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Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: A systematic review and meta-analysis.

ABSTRACT: OBJECTIVE:To better inform efforts to treat and control the current outbreak with a comprehensive characterization of COVID-19. METHODS:We searched PubMed, EMBASE, Web of Science, and CNKI (Chinese Database) for studies published as of March 2, 2020, and we searched references of identified articles. Studies were reviewed for methodological quality. A random-effects model was used to pool results. Heterogeneity was assessed using I2. Publication bias was assessed using Egger's test. RESULTS:43 studies involving 3600 patients were included. Among COVID-19 patients, fever (83.3% [95% CI 78.4-87.7]), cough (60.3% [54.2-66.3]), and fatigue (38.0% [29.8-46.5]) were the most common clinical symptoms. The most common laboratory abnormalities were elevated C-reactive protein (68.6% [58.2-78.2]), decreased lymphocyte count (57.4% [44.8-69.5]) and increased lactate dehydrogenase (51.6% [31.4-71.6]). Ground-glass opacities (80.0% [67.3-90.4]) and bilateral pneumonia (73.2% [63.4-82.1]) were the most frequently reported findings on computed tomography. The overall estimated proportion of severe cases and case-fatality rate (CFR) was 25.6% (17.4-34.9) and 3.6% (1.1-7.2), respectively. CFR and laboratory abnormalities were higher in severe cases, patients from Wuhan, and older patients, but CFR did not differ by gender. CONCLUSIONS:The majority of COVID-19 cases are symptomatic with a moderate CFR. Patients living in Wuhan, older patients, and those with medical comorbidities tend to have more severe clinical symptoms and higher CFR.

SUBMITTER: Fu L

PROVIDER: S-EPMC7151416 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: A systematic review and meta-analysis.

Fu Leiwen L Wang Bingyi B Yuan Tanwei T Chen Xiaoting X Ao Yunlong Y Fitzpatrick Thomas T Li Peiyang P Zhou Yiguo Y Lin Yi-Fan YF Duan Qibin Q Luo Ganfeng G Fan Song S Lu Yong Y Feng Anping A Zhan Yuewei Y Liang Bowen B Cai Weiping W Zhang Lin L Du Xiangjun X Li Linghua L Shu Yuelong Y Zou Huachun H

The Journal of infection 20200410 6

<h4>Objective</h4>To better inform efforts to treat and control the current outbreak with a comprehensive characterization of COVID-19.<h4>Methods</h4>We searched PubMed, EMBASE, Web of Science, and CNKI (Chinese Database) for studies published as of March 2, 2020, and we searched references of identified articles. Studies were reviewed for methodological quality. A random-effects model was used to pool results. Heterogeneity was assessed using I<sup>2</sup>. Publication bias was assessed using ...[more]

PMID: 32283155

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Project description:Importance: Coronavirus disease 2019 (COVID-19) is a newly emerging infectious disease that has caused a global pandemic. The presenting symptoms are mainly respiratory symptom, yet studies have reported nervous system involvement in the disease. A systematic review and meta-analysis of these studies are required to understanding the neurologic characteristic of the disease and help physicians with early diagnosis and management. Objective: To conduct a systematic review and meta-analysis on the neurologic characteristics in patients with COVID-19. Evidence Review: Authors conducted a literature search through PubMed from January 1st, 2020 to April 8th, 2020. Furthermore, the authors added additional sources by reviewing related references. Studies presenting the neurologic features of COVID-19 patients in their data were included. Case reports and case series were also included in this review. The quality of the studies was assessed based on the Oxford Center for Evidence-Based Medicine guidelines. Selected studies were included in the meta-analysis of proportion and the heterogeneity test. Finding: From 280 identified studies, 33 were eligible, with 7,559 participants included. Most of the included studies were from China (29 [88%]). Muscle injury or myalgia was the most common (19.2%, 95%CI 15.4-23.2%) neurologic symptom of COVID-19, followed by headache (10.9%, 95%CI 8.62-13.51%); dizziness (8.7%, 95%CI 5.02-13.43%); nausea with or without vomiting (4.6%, 95%CI 3.17-6.27%); concurrent cerebrovascular disease (4.4%, 95%CI 1.92-7.91%); and impaired consciousness (3.8%, 95%CI 0.16-12.04%). Underlying cerebrovascular disease was found in 8.5% (95%CI 4.5-13.5%) of the studies. Conclusion: Neurologic findings vary from non-specific to specific symptoms in COVID-19 patients. Some severe symptoms or diseases can present in the later stage of the disease. Physicians should be aware of the presence of neurologic signs and symptoms as a chief complaint of COVID-19, in order to improve management and prevent a worsening outcome of the patients.

Project description:Objective:Clinical and laboratory biomarkers to predict the severity of coronavirus disease 2019 (COVID-19) are essential in this pandemic situation of which resource allocation must be urgently prepared especially in the context of respiratory support readiness. Lymphocyte count has been a marker of interest since the first COVID-19 publication. We conducted a systematic review and meta-analysis in order to investigate the association of lymphocyte count on admission and the severity of COVID-19. We would also like to analyze whether patient characteristics such as age and comorbidities affect the relationship between lymphocyte count and COVID-19. Methods:Comprehensive and systematic literature search was performed from PubMed, SCOPUS, EuropePMC, ProQuest, Cochrane Central Databases, and Google Scholar. Research articles in adult patients diagnosed with COVID-19 with information on lymphocyte count and several outcomes of interest, including mortality, acute respiratory distress syndrome (ARDS), intensive care unit (ICU) care, and severe COVID-19, were included in the analysis. Inverse variance method was used to obtain mean differences and its standard deviations. Maentel-Haenszel formula was used to calculate dichotomous variables to obtain odds ratios (ORs) along with its 95% confidence intervals. Random-effect models were used for meta-analysis regardless of heterogeneity. Restricted-maximum likelihood random-effects meta-regression was performed for age, gender, cardiac comorbidity, hypertension, diabetes mellitus, COPD, and smoking. Results:There were a total of 3099 patients from 24 studies. Meta-analysis showed that patients with poor outcome have a lower lymphocyte count (mean difference - 361.06 μL [- 439.18, - 282.95], p < 0.001; I 2 84%) compared to those with good outcome. Subgroup analysis showed lower lymphocyte count in patients who died (mean difference - 395.35 μL [- 165.64, - 625.07], p < 0.001; I 2 87%), experienced ARDS (mean difference - 377.56 μL [- 271.89, - 483.22], p < 0.001; I 2 0%), received ICU care (mean difference - 376.53 μL [- 682.84, - 70.22], p = 0.02; I 2 89%), and have severe COVID-19 (mean difference - 353.34 μL [- 250.94, - 455.73], p < 0.001; I 2 85%). Lymphopenia was associated with severe COVID-19 (OR 3.70 [2.44, 5.63], p < 0.001; I 2 40%). Meta-regression showed that the association between lymphocyte count and composite poor outcome was affected by age (p = 0.034). Conclusion:This meta-analysis showed that lymphopenia on admission was associated with poor outcome in patients with COVID-19.

Project description:BackgroundSince the outbreak of coronavirus disease 2019 (COVID-19), many researchers in China have performed related clinical research. However, systematic reviews of the registered clinical trials are still lacking. Therefore, we conducted a systematic review of clinical trials for COVID-19 to summarize their characteristics.MethodsThis study is based on the PRISMA recommendations in the Cochrane handbook. The Chinese Clinical Registration Center and the ClinicalTrials.gov databases were searched to identify registered clinical trials related to COVID-19. The retrieval inception date was February 9, 2020. Two researchers independently selected the literature based on the inclusion and exclusion criteria, extracted data, and evaluated the risk of bias.ResultsA total of 75 registered clinical trials (63 interventional studies and 12 observational studies) for COVID-19 were identified. The majority of clinical trials were sponsored by Chinese hospitals. Only 11 trials have begun to recruit patients, and none of the registered clinical trials have been completed; 34 trials were early clinical exploratory trials or in the pre-experiment stage, 13 trials were phase III, and four trials were phase IV. The intervention methods included traditional Chinese medicine in 26 trials, Western medicine in 30 trials, and integrated traditional Chinese medicine and Western medicine in 19 trials. The subjects were primarily non-critical adult patients (≥ 18 years old). The median sample size of the trials was 100 (IQR: 60-200), and the median length of the trial periods was 179 d (IQR: 94-366 d). The main outcomes were clinical observation and examinations. Overall, the methodological quality of both the interventional trials and observational studies was low.ConclusionsIntensive clinical trials on the treatment of COVID-19 using traditional Chinese medicine and Western medicine are ongoing or will be performed in China. However, based on the uncertain methodological quality, small sample size, and long trial duration, we will not be able to obtain reliable, high-quality clinical evidence regarding the treatment of COVID-19 in the near future. Improving the quality of study design, prioritizing promising drugs, and using different designs and statistical methods are worth advocating and recommending for clinical trials of COVID-19 in the future.

Project description:BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has caused recurring and major outbreaks in multiple human populations around the world. The plethora of clinical presentations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been described extensively, of which olfactory dysfunction (OD) was established as an important and common extrapulmonary manifestation of COVID-19 infection. The aim of this protocol is to conduct a systematic review and meta-analysis on peer-reviewed articles which described clinical data of OD in COVID-19 patients.MethodsThis research protocol has been prospectively registered with the Prospective Register of Systematic Reviews (PROSPERO; CRD42020196202). CINAHL, ClinicalTrials.gov, Cochrane Central, EMBASE, MEDLINE and PubMed, as well as Chinese medical databases China National Knowledge Infrastructure (CNKI), VIP and WANFANG, will be searched using keywords including 'COVID-19', 'coronavirus disease', '2019-nCoV', 'SARS-CoV-2', 'novel coronavirus', 'anosmia', 'hyposmia', 'loss of smell', and 'olfactory dysfunction'. Systematic review and meta-analysis will be conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and the Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines. Articles will be screened according to pre-specified inclusion and exclusion criteria to extract studies that include new clinical data investigating the effect of COVID-19 on olfactory dysfunction. Included articles will be reviewed in full; data including patient demographics, clinical characteristics of COVID-19-related OD, methods of olfactory assessment and relevant clinical outcomes will be extracted. Statistical analyses will be performed using the Comprehensive Meta-Analysis version 3.DiscussionThis systematic review and meta-analysis protocol will aim to collate and synthesise all available clinical evidence regarding COVID-19-related OD as an important neurosensory dysfunction of COVID-19 infection. A comprehensive search strategy and screening process will be conducted to incorporate broad clinical data for robust statistical analyses and representation. The outcome of the systematic review and meta-analysis will aim to improve our understanding of the symptomatology and clinical characteristics of COVID-19-related OD and identify knowledge gaps in its disease process, which will guide future research in this specific neurosensory defect.Systematic review registrationPROSPERO registration number: CRD42020196202.

Dataset Information

Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: A systematic review and meta-analysis.

Publications

Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: A systematic review and meta-analysis.

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