias?   High risk  \nAre there concerns that the included patients and setting do not match the review question?     High\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Unclear    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Unclear    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Low risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Unclear    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Low risk  \nChen X 2020\nStudy characteristics\nPatient Sampling Purpose: diagnosis COVID‐19 pneumonia ‐ to identify differences in CT imaging and clinical manifestations between pneumonia patients with and without COVID‐19, and to develop and validate a diagnostic model for COVID‐19 based on radiological semantic and clinical featuresDesign: cross‐sectional multicentre retrospective studyRecruitment:\u2028cases: consecutive patients with COVID‐19 admitted in 5 independent hospitals\u2028controls: at the same period, another 66 consecutive pneumonia patients without COVID‐19 from Meizhou People’s HospitalSample size: n = 136 (cases = 70)Inclusion criteria: patients admitted with COVID‐19 pneumonia (cases) and patients admitted with non‐COVID‐19 pneumonia (controls)Exclusion criteria: not specified for cases except those from 1 hospital (Meizhou), for cases and controls in Meizhou: after chest CT neoplasm, tuberculosis, pulmonary oedema, pulmonary contusion, aspiration pneumonia, bronchitis, any local or systemic treatment before CT scan, normal CT image without epidemiological history\nPatient characteristics and setting Facility cases: pneumonia patients with positive SARS‐CoV‐2 testFacility controls: CT pneumonia patients with consecutive negative RT‐PCRCountry: ChinaDates: 1 January 2020‐8 February 2020Symptoms and severity: pneumonia patients for cases and control; unclear severity of casesDemographics: M/F: cases 41/29, controls 43/23\u2028mean age: cases 42.9 range, 16‐69 years, controls 46.7 range, 0.3‐93 yearsExposure history: data about exposure to epidemic centres collected, but no results in the study nor in appendices\nIndex tests Systolic BP\nDiastolic BP\nRespiration rate\nHeart rate\nTemperature\nDry cough\nFatigue\nSore throat\nStuffy\nRunny nose\nTarget condition and reference standard(s) TC: COVID‐19 pneumonia\nRS: RT‐PCR and next generation sequencing for SARS‐Cov2\nFlow and timing Time interval not specified\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Yes    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Yes    \nDid the study avoid inappropriate inclusions? No    \nCould the selection of patients have introduced bias?   High risk  \nAre there concerns that the included patients and setting do not match the review question?     High\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Unclear    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   Unclear risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Unclear\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Yes    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Low risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Unclear    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Low risk  \nCheng 2020a\nStudy characteristics\nPatient Sampling Purpose: to identify the clinical features and CT manifestations of COVID‐19 and compare them with those of pneumonia occurring in patients who do not have COVID‐19Design: cross‐sectional single‐centre retrospective studyRecruitment: pneumonia patients who presented at a fever observation department in ShanghaiSample size: n = 33 (11 cases)Inclusion criteria: patients with clinical and radiological features of pneumonia, and a normal or reduced total leukocyte count or total lymphocyte count, plus an epidemiologic history that included travel or a history of residence in Hubei province or other areas where continuous transmission of local cases occurred within 14 days before onset of symptoms, a history of contact with patients who had fever or respiratory symptoms and were from Hubei province or other areas with continuous transmission of local cases within 14 days before onset of the disease, or clustering or epidemiologic association with the new coronavirus infectionExclusion criteria: not defined\nPatient characteristics and setting Facility cases: confirmed case: positive RT‐PCR test result obtained by a throat swab. Test was repeated when the first test was negativeFacility controls: pneumonia patients confirmed not to be infected by SARS‐Cov2 (2 PCR tests)Country: ChinaDates: 19 January 2020‐6 February 2020Symptoms and severity: pneumonia was defined as patients with at least 1 clinical symptom (i.e. cough, sputum, fever, dyspnoea, or pleuritic chest pain), a finding of either coarse crackles on auscultation or elevated inflammatory biomarkers, and observation of a new pulmonary opacification on chest CTDemographics: median age +‐ SD cases 50.36 +‐ 15.5, controls 43.59 +‐ 16.02, gender distribution cases (M/F: 8/3), controls (M/F: 7/15)Exposure history: cases 8/11, controls 7/22 (in the last 14 days with patients with fever or respiratory symptoms or with known cases)\nIndex tests Fever\nCough\nSputum\nShortness of breath\nMuscle ache\nDiarrhoea\nSore throat\nPeak body temperature\nTarget condition and reference standard(s) TC: COVID‐19 pneumonia\nRS: RT‐PCR testing on throat swab specimens\nTests were repeated if the first test was negative\nFlow and timing Time interval not specified, reference test at day 0 (or later when the first test was negative), index tests were questionnaired at day 0 for the presence of symptoms in the past period of time\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Unclear    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Unclear    \nDid the study avoid inappropriate inclusions? No    \nCould the selection of patients have introduced bias?   High risk  \nAre there concerns that the included patients and setting do not match the review question?     High\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Yes    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Unclear    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Low risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Unclear    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Low risk  \nFeng 2020a\nStudy characteristics\nPatient Sampling Purpose: diagnosis COVID‐19 pneumoniaDesign: cross‐sectional, retrospective, single‐centre studyRecruitment: patients admitted to ED with history of exposure to COVID‐19Sample size: n = 132 (cases = 7)inclusion criteria: all patients admitted to the fever clinic of the ED of the First medical center, Chinese People's Liberation Army General Hospital (PLAGH) in Beijing with the epidemiological history of exposure to COVID‐19 according to WHO interim guidanceExclusion criteria: \u003c 14 years old, no other criteria specified\nPatient characteristics and setting Facility cases: among clinically suspected patients: those with a positive RT‐PCRFacility controls: clinically non‐suspected patients + suspected patients with negative RT‐PCRCountry: ChinaDates: 14 January 2020‐9 February 2020Symptoms and severity: all patients admitted, with exposure history to COVID‐19, so all levels of severity; days from illness onset until admission (median, IQR): 2.0 (1.0‐5.0); patient population with general mild disease and limited presence of comorbidities (range 0%‐2.3% (COPD))Demographics: age: controls median 40.0 years (IQR 32.5‐54.5), cases median 39.0 years (IQR 37.0‐41.5)M%/F%: cases 71.4/28.6, controls 63.2/36.8Exposure history: epidemiological history of exposure to COVID‐19 (as per WHO guidance)\nIndex tests Heart rate\nDiastolic BP\nSystolic BP\nFever (former: median only on all and cases ‐ no control median given)\nHighest temperature\nCough\nShortness of breath\nMuscle ache\nHeadache\nSore throat\nRhinorrhoea\nDiarrhoea\nNausea\nVomiting\nChills\nShiver\nExpectoration\nAbdominal pain\nFatigue\nPalpitation\nTarget condition and reference standard(s) TC: COVID‐19 pneumonia\nRS: in‐house RT‐PCR (E‐gene) ‐ at 4 institutions\nFlow and timing Index test and RS both taken on admission\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Yes    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Yes    \nDid the study avoid inappropriate inclusions? Yes    \nCould the selection of patients have introduced bias?   Low risk  \nAre there concerns that the included patients and setting do not match the review question?     Low concern\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Yes    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Unclear    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   High risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Yes    \nDid all patients receive the same reference standard? No    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   High risk  \nLiang 2020\nStudy characteristics\nPatient Sampling Purpose: to estimate the prevalence of COVID‐19 in pneumonias during this period and to find the unique features of COVID‐19 as compared to pneumonias caused by other agentsDesign: cross‐sectional, single‐centre, retrospective studyRecruitment: 342 cases of pneumonia were diagnosed in Fever Clinic in Peking University Third Hospital. From these patients, 88 were reviewed by panel discussion as possible or probable cases of COVID‐19, and received 2019‐nCoV detection by RT‐PCRSample size: n = 88 (21 cases)Inclusion criteria: patients visiting the Fever Clinic at Peking University Third Hospital. Based on epidemiological history, epidemiological evidence, fever and/or respiratory symptoms, chest radiological findings and WBC results, cases with possible or probable COVID‐19 were sent for panel discussion and then for 2019‐nCoV detection by RT‐PCRExclusion criteria: COVID‐19 unlikely by panel discussion; lack of CT scan or no signs of pneumonia on CT scan; paediatric patients\nPatient characteristics and setting Facility cases: 2019‐nCoV real‐time PCR testing, which was positive in 19 cases (confirmed cases). In another 2 patients, though PCR testing was negative, a clinical diagnosis was made according to\u2028epidemiological evidence, consistent clinical and CT findings (clinical cases)Facility controls: for the cases with negative viral detection, the diagnosis of COVID‐19 was excluded based on inconsistent epidemiological, clinical or radiological dataCountry: ChinaDates: 21 January 2020‐15 February 2020SymptomsFever with a mean body temperature of 37.8 C\nCough\nExpectoration\nFatigue\nHeadache\nDizziness\nShortness of breath\nMyalgia or arthralgia\nSore throat\nNasal symptoms and diarrhoea\nSeverity of COVID‐19Mild‐moderate: fever and/or respiratory symptoms with pneumonia in radiology examination, without signs of severe or very severe diseases\nSevere: presence of 1 of the following: respiratory rate ≥ 30 beat/min; SpO2 ≤ 93% at rest; PaO2/FiO2 ≤ 300 mmHg\nVery severe: presence of 1 of the following: severe respiratory failure requiring mechanical ventilation; shock; complicated with other organ failure and requiring ICU admission\nDemographics: COVID‐group only: median age was 42.0 years (25th‐75th percentile, 34.5‐66.0 years). Range 24‐85. Male/female: 11 (52.4%)/10 (47.6%)Exposure history: 19/21 (90.5%) had a clear epidemiological history of COVID‐19. 7 patients, from 5 family clusters, had close contact with their family members\nIndex tests Fever with a mean body temperature of 37.8 C\nCough\nExpectoration\nFatigue\nHeadache\nDizziness\nShortness of breath\nMyalgia or arthralgia\nSore throat\nNasal symptoms and diarrhoea\nTarget condition and reference standard(s) TC: COVID‐19 pneumonia\nRS: 2019‐nCoV real‐time PCR testing or clinical diagnosis was made according to epidemiological evidence, consistent clinical and CT findings\nFlow and timing Time interval not specified\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Unclear    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? No    \nDid the study avoid inappropriate inclusions? No    \nCould the selection of patients have introduced bias?   High risk  \nAre there concerns that the included patients and setting do not match the review question?     High\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Yes    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? No    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Low risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Unclear    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   High risk  \nNobel 2020\nStudy characteristics\nPatient Sampling Purpose: assess GI symptoms in COVID‐19 and their association with short‐term outcomesDesign: diagnostic case‐control, retrospective studyRecruitment: adults who underwent nasopharyngeal swab testing for SARS‐CoV‐2 at outpatient settings: clinics or the ED, of New York‐Presbyterian‐Columbia or the medical centre's affiliates in New YorkSample size: 516 (278 cases)Inclusion criteria: adults ≥ 18 years of age who underwent nasopharyngeal swab testing for SARS‐CoV‐2. Indications for testing during this period were respiratory symptoms (cough, fever, shortness of breath) with intent to hospitalise or the same symptoms in essential personnel.Exclusion criteria: if insufficient data were available in the electronic medical record or if testing was performed during a pre‐existing inpatient admission\nPatient characteristics and setting Facility cases: SARS‐CoV‐2 PCR test result positive (1 test)Facility controls: SARS‐CoV‐2 PCR test result negativeCountry: USADates: 10 March 2020‐21 March 2020Symptoms and severity: respiratory symptoms (cough, fever, shortness of breath) with intent to hospitalise or in essential workersDemographics: median age: 51‐70 years (cases and controls), gender distribution: cases (M/F(%): 52/48), controls (M/F(%): 45/55)Exposure history: not specified\nIndex tests GI symptoms: diarrhoea, vomiting/nausea\nTarget condition and reference standard(s) TC: SARS‐Cov‐2 infection\nRS: SARS‐CoV‐2 PCR test, once (nasopharyngeal swab)\nFlow and timing Time interval: both taken at intake\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Yes    \nWas a case‐control design avoided? No    \nDid the study avoid inappropriate exclusions? Yes    \nDid the study avoid inappropriate inclusions? Yes    \nCould the selection of patients have introduced bias?   Low risk  \nAre there concerns that the included patients and setting do not match the review question?     Low concern\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Yes    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Unclear    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Low risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Yes    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Low risk  \nPeng 2020a\nStudy characteristics\nPatient Sampling Purpose: analyse the clinical features and imaging manifestations of COVID‐19Design: cross‐sectional, single‐centre, retrospective studyRecruitment: clinically suspected cases who were sent to hospital for screeningSample size: n = 86 (n = 11)Inclusion criteria: clinically suspected patientsExclusion criteria: not specified\nPatient characteristics and setting Facility cases: positive RT‐PCR via nasopharyngeal swabFacility controls: negative RT‐PCR via nasopharyngeal swab (1x)Country: ChinaDates: 23 January 2020‐16 February 2020Symptoms and severity: fever, cough, dyspnoea, sore throat, fatigue, systemic soreness, runny noseDemographics: M/F: total 39/47, cases: 5/6, controls 34/40Case group: mean age 40.73 ± 11.32 years, 5 men. Control group: mean age 39.67 ± 13.90 years, 34 menExposure history: 7/11 COVID‐19 patients (63.6%) had a history of travel to Hubei (5 Wuhan, 1 Huanggang, 1 Xiaogan), 2 patients had close contact with the COVID‐19 patients, and 2 taxi drivers\nIndex tests Fever\nCough\nDyspnoea\nSore throat\nFatigue\nSystemic soreness\nRunny nose\nTarget condition and reference standard(s) TC: SARS‐Cov‐2 infection\nRS: RT‐PCR (nasopharyngeal swab)\nFlow and timing Time interval not specified\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Unclear    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Unclear    \nDid the study avoid inappropriate inclusions? Unclear    \nCould the selection of patients have introduced bias?   Unclear risk  \nAre there concerns that the included patients and setting do not match the review question?     Unclear\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Yes    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Unclear    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Low risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Unclear    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Low risk  \nRentsch 2020\nStudy characteristics\nPatient Sampling Purpose: diagnosis SARS‐CoV‐2 test positivesDesign: cross‐sectional, retrospective studyRecruitment: electronic health record data from the national Veterans Affairs Healthcare System ‐ national Corporate Data Warehouse (USA)Sample size: 3789 (585 cases)Inclusion criteria: all patients in the Veterans Affairs cohort, born between 1945 and 1965 and active in care, tested for COVID‐19 between 8 February and 30 March 2020Exclusion criteria: patients for whom results were pending (n = 93) or inconclusive (n = 33) were excluded\nPatient characteristics and setting Facility cases: tested positive for SARS‐CoV‐2Facility controls: tested negative for SARS‐CoV‐2Country: USADates: 8 February 2020‐30 March 2020Symptoms and severity: all patients who were tested were includedDemographics: median age overall: 65.7 years (IQR 60.5‐70.7) (cases: 66.1 years, controls: 65.6 years);gender overall (M%/F%): 90.2/9.8, cases 95.4/4.6, controls 89.2/10.8Exposure history: not specified (all over USA)\nIndex tests Hypoxia (oxygen saturation ≤ 93%)\nBody temperature (3 categories)\nTarget condition and reference standard(s) TC: SARS‐CoV‐2 infection\nRS: no data on reference PCR test used, multiple different reference tests used with unknown test characteristics (samples: nasopharyngeal swabs)\nFlow and timing Time interval maximum 2 days\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Yes    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Yes    \nDid the study avoid inappropriate inclusions? Unclear    \nCould the selection of patients have introduced bias?   Low risk  \nAre there concerns that the included patients and setting do not match the review question?     Unclear\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Unclear    \nIf a threshold was used, was it pre‐specified? Yes    \nCould the conduct or interpretation of the index test have introduced bias?   Unclear risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Unclear    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Unclear    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Unclear risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Yes    \nDid all patients receive the same reference standard? Unclear    \nWere all patients included in the analysis? No    \nCould the patient flow have introduced bias?   Low risk  \nSong 2020b\nStudy characteristics\nPatient Sampling Purpose: to develop a tool for early diagnosis of SARS‐CoV2‐infected patientsDesign: cross‐sectional, retrospective, single‐centre (2 time frame study: training ‐ validation data set)Recruitment: 1311 patients who presented to the First Affiliated Hospital, School of Medicine, Zhejiang University with at least 1 SARS‐CoV‐2 RT‐PCR testSample size: n = 304 (73 cases) (= subset of the study including training dataset only)n = 95 (18 cases) (= validation dataset)Inclusion criteriaAll RT‐PCR‐positive cases; 1311\nAll RT‐PCR‐negative patients who came to the First Affiliated Hospital, School of Medicine, Zhejiang University and performed with at least 1 SARS‐CoV‐2 nucleic acid detection for analysis RT‐PCR\nFirst 60% of negative outpatients sorted by 'Z‐A' based on Chinese first name from Qingchun District (training dataset), and then final 40% who presented (validation dataset)\nExclusion criteriaAsymptomatic patients without history of exposure but had strong willingness for detection\nPatients with \"important\" missing data\nPatient characteristics and setting Facility cases: positive SARS‐CoV‐2Facility controls: negative SARS‐CoV‐2Country: ChinaDates: 20 January 2020‐05 February 2020Symptoms and severity: in positives: non‐severe (n = 31), including mild or moderate patients to severe (n = 42) including severe or critical patientsMild: patients had no pneumonia on imaging (CT)\nModerate: patients with symptoms and imaging examination showing pneumonia\nSevere: patients meet any of the following:\nrespiratory rate ≥ 30/min\nresting pulse SpO2 ≤ 93%\nPaO2/FiO2 ≤ 300 mmHg (1 mmHg = 0.133 kPa)\nmultiple pulmonary lobes showing more than 50% progression of lesion in 24‐48 hours on imaging\nCritical: patients meet any of the following:\nrespiratory failure requiring mechanical ventilation\nshock\ncombination of other organ failure that requires admission to ICU\nDemographics: M/F: cases 46/27, controls 104/127\u2028median age: cases 53.0 years (43.5‐62.0) controls 34 years (29‐49)Exposure history: Wuhan‐related exposure and or close contact to confirmed COVID‐19 case: cases 40.7%, controls 57.5%\nIndex tests Fever\nCough\nExpectoration\nHeadache\nMyalgia or fatigue\nChill\nRhinobyon/rhinorrhoea\nPharyngalgia\nDyspnoea\nDiarrhoea\nNausea/vomiting\nTemperature (maximum)\nBody temperature\nSpO2\nRespiratory rate\nHeart rate\nMean arterial pressure\nTarget condition and reference standard(s) TC: SARS‐CoV‐2 infection\nRS: RT‐PCR for SARS‐CoV‐2 (test not specified: \"using emergency use authorization approved SARS‐CoV‐2 assays)\" (following WHO protocol, 2 target RT‐PCR (ORF1 and N)\nFlow and timing Within 3 h for RS, first in‐hospital stay for index tests\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? No    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Unclear    \nDid the study avoid inappropriate inclusions? Yes    \nCould the selection of patients have introduced bias?   Unclear risk  \nAre there concerns that the included patients and setting do not match the review question?     Low concern\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Unclear    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Yes    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Low risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Yes    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Low risk  \nSun 2020a\nStudy characteristics\nPatient Sampling Purpose: algorithm development for estimating risk COVID‐19Design: cross‐sectional, retrospective studyRecruitment: patients presenting at the designated national outbreak screening centre and tertiary care hospital in Singapore for SARS‐CoV‐2 testing. Patients were either self‐referred, referred from primary care facilities, or were at‐risk cases identified by national contact tracing efforts (recruited n = 991)Sample size: n = 788 (n = 54)Inclusion criteria: patients presenting to the centre:self‐referred\nreferred from primary care facilities\nat‐risk cases identified by national contact tracing efforts\nExclusion criteria: PCR results not available at time of data collection ‐ no electronic medical records ‐ unavailable vital sign records\nPatient characteristics and setting Facility cases: positive SARS‐CoV2 RT‐PCR testFacility controls: all SARS‐CoV‐2 RT‐PCR results were negative (minimum 2 test negatives in high‐risk patients, minimum 1 test low‐risk patients)Country: SingaporeDates: 26 January 2020‐16 February 2020Symptoms and severity: 252 (33.2%) symptoms \u003e 5 days at presentation, 75 (9.5%) any comorbiditybody temperature\nheart rate\nrespiratory rate\nsystolic BP\ndiastolic BP\ncough\nsputum production\nshortness of breath\nrhinnorhoea or nasal congestion\nsore throat\nauscultation finding of pneumonia\nother respiratory symptoms\ngastrointestinal symptoms\nDemographics: median age 34 years (range 7 years‐98 years, IQR 27‐45) (cases median 42 years, range 16‐79; controls 34 years (range 7‐98); M/F: 48.3%/51.7% F (cases M: 88 (88.9%))Exposure history: contact with a known COVID‐19 case (20.1% (32/54 cases (59.3%)); 126/734 controls (17.2%), contact with travellers from China (22.1%, 15/54 cases (27.8%); 42/734 controls (5.7%)), recent travel history, and visit to hospital in China within 14 days prior to symptom onset (0.8%)\nIndex tests Body temperature\nHeart rate\nRespiratory rate\nSystolic BP\nDiastolic BP\nCough\nSputum production\nShortness of breath\nRhinnorhea or nasal congestion\nSore throat\nAuscultation finding of pneumonia\nOther respiratory symptoms\nGI symptoms\nTarget condition and reference standard(s) TC: SARS‐CoV‐2 infection\nRS: SARS‐CoV‐2 2 commercial assays 2‐target (1 assay: Orf1ab and N ‐ other unclear) RT‐PCR\nFlow and timing Time interval not specified\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Yes    \nWas a case‐control design avoided? No    \nDid the study avoid inappropriate exclusions? Yes    \nDid the study avoid inappropriate inclusions? Yes    \nCould the selection of patients have introduced bias?   High risk  \nAre there concerns that the included patients and setting do not match the review question?     High\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Yes    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? No    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Low risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Unclear    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Low risk  \nTolia 2020\nStudy characteristics\nPatient Sampling Purpose: diagnosis of acute SARS‐CoV‐2 infectionDesign: cross‐sectional, retrospective studyRecruitment: all patients presenting to 1 of 2 EDs, located at an urban teaching hospital, and academic quaternary medical centre, within the same healthcare system who had targeted testing based on clinician's decision during the initial 10 days of test availabilitySample size: n = 283 (29 cases)Inclusion criteria:patients presenting with symptoms related to COVID‐19 infection (fever and cough or shortness of breath)\ntravel within 14 days to countries with high rates of infection (at that time China, Iran, Italy, Japan, and South Korea) or\nrisk factors for infection complications (including age or comorbid conditions) or\nthe patient was a healthcare worker who could potentially expose others at risk and clinician made decision for testing\nExclusion criteria: not specified\nPatient characteristics and setting Facility cases: positive SARS‐CoV‐2 testFacility controls: negative SARS‐CoV‐2 test, visiting the same EDs and being testedCountry: USA (San Diego, CA)Dates: 10 March 2020‐19 March 2020Symptoms and severity:all patients presenting to ED who were eligible for targeted testing (= patients presenting with symptoms related to COVID‐19 infection (fever and cough or shortness of breath)\ntravel within 14 days to countries with high rates of infection (at that time China, Iran, Italy, Japan, and South Korea) or\nrisk factors for infection complications (including age or comorbid conditions) or\nthe patient was a healthcare worker who could potentially expose others at risk\ncomorbidities 101/235 (43.0%) (cases: 8/27 (29.6%), controls 93/208 (44.7%))\nDemographics: age (\u003c 18 years: 0.7%, 18‐64 years: 83.4%, \u003e 65 years: 15.9%); gender: cases M/F%: 55.2/44.8; controls M/F%: 52.8/47.2; all M/F%: 53.0/47.0Exposure history: recent travel (5.5%), 90.6% symptom‐based criteria for testing, no known exposure history based\nIndex tests Fever\nTarget condition and reference standard(s) TC: SARS‐CoV‐2 infection\nRS: Commercial RT‐PCR test ‐ ePLex SARS‐CoV‐2 test (nasopharyngeal swab)\nFlow and timing Probably no time interval between index test and RS, but not specified\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Yes    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Unclear    \nDid the study avoid inappropriate inclusions? Yes    \nCould the selection of patients have introduced bias?   Unclear risk  \nAre there concerns that the included patients and setting do not match the review question?     Low concern\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Yes    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Unclear    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Unclear risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Unclear    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Low risk  \nWee 2020\nStudy characteristics\nPatient Sampling Purpose: to analyse OTDs as a diagnostic criterion for COVID‐19Design: cross‐sectional, prospective single‐centre studyRecruitment: all suspected cases presenting to the EDSample size: n = 870 (cases = 154)Inclusion criteria:presence of respiratory symptoms and suspicious epidemiological links or travel history or\nnew onset OTD\nExclusion criteria: not specified\nPatient characteristics and setting Facility cases: positive RT‐PCR for 2019‐nCovFacility controls: negative RT‐PCR for 2019‐nCovCountry: SingaporeDates: 26 March 2020‐10 April 2020Symptoms and severity: loss of sense of smell/tasteDemographics: not specifiedExposure history: close contact of a confirmed COVID‐19 case: cases 42/112, controls 37/679\nIndex tests Loss of sense of smell/taste\nTarget condition and reference standard(s) TC: SARS‐Cov‐2 infection\nRS: RT‐PCR (oropharyngeal swabs)\nFlow and timing Time interval: same day\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Unclear    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Unclear    \nDid the study avoid inappropriate inclusions? Yes    \nCould the selection of patients have introduced bias?   Low risk  \nAre there concerns that the included patients and setting do not match the review question?     Low concern\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Yes    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Unclear    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Low risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Yes    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Low risk  \nYan 2020a\nStudy characteristics\nPatient Sampling Purpose: to evaluate association of patient‐reported symptoms with a focus on sense of smell and taste and SARS‐CoV‐2 infectionDesign: internet survey of patients after presentation to a single‐centreRecruitment: email invitation with 1 phone call follow‐up to everyone who was tested for COVID‐19 between 3 March 2020 and 29 March 2020Sample size: n = 262 (cases: 59)Inclusion criteria:adult patients who presented to the institution and got tested for COVID‐19\nanalysis on responders to email survey (responses: cases 59/102, controls 203/1378)\nExclusion criteria:\nPatient characteristics and setting Facility cases: SARS‐CoV‐2‐positiveFacility controls: SARS‐CoV‐2‐negativeCountry: USA, San DiegoDates: 3 March 2020‐29 March 2020Symptoms and severity:larger representation of ambulatory patients (higher response rate to survey)\nseverity ‐ hospital admission: cases 4/59, controls 14/203\nDemographics: adults only, M/F: cases 29/29, controls 69/132Exposure history: not specified\nIndex tests Fatigue\nLoss of taste\nFever\nLoss of sense of smell\nCough\nHeadache\nMyalgia\nDyspnoea\nDiarrhoea\nNasal obstruction\nSore throat\nRhinorrhoea\nNausea\nTarget condition and reference standard(s) TC: SARS‐CoV‐2 infection\nRS: PCR for SARS‐CoV‐2 (sample not specified)\nFlow and timing PCR taken at presentation, not specified when the questionnaire was sent. Patients had to list their symptoms at presentation.\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Yes    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Unclear    \nDid the study avoid inappropriate inclusions? Unclear    \nCould the selection of patients have introduced bias?   Unclear risk  \nAre there concerns that the included patients and setting do not match the review question?     Unclear\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? No    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Unclear    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Yes    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Low risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Unclear    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Unclear risk  \nYang 2020d\nStudy characteristics\nPatient Sampling Purpose: to identify differences in CT imaging and clinical features between COVID‐19 and\u2028influenza pneumonia in the early stage, and to identify the most valuable features in the differential\u2028diagnosisDesign: diagnostic case‐control study, retrospective multicentre with historic control groupRecruitment: cases: confirmed SARS‐CoV‐2 patients; controls: influenza pneumonia patients (1 January 2015‐30 September 2019 from 2 hospitals)Sample size: n = 121 (cases = 73)Inclusion criteria: patients confirmed with SARS‐CoV‐2; controls: patients who had 9 respiratory pathogen IgM antibody tested from January 2015‐September 2019Exclusion criteria: cases: not specifiedcontrols:parainfluenza\nrespiratory syncytial virus\nadenovirus\nLegionella spp\nMycoplasma pneumoniae\nChlamydia pneumoniae\nCoxiella burnetii\naspiration pneumonia\nradiation pneumonia\npulmonary contusion\npulmonary oedema\nneoplasm\nNo CT date, no clinical date\nPatient characteristics and setting Facility cases: positive RT‐PCR for 2019‐nCovFacility controls: influenza pneumoniaCountry: ChinaDates: 1 January 2020‐15 February 2020Symptoms and severity: all patients in early stages of COVID‐19 or influenza pneumoniaDemographics: M/F: cases 41/32, controls 30/18\u2028mean age: cases 41.9, controls 40.4Exposure history: not specified\nIndex tests Body temperature\nCough\nFatigue\nSore throat\nStuffy and runny nose\nTarget condition and reference standard(s) TC: COVID‐19 pneumonia\nRS: RT‐PCR (sample not specified)\nFlow and timing Time interval unclear\nComparative  \nNotes Overlaps with Chen X 2020\nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Yes    \nWas a case‐control design avoided? No    \nDid the study avoid inappropriate exclusions? Unclear    \nDid the study avoid inappropriate inclusions? No    \nCould the selection of patients have introduced bias?   High risk  \nAre there concerns that the included patients and setting do not match the review question?     High\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Unclear    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Unclear    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   High risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     High\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Unclear    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Unclear risk  \nZhao 2020a\nStudy characteristics\nPatient Sampling Purpose: to compare and assess the clinical features of COVID‐19 pneumonia with features in non‐COVID‐19 pneumonia patientsDesign: diagnostic case control, retrospective studyRecruitment: patients with similar duration between symptom onset to admission were selected as controlsSample size: n = 34 (n = 15)Inclusion criteria: admitted pneumonia cases with a history of travel to Hubei or exposure to a PCR SARS‐CoV‐2‐confirmed‐positive patientExclusion criteria: not specified\nPatient characteristics and setting Facility cases: single sputum or throat swab test RT‐PCR‐positive pneumoniaFacility controls: for non‐COVID‐19 confirmation: 3 consecutive negative throat swabs or sputum sampling every other day during first 7 days of admissionCountry: China, AnhuiDates: 23 January 2020‐5 February 2020Symptoms and severity:fever\ncough\nsore throat\nheadache\nfatigue\ndiarrhoea\nchest tightness\nabnormal lung auscultation\nDemographics: mean age (cases/controls): 48 (IQR 27~56)/35 (IQR 27~46) in COVID‐19 and non‐COVID‐19 patients, respectively; F/M (cases/controls): 8 (42.11%)Exposure history: all patients had a history of exposure to confirmed cases of 2019‐nCoV or travel to Hubei before illness. Investigators interviewed each patient and their relatives, where necessary, to determine exposure or close contact histories during the 2 weeks before the illness onset\nIndex tests Fever\nCough\nSore throat\nHeadache\nFatigue\nDiarrhoea\nChest tightness\nAbnormal lung auscultation\nTarget condition and reference standard(s) TC: COVID‐19 pneumonia\nRS: real‐time RT‐PCR (unknown assay) (sample: throat swabs or/and sputa)\nFlow and timing Time interval not specified\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? No    \nWas a case‐control design avoided? No    \nDid the study avoid inappropriate exclusions? Unclear    \nDid the study avoid inappropriate inclusions? Yes    \nCould the selection of patients have introduced bias?   High risk  \nAre there concerns that the included patients and setting do not match the review question?     High\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Yes    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Yes    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Unclear risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Unclear    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Unclear risk  \nZhu 2020b\nStudy characteristics\nPatient Sampling Purpose: description of initial clinical features in patients with suspected and confirmed SARS‐CoV‐2 infectionDesign: cross‐sectional, retrospective studyRecruitment: all patients with suspected COVID‐19 who presented to the ED of the First Affiliated Hospital of USTC and the Infectious Hospital of the First Affiliated Hospital of USTC for the first timeSample size: n = 116 (32 cases)Inclusion criteria:patients defined as suspected SARS‐CoV‐2 infection based on guidelines for the diagnosis and treatment of pneumonia caused by novel coronavirus infection (trial version III)\npresentation to, clinical observation and quarantine in our ED\nnucleic acid amplification test performed in the ED\nExclusion criteria: transfer from another hospital or previous visit to our hospital and previous diagnosis of COVID‐19\nPatient characteristics and setting Facility cases: positive nucleic acid amplification test on admission or 24 h laterFacility controls: SARs‐CoV‐2 PCR test negativeCountry: China, AnhuiDates: 24 January 2020‐20 February 2020Symptoms and severity: all suspected COVID‐19 patients included; days since onset of symptoms median 5 (IQR 2‐7)Demographics: median age: all: 40 years (IQR 27‐53), cases: 46 years (IQR 35‐52), controls: 35 years (IQR 27‐53); gender distribution M%/F%: all 46/54, cases 47/53, controls 46/54Exposure history: no specific exposure history common to all patients with suspected disease: 8 (25%) diagnosed patients had visited Wuhan in the previous 2 weeks and 12 (38%) had been exposed to patients with infection in the previous 2 weeks\nIndex tests Fever\nCough\nMyalgia or fatigue\nExperctoration\nChest stuffiness (congestion)\nHaemoptysis\nHeadache\nDiarrhoea\nTarget condition and reference standard(s) TC: SARS‐CoV‐2 infection\nRS: nucleic acid amplification test not further specified (twice in case negatives) (samples: swabs, origin not specified)\nFlow and timing Index tests and RS both taken on admission or after 24 h\nComparative  \nNotes  \nMethodological quality\nItem Authors' judgement Risk of bias Applicability concerns\nDOMAIN 1: Patient Selection\nWas a consecutive or random sample of patients enrolled? Yes    \nWas a case‐control design avoided? Yes    \nDid the study avoid inappropriate exclusions? Yes    \nDid the study avoid inappropriate inclusions? Yes    \nCould the selection of patients have introduced bias?   Low risk  \nAre there concerns that the included patients and setting do not match the review question?     Low concern\nDOMAIN 2: Index Test (All tests)\nWere the index test results interpreted without knowledge of the results of the reference standard? Yes    \nIf a threshold was used, was it pre‐specified? No    \nCould the conduct or interpretation of the index test have introduced bias?   High risk  \nAre there concerns that the index test, its conduct, or interpretation differ from the review question?     Low concern\nDOMAIN 3: Reference Standard\nIs the reference standards likely to correctly classify the target condition? Yes    \nWere the reference standard results interpreted without knowledge of the results of the index tests? Unclear    \nCould the reference standard, its conduct, or its interpretation have introduced bias?   Unclear risk  \nAre there concerns that the target condition as defined by the reference standard does not match the question?     Low concern\nDOMAIN 4: Flow and Timing\nWas there an appropriate interval between index test and reference standard? Yes    \nDid all patients receive the same reference standard? Yes    \nWere all patients included in the analysis? Yes    \nCould the patient flow have introduced bias?   Unclear risk  \nBP: blood pressure; COPD: constructive obstructive pulmonary disease; COVID‐19: coronavirus disease 2019; CT: computed tomography; ED: emergency department; F: female; FiO2: fraction of inspired oxygen; GI: gastrointestinal; ICU: intensive care unit; IgM: immunoglobulin M;IQR: interquartile range; M: male; NCP: novel coronavirus pneumonia; OTD: olfactory and taste disorder; PaO2: partial pressure of oxygen; RS: reference standard; RT‐PCR: reverse transcription polymerase chain reaction; SARS‐CoV‐2: severe acute respiratory syndrome coronavirus 2; SD: standard deviation;SpO2: oxygen saturation; TC: target condition; WBC: blood white blood cell; WHO: World Health Organization; 2019‐nCoV: 2019 novel coronavirus\n\nCharacteristics of excluded studies [ordered by study ID]\nStudy Reason for exclusion\nGuan 2020 SARS‐CoV‐2‐positive cases only\nSoares 2020 No data\nSong 2020 SARS‐CoV‐2‐positive cases only\nWang 2020 No data\n\nContributions of authors\nJD, JDi, YT, CD, ML, RS, LH, AV, DE, and SD contributed clinical, methodological and/or technical expertise to drafting the protocol. JD co‐ordinated contributions from all co‐authors and drafted the protocol. ML drafted the QUADAS‐2 criteria. AVDB oversaw the overall progress of this review, drafted the manuscript and participated in the selection and data extraction. TS participated in the data extraction, analyses and drafting of the manuscript. JD and BH also participated in the data extraction, interpretation of the findings and commented on the manuscript.\n\nSources of support\n\nInternal sources\nLiverpool School of Tropical Medicine, UK\nUniversity of Birmingham, UK\n\nExternal sources\nDepartment for International Development, UK\nProject number: 300342‐104\nNational Institute for Health Research (NIHR), UK\nNIHR Birmingham Biomedical Research Centre at the University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham, UK\n\nDeclarations of interest\nThomas Struyf: none known\nJonathan J Deeks: none known\nJacqueline Dinnes: none known\nYemisi Takwoingi: none known\nClare Davenport: none known\nMariska MG Leeflang: none known\nRené Spijker: the Dutch Cochrane Centre (DCC) has received grants for performing commissioned systematic reviews. In no situation, the commissioner had any influence on the results of the work.\nLotty Hooft: none known\nDevy Emperador: is employed by FIND. FIND has several clinical research projects to evaluate multiple new diagnostic tests against published Target Product Profiles that have been defined through consensus processes. These studies are for diagnostic products developed by private sector companies who provide access to know‐how, equipment/reagents, and contribute through unrestricted donations as per FIND policy and external SAC review.\nSabine Dittrich: is employed by FIND with funding from DFID and Australian Aid. FIND is a global non‐for profit product development partnership and WHO Diagnostic Collaboration Centre. It is FIND’s role to accelerate access to high quality diagnostic tools for low resource settings and this is achieved by supporting both R\u0026D and access activities for a wide range of diseases, including COVID‐19. .FIND has several clinical research projects to evaluate multiple new diagnostic tests against published Target Product Profiles that have been defined through consensus processes. These studies are for diagnostic products developed by private sector companies who provide access to know‐how, equipment/reagents, and contribute through unrestricted donations as per FIND policy and external SAC review.\nJulie Domen: none known\nSebastiaan Horn: none known\nAnn Van den Bruel: none 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