key: cord-266730-mio282vy authors: Li, Long‐quan; Huang, Tian; Wang, Yong‐qing; Wang, Zheng‐ping; Liang, Yuan; Huang, Tao‐bi; Zhang, Hui‐yun; Sun, Weiming; Wang, Yuping title: COVID‐19 patients' clinical characteristics, discharge rate, and fatality rate of meta‐analysis date: 2020-03-23 journal: J Med Virol DOI: 10.1002/jmv.25757 sha: doc_id: 266730 cord_uid: mio282vy The aim of this study was to analyze the clinical data, discharge rate, and fatality rate of COVID‐19 patients for clinical help. The clinical data of COVID‐19 patients from December 2019 to February 2020 were retrieved from four databases. We statistically analyzed the clinical symptoms and laboratory results of COVID‐19 patients and explained the discharge rate and fatality rate with a single‐arm meta‐analysis. The available data of 1994 patients in 10 literatures were included in our study. The main clinical symptoms of COVID‐19 patients were fever (88.5%), cough (68.6%), myalgia or fatigue (35.8%), expectoration (28.2%), and dyspnea (21.9%). Minor symptoms include headache or dizziness (12.1%), diarrhea (4.8%), nausea and vomiting (3.9%). The results of the laboratory showed that the lymphocytopenia (64.5%), increase of C‐reactive protein (44.3%), increase of lactic dehydrogenase (28.3%), and leukocytopenia (29.4%) were more common. The results of single‐arm meta‐analysis showed that the male took a larger percentage in the gender distribution of COVID‐19 patients 60% (95% CI [0.54, 0.65]), the discharge rate of COVID‐19 patients was 52% (95% CI [0.34,0.70]), and the fatality rate was 5% (95% CI [0.01,0.11]). Data extraction and the evaluation of literature quality were conducted independently by two investigators (L.Q.L. and T.H.). Microsoft Excel database was used to record all available information, including baseline details, clinic data, discharge rate, and fatality rate. Any disagreement was resolved by another investigator (Y.Q.W.). The MINORS (Table 1) 7 was used to assess bias risk. Microsoft Excel was used to analyze the clinical symptoms and Laboratory results. Single-arm meta-analysis was performed using Stata 15.0 software. Heterogeneity among studies was tested using the Cochran Chi-square test and I 2 , When I 2 < 50%, a fixedeffects model was used, while when I 2 > 50%, a random-effects model was selected. If there was statistical heterogeneity among the results, a further sensitivity analysis was conducted to determine the source of heterogeneity. After the significant clinical heterogeneity was excluded, the randomized effects model was used for meta-analysis. Funnel plot and Egger test were used to detect the publication bias. P < .05 was considered as statistically significant (two-sided). Guan WJ 2 2 2 2 2 0 0 0 10 Chang D 2 2 2 2 2 1 2 0 13 Huang CL 2 2 2 2 2 1 2 0 13 Wang DW 2 2 2 2 2 1 2 0 13 LiQ 2 2 2 2 2 0 0 0 10 Chen NS 2 2 2 2 2 1 1 0 12 Wang ZW 2 2 2 2 2 1 2 0 13 LiuK 2 2 2 2 2 0 0 0 10 Chen L 2 2 2 2 2 1 2 0 13 Zhang MQ 2 2 2 2 2 0 0 0 10 Note: ① A clearly stated aim; ② Inclusion of consecutive patients; ③ Prospective collection of data; ④ Endpoints appropriate to the aim of the study; ⑤ Unbiased assessment of the study endpoint; ⑥ Follow-up period appropriate to the aim of the study; ⑦ Loss to followup less than 5%; ⑧ Prospective calculation of the study size. The items are scored 0 (not reported), 1 (reported but inadequate), or 2 (reported and adequate). The global ideal score being 16 for noncomparative studies. Study ① ② ③ ④ ⑤ ⑥ ⑦ ⑧ Score A total of nine studies were included. [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] The results of the randomized effects model meta-analysis showed that in the sex distribution of this disease men accounted for 60% (95% CI [0.54,0.65]) of COVID-19 patients (Figure 2A) , which was higher than women. The sensitivity analysis (Supporting Information Materials) showed that there was no study that greatly interfered with the results of this meta-analysis, suggesting that the study was stable. A funnel plot was drawn to test the publication bias ( Figure 2B ). Publication bias test results: Egger's test (P = .312 > .1) indicated that there was no publication bias. A total of eight studies were included, [8] [9] [10] [11] [13] [14] [15] [16] with 1560 cases. The results of the random effects model meta-analysis showed that the fatality rate of the COVID-19 patients was 5% (95% CI 15, 27 found that the fatality rate of patients with viral pneumonia increased when they had a basic disease and mixed bacterial infection, which was consistent with the results of our study. Owing to the lack of awareness of the virus in the early stage of this disease, inadequate medical protection, and treatment measures, the high infectivity of the virus led to a dramatic increase in the number of patients, which reflects a lack of medical resources. As a result, the patient discharge rate is relatively low. Recently, it was reported that Remdesivir clinical effect is visible, clinical III trials are ongoing in the domestic, and survivors plasma treatment for heavy, severe cases has shown definite curative effect. 6 We should believe that these treatments will significantly reduce the mortality of such patients soon. Limited by the number and quality of included studies, more extensive and large-scale studies are required to identify the clinical features of the disease. 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SW-m: methodology; ZH-y: validation; LY: formal analysis; HT-b:investigation; WZ-p: data curation; LL-q, HT, and WY-q: original draft preparation; WY-p: writing review and editing. http://orcid.org/0000-0002-6373-2263