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      The prevalence of symptoms in 24,410 adults infected by the novel coronavirus (SARS-CoV-2; COVID-19): A systematic review and meta-analysis of 148 studies from 9 countries

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          Abstract

          Background

          To limit the spread of SARS-CoV-2, an evidence-based understanding of the symptoms is critical to inform guidelines for quarantining and testing. The most common features are purported to be fever and a new persistent cough, although the global prevalence of these symptoms remains unclear. The aim of this systematic review is to determine the prevalence of symptoms associated with COVID-19 worldwide.

          Methods

          We searched PubMed, Embase, CINAHL, AMED, medRxiv and bioRxiv on 5 th April 2020 for studies of adults (>16 years) with laboratory test confirmed COVID-19. No language or publication status restrictions were applied. Data were independently extracted by two review authors into standardised forms. All datapoints were independently checked by three other review authors. A random-effects model for pooling of binomial data was applied to estimate the prevalence of symptoms, subgrouping estimates by country. I 2 was used to assess inter-study heterogeneity.

          Results

          Of 851 unique citations, 148 articles were included which comprised 24,410 adults with confirmed COVID-19 from 9 countries. The most prevalent symptoms were fever (78% [95% CI 75%-81%]; 138 studies, 21,701 patients; I 2 94%), a cough (57% [95% CI 54%-60%]; 138 studies, 21,682 patients; I 2 94%) and fatigue (31% [95% CI 27%-35%]; 78 studies, 13,385 patients; I 2 95%). Overall, 19% of hospitalised patients required non-invasive ventilation (44 studies, 6,513 patients), 17% required intensive care (33 studies, 7504 patients), 9% required invasive ventilation (45 studies, 6933 patients) and 2% required extra-corporeal membrane oxygenation (12 studies, 1,486 patients). The mortality rate was 7% (73 studies, 10,402 patients).

          Conclusions

          We confirm that fever and cough are the most prevalent symptoms of adults infected by SARS-CoV-2. However, there is a large proportion of infected adults which symptoms-alone do not identify.

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          Most cited references70

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Clinical Characteristics of Coronavirus Disease 2019 in China

            Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)
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              Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

              Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
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                Author and article information

                Contributors
                Role: Data curationRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Project administrationRole: SoftwareRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                23 June 2020
                2020
                23 June 2020
                : 15
                : 6
                : e0234765
                Affiliations
                [1 ] University of Sheffield, Broomhall, Sheffield, United Kingdom
                [2 ] Academic section of vascular surgery, department of surgery and cancer, Imperial College London, London, United Kingdom
                [3 ] Unit Cancer Epidemiology–Belgian Cancer Centre, Sciensano, Belgium
                [4 ] Leeds Institute for Medical Research, University of Leeds, Leeds, United Kingdom
                [5 ] Department of Plastic and Reconstructive Surgery, Leeds Teaching Hospitals, Leeds, United Kingdom
                [6 ] Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
                [7 ] MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
                [8 ] Division of Pathology and Data Analytics, University of Leeds, Leeds, United Kingdom
                [9 ] Department of Histopathology, Leeds Teaching Hospitals, Leeds, United Kingdom
                University of Oxford, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-9504-2147
                http://orcid.org/0000-0002-2045-2923
                http://orcid.org/0000-0001-8365-6547
                Article
                PONE-D-20-13070
                10.1371/journal.pone.0234765
                7310678
                32574165
                318e6838-19c8-4240-b7f7-36360d81ba5a
                © 2020 Grant et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 5 May 2020
                : 2 June 2020
                Page count
                Figures: 3, Tables: 1, Pages: 19
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000659, Research Trainees Coordinating Centre;
                Award ID: DRF-2018-11-ST2-028
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000659, Research Trainees Coordinating Centre;
                Award ID: DRF-2018-11-ST2-048
                Award Recipient :
                Funded by: Sciensano
                Award ID: VALCOR project
                Award Recipient :
                Ryckie G Wade is a Doctoral Research Fellow funded by the National Institute for Health Research (NIHR, DRF-2018-11-ST2-028). Luke McGuinness is supported by an NIHR Doctoral Research Fellowship (DRF-2018-11-ST2-048). 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. Marc Arbyn was supported by the VALCOR project (Sciensano, Brussels, Begium). The funders had no role in the initiation, conduct or publication of this project.
                Categories
                Research Article
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Coughing
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Coughing
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Coughing
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Signs and Symptoms
                Coughing
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Fevers
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Signs and Symptoms
                Fevers
                Research and Analysis Methods
                Research Assessment
                Systematic Reviews
                Research and Analysis Methods
                Mathematical and Statistical Techniques
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                Physical Sciences
                Mathematics
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                Statistical Methods
                Metaanalysis
                Research and Analysis Methods
                Research Design
                Laboratory Tests
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Vomiting
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Vomiting
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Vomiting
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Signs and Symptoms
                Vomiting
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Fatigue
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Signs and Symptoms
                Fatigue
                Research and Analysis Methods
                Research Assessment
                Research Reporting Guidelines
                Custom metadata
                The raw extracted data and additional relevant files are available via an Open Science Framework repository ( https://doi.org/10.17605/OSF.IO/9VX6U).
                COVID-19

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