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      Demographic risk factors for COVID-19 infection, severity, ICU admission and death: a meta-analysis of 59 studies

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          Abstract

          Objective

          We aimed to describe the associations of age and sex with the risk of COVID-19 in different severity stages ranging from infection to death.

          Design

          Systematic review and meta-analysis.

          Data sources

          PubMed and Embase through 4 May 2020.

          Study selection

          We considered cohort and case–control studies that evaluated differences in age and sex on the risk of COVID-19 infection, disease severity, intensive care unit (ICU) admission and death.

          Data extraction and synthesis

          We screened and included studies using standardised electronic data extraction forms and we pooled data from published studies and data acquired by contacting authors using random effects meta-analysis. We assessed the risk of bias using the Newcastle-Ottawa Scale.

          Results

          We screened 11.550 titles and included 59 studies comprising 36.470 patients in the analyses. The methodological quality of the included papers was high (8.2 out of 9). Men had a higher risk for infection with COVID-19 than women (relative risk (RR) 1.08, 95% CI 1.03 to 1.12). When infected, they also had a higher risk for severe COVID-19 disease (RR 1.18, 95% CI 1.10 to 1.27), a higher need for intensive care (RR 1.38, 95% CI 1.09 to 1.74) and a higher risk of death (RR 1.50, 95% CI 1.18 to 1.91). The analyses also showed that patients aged 70 years and above have a higher infection risk (RR 1.65, 95% CI 1.50 to 1.81), a higher risk for severe COVID-19 disease (RR 2.05, 95% CI 1.27 to 3.32), a higher need for intensive care (RR 2.70, 95% CI 1.59 to 4.60) and a higher risk of death once infected (RR 3.61, 95% CI 2.70 to 4.84) compared with patients younger than 70 years.

          Conclusions

          Meta-analyses on 59 studies comprising 36.470 patients showed that men and patients aged 70 and above have a higher risk for COVID-19 infection, severe disease, ICU admission and death.

          PROSPERO registration number

          CRD42020180085.

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          Most cited references83

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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 Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China

              In December 2019, novel coronavirus (2019-nCoV)-infected pneumonia (NCIP) occurred in Wuhan, China. The number of cases has increased rapidly but information on the clinical characteristics of affected patients is limited.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2021
                11 January 2021
                : 11
                : 1
                : e044640
                Affiliations
                [1 ]departmentDepartment of Orthopaedics , Leiden University Medical Center , Leiden, The Netherlands
                [2 ]departmentDepartment of Methodology and Statistics, Care and Public Health Research Institute (CAPHRI) , Maastricht University , Maastricht, The Netherlands
                [3 ]departmentDepartment of Educational Research and Development, School of Health Professions Education , Maastricht University , Maastricht, The Netherlands
                [4 ]departmentDepartment of General Practice, Care and Public Health Research Institute (CAPHRI) , Maastricht University , Maastricht, The Netherlands
                [5 ]Amsterdam University Medical Center, location VUmc , Amsterdam, The Netherlands
                [6 ]departmentMaastricht University Library , Maastricht University , Maastricht, The Netherlands
                [7 ]departmentSchool of Mental Health and Neuroscience (MHeNS) , Maastricht University , Maastricht, The Netherlands
                [8 ]departmentDepartment of Research and Development , The Netherlands Comprehensive Cancer Organisation , Utrecht, The Netherlands
                [9 ]De Onderzoekerij , Leiden, The Netherlands
                [10 ]UCB Pharma B.V , Breda, The Netherlands
                [11 ]departmentNUTRIM School of Translational Research in Metabolism, Care and Public Health Research Institute (CAPHRI) , Maastricht University , Maastricht, The Netherlands
                Author notes
                [Correspondence to ] Dr Bart G Pijls; b.g.c.w.pijls@ 123456lumc.nl
                Author information
                http://orcid.org/0000-0001-5351-5057
                http://orcid.org/0000-0002-1580-1543
                Article
                bmjopen-2020-044640
                10.1136/bmjopen-2020-044640
                7802392
                33431495
                2021b287-8506-4d19-8380-c2ad1ae44d52
                © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 08 September 2020
                : 16 November 2020
                : 14 December 2020
                Categories
                Epidemiology
                1506
                2474
                1692
                Original research
                Custom metadata
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                Medicine
                covid-19,infectious diseases,epidemiology
                Medicine
                covid-19, infectious diseases, epidemiology

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