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Indian Journal of Medical Microbiology xxx (xxxx) xxx Contents lists available at ScienceDirect Indian Journal of Medical Microbiology journal homepage: www.journals.elsevier.com/indian-journal-of-medical-microbiology Clinical, epidemiological, laboratory, and radiological characteristics of novel Coronavirus (2019-nCoV) in retrospective studies: A systemic review and meta-analysis Ebrahim Kouhsari a, b, Khalil Azizian c, Mohammad Sholeh d, Mohammad Shayestehpour e, f, Marzieh Hashemian a, Somayeh Karamollahi a, Sajad Yaghoubi g, **, Nourkhoda Sadeghiifard a, * a Clinical Microbiology Research Center, Ilam University of Medical Sciences, Ilam, Iran Laboratory Sciences Research Center, Golestan University of Medical Sciences, Gorgan, Iran c Department of Lab Science, Sirjan School of Medical Sciences, Sirjan, Iran d Department of Microbiology, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran e Department of Microbiology and Immunology, Faculty of Medicine, Kashan University of Medical Sciences, Kashan, Iran f Autoimmune Diseases Research Center, Kashan University of Medical Sciences, Kashan, Iran g Department of Clinical Microbiology, Iranshahr University of Medical Sciences, Iranshahr, Iran b A R T I C L E I N F O A B S T R A C T Keywords: 2019-nCoV Clinical Epidemiological Laboratory, and radiological characteristics Meta-analysis Background: In December 2019, a novel pneumonia related to the 2019 coronavirus unexpectedly developed in Wuhan, China. We aimed to review data of the novel Coronavirus (2019-nCoV) by analyzing all the published retrospective studies on the clinical, epidemiological, laboratory, and radiological characteristics of patients with 2019-nCoV. Methods: We searched in four bibliographic databases PubMed, Scopus, Embase, and Web of Science) for studies March 10, 2020 focused on the clinical, epidemiological, laboratory, and radiological characteristics of patients with 2019-nCoV for meta-analysis. The Newcastle-Ottawa Scale was used to quality assessment, and publication bias was analyzed by Egger's test. In the meta-analysis, a random-effects model with Stata/SE software, v.14.1 (StataCorp, College Station, TX) was used to obtain a pooled incidence rate. Results: Fifty studies were included in this systematic review and meta-analysis with 8815 patients and the mean age was 46 years and 4647 (52.7%) were male. The pooled incidences rate of clinical symptoms were: fever (83%, 95% CI: 0.77, 0.89), cough (59%, 95% CI: 0.48, 0.69), myalgia or fatigue (31%, 95% CI: 0.23, 0.39), sputum production (29%, 95% CI: 0.21, 0.39), and dyspnea (19%, 95% CI: 0.12, 0.26). The pooled incidence rate of acute respiratory distress syndrome (ARDS) was (22%, 95% CI: 0.00, 0.60). Conclusion: The results of this systemic review and meta-analysis present a quantitative pooled incidence rate of different characters of 2019-nCoV and has great potential to develop diagnosis and patient's stratification in 2019nCoV. However, this conclusions of this study still requisite to be warranted by more careful design, larger sample size multivariate studies to corroborate the results of this meta-analysis. 1. Introduction In December 8, 2019 a new coronavirus, which was called 2019 novel coronavirus (2019-nCoV), arise the pneumonia epidemic of the severe respiratory disease from Wuhan (Huanan seafood market) across China which now causes the main public health threats worldwide [1,2]. On January 30, 2020, WHO stated that the epidemic of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) become as a public health emergency of international concern (PHEIC) [3]. Currently, the number of patients with 2019-nCoV is dramatically increasing to other countries around the world [4,5]. According to worldwide statistics, the death rate is ~4.6%. Main symptoms of 2019-nCoV include pneumonia, fever, myalgia or fatigue [4,5]. However, some characterizations and conclusions in the published relevant research were varied, limited and * Corresponding author. Banganjab, Pazhouhesh Blvd, Ilam University of Medical Sciences, Ilam, Iran. ** Corresponding author. Noor St, Shahdai Anonymous Park, Iranshahr School of Medical Sciences, Iranshahr, Iran. E-mail addresses: sajadyaghuby@gmail.com (S. Yaghoubi), Sadeghiifard@gmail.com (N. Sadeghiifard). https://doi.org/10.1016/j.ijmmb.2020.10.004 Available online xxxx 0255-0857/© 2020 Indian Association of Medical Microbiologists. Published by Elsevier B.V. All rights reserved. Please cite this article as: Kouhsari E et al., Clinical, epidemiological, laboratory, and radiological characteristics of novel Coronavirus (2019-nCoV) in retrospective studies: A systemic review and meta-analysis, Indian Journal of Medical Microbiology, https://doi.org/10.1016/j.ijmmb.2020.10.004 E. Kouhsari et al. Indian Journal of Medical Microbiology xxx (xxxx) xxx and the duplicates were removed using EndNote X7 (Thomson Reuters, New York, NY, USA). controversial. At present, there is no successful vaccine or antiviral drugs has been clinically approved for 2019-nCoV. Therefore, to acquire more exact conclusions on the clinical, epidemiological, laboratory, and radiological characteristics and also to propose significant help for current clinical studies of patients with 2019-nCoV, we performed a systemic review and meta-analysis of all these evidence-based medical epidemiological, clinical, laboratory, and radiological characters. 2.2. Selection criteria and data extraction One of the team researchers randomly evaluated the search results and reported that no relevant study was ignored. Three authors (Ebrahim Kouhsari, Mohammad Sholeh and Sajad Yaghoubi) independently done all these steps and reviewed the potentially relevant studies to clarify whether they met the predetermined eligibility criteria. Any discrepancies and inconsistencies with article selection were resolved through discussion, and a fourth author (Nourkhoda Sadeghifard) was available to resolve the disagreement. In the first phase, studies obtained from the literature search were precisely screened by titles and abstracts to exclude irrelevant studies. The full text of relevant studies was reviewed in depth conferring to definite criteria. References lists of all related studies were also reviewed for any other related publication. Studies were excluded if they met the following conditions: reviews, theses, books, conference papers, repeat articles, letters, editorials, expert opinions, animal, in vitro studies, and overlapping, unusable data sets (Fig. 1). Information extracted from retrospective 2. Methods 2.1. Search strategy and study selection Four bibliographic databases, including international databases (PubMed, Scopus, Embase, and Web of Science) for relevant articles were searched (Until 10th/March/2020) by using the following keywords: (”2019 Novel coronavirus” OR “2019-nCoV” OR “Severe Acute Respiratory Syndrome Coronavirus 2” OR “SARS-CoV-2” OR “COVID-19” OR “Wuhan Coronavirus” OR “Wuhan pneumonia”) in the Title/Abstract/ Keywords fields. No limitation regarding ethnicity, language, country, gender, patient age was used while searching databases, but inclusion of the study in our full analysis required at least the abstract to be available in English. The records found through database searching were merged Fig. 1. Flow diagram showing the data selection process. 2 E. Kouhsari et al. Indian Journal of Medical Microbiology xxx (xxxx) xxx points: Moderate quality,  3 points: low quality). Higher score indicates higher study quality. A third reviewer (Ebrahim Kouhsari) adjudicated in any case of disagreement. Need for arbitration and reason was reported in the data collection tool. studies on the clinical, epidemiological, laboratory, and radiological characteristics of novel Coronavirus (2019-nCoV) infected patients (supplementary data 1). 2.3. Outcomes 2.5. Publication bias The main outcome of interest was the clinical, epidemiological, laboratory, and radiological characteristics of 2019-nCoV infected patients. Publication bias was analyzed using Egger's linear regression test, which measures funnel plot asymmetry. 2.4. Quality assessment 2.6. Statistical analysis Quality evaluation of the included studies was performed using by two authors (Marzieh Hashemian, Somayeh Karamollahi) independently, using an adapted version of the tool proposed by the Newcastle-Ottawa assessment scale [6]. A score ranging from 0 to 9 points was attributed to each study (7 points: high quality, 4–6 All statistical analyses were performed using a random-effects model with Stata/SE software, v.14.1 (StataCorp, College Station, TX). A chisquared test and I2 statistic were used to assess the inter-study heterogeneity. Hence, values above 75% are considered heterogeneity [7]; Table 1 Characteristics and Quality assessment of included studies. ID First Author, Year Country Study Design Selection (4 points) Comparability (2 points) Outcome (3 points) Total (9 points) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 Guan W, 2020 Huang Y, 2020 Tang N, 2020 Cai s, 2020 Chen L, 2020 Feng K, 2020 Liu W, 2020 Chen C, 2020 Zhang L, 2020 Tian S, 2020 Bernheim S, 2020 Wu J, 2020 Peng YD 2020 Wang D 2020 Xu H–Y, 2020 Xia W, 2020 Yang W, 2020 Xiong Y,2020 Hu Z,2020 Zhang JJ,2020 Wang D,2020 Walker,2020 Liu K,2020 Yang X,2020 Wang X,2020 Chung M,2020 Li Q,2020 Ki M,2020 Chen N,2020 Fan BE,2020 Chang D,2020 Yao Y,2020 Cheng J,2020 Song F,2020 Zhou S,2020 Yueying P,2020 Liu C,2020 Shi H,2020 Zhao W,2020 Pan F,2020 Huang C,2020 Li YY,2020 Yang HY,2020 Zhu ZW,2020 Ai T,2020 Ling Y,2020 Lan L,2020 Sun,2020 Li J,2020 Xu,2020 China China China China China China China China China China China China China China China China China China China China China Australia China China China China China Korea China China China China China China China China China China China China Chine China China China China China China USA China China retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective retrospective Retrospectively retrospectively retrospectively retrospectively retrospectively retrospectively retrospectively retrospectively retrospectively retrospectively retrospectively retrospectively retrospectively retrospectively 3 3 1 3 3 3 3 2 2 3 3 2 3 3 3 3 2 3 3 2 3 1 3 2 3 3 3 2 2 3 3 2 2 3 3 4 3 3 3 3 3 3 2 3 3 3 3 2 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 3 2 2 2 2 2 2 2 2 2 2 2 2 3 2 2 2 2 2 2 2 1 2 2 2 2 3 3 3 3 2 1 1 3 3 2 2 2 2 2 2 2 1 2 2 2 2 1 1 1 8 7 5 7 7 7 7 6 6 7 7 6 7 8 7 7 6 7 7 6 7 3 7 6 7 7 8 7 7 8 7 5 5 8 8 7 7 7 7 7 7 7 3 7 7 7 7 5 6 6 2 2 2 2 2 2 2 3 E. Kouhsari et al. Indian Journal of Medical Microbiology xxx (xxxx) xxx Table 2 (continued ) Characteristic Value (-CL, þCL) (0.84, 1.00) (0.00, 1.00) (0.01, 0.06) (0.99, 1.00) (0.10, 0.26) (0.01, 0.08) (0.82, 1.00) (0.04, 0.94) (0.67, 1.00) (0.15, 0.96) (0.88, 1.00) (0.10, 0.18) (0.04, 0.13) (0.87, 1.00) (0.02, 0.09) (0.04, 0.45) (0.26, 0.69) (0.54, 0.87) (0.85, 1.00) (0.02, 0.09) (0.04, 0.45) (0.83, 1.00) (0.00, 0.33) (0.00, 0.97) (0.88, 1.00) (0.47, 0.59) (0.18, 0.31) (0.87, 1.00) (0.12, 0.45) (0.02, 0.08) (0.71, 1.00) I2 P Positive Table 2 Meta-analysis results. Number of patients Characteristic Value (-CL, þCL) I2 P Positive Number of patients (0.51, 0.56) (0.44, 0.49) (0.15, 0.42) 68.34 0.00 4647 8815 68.34 0.00 4168 8815 95.94 0.00 328 1289 99.38 0.00 121 277 Epidemiology Male 0.54 * * 7 181 Female 0.46 * * 190 190 0.27 * * 17 99 * * 5 128 93.22 0.00 440 475 99.24 0.00 254 479 Contact with another person with respiratory symptoms History of travel from china (Wuhan, and …) Exposure to source of transmission Smoking history 95.57 0.00 313 368 Admission to ICU 0.16 99.00 0.00 276 461 Diabetes 0.11 94.23 0.00 382 399 Hypertension 0.19 * * 34 248 Malignancy 0.05 * * 11 128 Cardiovascular 0.12 96.48 0.00 559 599 Other comorbidity 0.16 * * 16 99 COPD 0.03 94.02 0.00 72 298 96.21 0.00 211 599 Clinical symptoms Fever 0.83 97.46 0.00 865 1159 Cough 0.59 92.38 0.00 514 541 Myalgia or fatigue 0.31 * * 7 149 Sputum production 0.29 94.02 0.00 38 297 Headache 0.10 95.40 0.00 532 571 Hemoptysis 0.02 95.30 0.00 35 282 Diarrhea 0.08 99.44 0.00 177 420 Dyspnea 0.19 95.81 0.00 502 546 0.22 * * 151 299 Acute respiratory distress syndrome (ARDS) Vomiting * * 47 190 Sore throat 0.12 93.01 0.00 524 563 Rhinorrhea 0.09 93.13 0.00 83 436 Chest pain 0.11 0.00 0.79 14 279 96.86 0.00 528 608 Laboratory WBC(Normal) 0.81 WBC (Decrease) 0.21 (0.18, 0.41) 84.10 0.00 135 449 WBC(Increase) 0.14 0.95 (0.72, 1.00) 97.02 0.00 321 370 Neutrophil (Normal) 0.95 (0.36, 0.95) 98.04 0.00 300 478 (0.73, 0.85) * Neutrophil (Decrease) Neutrophil (Increase) Albumin (Normal) 0.16 0.69 Albumin (Decrease) 0.54 Albumin (Increase) 0.03 Serum Creatinine (Normal) Serum Creatinine (Decrease) Serum Creatinine (Increase) D-Dimer (Normal) 1.00 0.17 0.03 0.94 D-Dimer (Increase) 0.48 Procalcitonin (Normal) Procalcitonin (Increase) Blood Urea nitrogen (Normal) Blood Urea nitrogen (Decrease) Blood Urea nitrogen (Increase) Thromboplastin time (Normal) Thromboplastin time (Decrease) Thromboplastin time (Increase) C-reactive protein (Normal) C-reactive protein (Increase) Total Bilirubin (Normal) Total Bilirubin (Decrease) Total Bilirubin (Increase) Prothrombin time (Normal) Prothrombin time (Decrease) Prothrombin time (Increase) Creatinine (Normal) 0.88 0.60 0.98 0.14 0.08 0.98 0.05 0.20 0.48 0.72 0.95 0.05 0.20 0.95 0.10 0.44 0.98 Creatinine (Decrease) Creatinine (Increase) 0.53 Platelet count (Normal) Platelet count (Decrease) Platelet count (Increase) Aspartate Aminotransferase (Normal) Aspartate Aminotransferase (Increase) Lactate Dehydrogenase (Normal) Lactate Dehydrogenase (Increase) 0.96 0.24 0.27 0.05 0.90 0.29 0.80 * 126 177 0.58 (0.41, 0.73) 99.02 0.00 1917 4208 0.30 (0.16, 0.45) (0.00, 0.53) (0.08, 0.27) (0.08, 0.14) (0.12, 0.27) (0.02, 0.08) (0.06, 0.20) (0.11, 0.22) (0.01, 0.06) 98.51 0.00 719 3583 99.18 0.00 1001 1559 94.70 0.00 175 1843 68.64 0.00 250 2505 94.35 0.00 484 2403 82.12 0.00 72 2250 95.16 0.00 207 2301 75.84 0.00 598 2897 75.84 0.00 48 1900 (0.77, 0.89) (0.48, 0.69) (0.23, 0.39) (0.21, 0.39) (0.06, 0.14) (0.00, 0.05) (0.06, 0.11) (0.12, 0.26) (0.00, 0.60) 95.15 0.00 3273 4370 97.33 0.00 2100 4308 94.28 0.00 1051 3029 84.96 0.00 478 1497 70.94 0.00 306 3557 70.94 0.00 21 1370 80.05 0.00 203 3690 93.99 0.00 495 2651 96.19 0.00 49 173 (0.02, 0.05) (0.07, 0.18) (0.03, 0.17) (0.04, 0.21) 65.12 0.00 105 2961 91.85 0.00 287 2996 87.72 0.00 64 1455 95.44 0.00 108 1834 (0.69, 0.91) (0.16, 0.27) (0.08, 0.21) (0.87, 1.00) (0.12, 0.21) (0.05, 0.34) 95.56 0.00 958 1260 70.65 0.00 180 785 84.85 0.00 109 760 93.15 0.00 721 797 * * 39 229 92.34 0.00 67 380 86.35 0.00 243 259 0.17 0.03 0.17 0.95 (continued on next page) 4 E. Kouhsari et al. Indian Journal of Medical Microbiology xxx (xxxx) xxx Table 2 (continued ) Characteristic Erythrocyte Sedimentation rate (Increase) Alanine Aminotransferase (Normal) Alanine Aminotransferase (Decrease) Alanine Aminotransferase (Increase) Creatine kinase (Normal) Creatine kinase (Decrease) Creatine kinase (Increase) Lymphocyte (Normal) Lymphocyte (Decrease) Lymphocyte (Increase) Hemoglobin (Normal) Hemoglobin (Decrease) Radiology Multiple mottling and ground-glass opacity Bilateral patchy shadowing Crazy paving Table 2 (continued ) Value 0.90 (-CL, þCL) I2 P 92.20 (0.00, 0.05) * 0.18 (0.12, 0.25) 54.18 0.00 65 358 0.94 (0.81, 1.00) (0.12, 0.22) (0.03, 0.24) (0.46, 0.75) (0.40, 0.75) (0.06, 0.24) (0.98, 1.00) (0.95, 1.00) 93.92 0.00 427 467 * * 42 248 85.74 0.00 32 320 93.25 0.00 385 701 97.86 0.00 826 1431 0.00 0.00 9 63 * * 69 69 * * 162 179 0.17 0.12 0.61 0.58 0.14 1.00 0.98 * 459 2 149 95.37 0.00 1399 2951 0.50 (0.44, 0.57) (0.06, 0.29) (0.00, 0.30) (0.45, 0.75) (0.45, 0.75) (0.34, 0.39) (0.24, 0.51) (0.00, 0.02) (0.00, 0.05) (0.59, 0.79) (0.00, 0.05) (0.11, 0.15) (0.04, 0.13) (0.02, 0.09) 40.60 0.17 592 1257 85.09 0.00 47 324 93.19 0.00 15 305 91.16 0.00 327 517 91.16 0.00 61 249 * * 411 1114 94.74 0.00 650 1594 4 141 0.10 Peripheral distribution Unilateral Pneumonia Local patchy shadowing Consolidation 0.61 0.61 0.36 0.37 Cavitation 0.00 Lymphadenopathy 0.02 Bilateral pneumonia 0.70 Pneumothorax 0.01 Interstitial abnormalities Linear 0.13 Pleural effusion 0.05 Supportive treatment Antiviral therapy 0.90 Antibiotic therapy 0.68 Use of corticosteroid 0.32 Immunotherapy 0.39 Oxygen support 0.56 Non-invasive ventilation or 0.11 0.08 (0.74, 0.99) (0.49, 0.84) (0.19, 0.47) (0.13, 0.69) (0.32, 0.78) (0.05, 0.19) Continuous renal replacement therapy Clinical outcomes Recovered Staying in hospital Death Value (-CL, þCL) I2 P Positive Number of patients 0.08 (0.01, 0.19) (0.00, 0.05) 96.06 0.00 88 1643 71.69 0.00 15 576 97.00 0.00 218 339 79.86 0.00 23 361 788 1791 151 2952 2355 3054 0.02 0.55 0.06 0.53 0.67 0.05 (0.24, 0.84) (0.01, 0.13) 98.63 97.93 89.08 0.00 0.00 0.00 Thus, DerSimonian and Laird random effects models were used [8]. All statistical interpretations were reported on a 95% confidence interval (CI) basis. 3. Results (0.50, 0.70) Discrete nodules high-flow nasal canula Invasive mechanical ventilation Invasive mechanical ventilation and ECMO Nasal cannula 500 0.60 0.16 Characteristic Number of patients (0.77, 0.98) 0.01 0.00 Positive 3.1. Search results We evaluated 5 electronic databases and categorized 2095 articles published until 10 March 2020 (Fig. 1). Of these, after initial screening of the title and abstract, 1795 articles were excluded due to their irrelevance and duplication and the full text of remaining 300 articles were reviewed (Fig. 1). Among the 250 articles, were excluded again for specific reasons: case reports, conference papers, repeat articles, letters, editorials, expert opinions, animal, in vitro studies, and unusable data sets. Finally, 50 studies were included in this systematic review and metaanalysis. Supplementary data 1 depicts the main characteristics of 50 included studies. 3.2. Characteristics of studies A total of 50 articles were included in this meta-analysis [2,4,5,9–20], [21–30, 31–55] including data from 8815 patients. Study size ranged from 4 to 1719 subjects. The methodological quality of the included studies was high for observational studies (Table 1). The highest quality of the literature was 8 stars and the lowest 3 stars. 59.24 0.02 18 523 90.99 0.00 1330 1644 * * 1 99 * * 143 1099 * * 12 142 69.66 0.00 39 615 3.4. Epidemiological characteristics 98.61 0.00 1374 2205 97.80 0.00 1094 1806 96.97 0.00 498 2028 98.92 0.00 428 1674 98.95 0.00 1003 2141 93.91 0.00 163 1858 A total of 50 studies including 8815 patients were included in this study, the mean age was 46 years and 4647 (0.54%) were male. Among studies been reported that data on the epidemiological characteristics, evidence of heterogeneity was present in the history contact with another person with respiratory symptoms (I2 ¼ 95.94, P ¼ 0.00), history of travel from China (Wuhan) (I2 ¼ 99.02, P ¼ 0.00), exposure to source of transmission (COVID-19 infected patients, wildlife) within 14 days (I2 ¼ 98.51, P ¼ 0.00), admission to ICU (I2 ¼ 94.70, P ¼ 0.00), smoking history (current or past) (I2 ¼ 99.18, P ¼ 0.00) (Table 2). Among eligible literatures, 26 studies reported that hypertension, diabetes, and cardiovascular illness were more prevalent in patients. Detailed results of Metaanalysis are shown in Table 2. 3.3. Publication bias detection The results of the Egger test are displayed in Table 3. There was a publication bias in the meta-analysis of the bilateral pneumonia group (P ¼ 0.004). 5 E. Kouhsari et al. Indian Journal of Medical Microbiology xxx (xxxx) xxx Table 3 Results of Egger test. Group Fever Cough Myalgia or fatigue Acute respiratory distress syndrome Death COPD Multiple mottling and groundglass opacity Bilateral patchy shadowing Bilateral pneumonia P 0.103 0.054 0.592 0.868 0.197 0.127 0.155 0.238 0.004 There were 13 symptoms of 2019-nCoV in infected patients which were reported. Among studies been reported that data on the clinical symptoms, evidence of heterogeneity was present in the symptoms of fever (I2 ¼ 95.15, P ¼ 0.00), cough (I2 ¼ 97.33, P ¼ 0.00), myalgia or fatigue (I2 ¼ 94.28, P ¼ 0.00), sputum production (I2 ¼ 84.96, P ¼ 0.00), headache or hemoptysis (I2 ¼ 70.94, P ¼ 0.00), and diarrhea (I2 ¼ 80.05, P ¼ 0.00) (Table 2). Among been reported clinical symptoms, the pooled incidence rate was calculated for four symptoms: acute respiratory distress syndrome (ARDS) (22%, 95% CI: 0.00, 0.60), dyspnea (19%, 95% CI: 0.12, 0.26), sore throat (12%, 95% CI: 0.07, 0.18), chest pain (11%, 95% CI: 0.04, 0.21), rhinorrhea (9%, 95% CI: 0.03, 0.17), vomiting (3%, 95% CI: 0.02, 0.05) (Table 2). with antiviral and antimicrobial agents (the pooled incidence rates and heterogeneities were 90%; 68%, I2 ¼ 98.61; 97.80). The pooled incidence rates were 32% and 39% in use of corticosteroids and immunotherapy. Totally, 1510 patients used oxygen therapy. Among these studies, there were 218 patients who used nasal cannula, the pooled incidence was 55% (95% CI: 0.24, 0.84) for five studies. 11% (95% CI: 0.32, 0.78) patients used non-invasive ventilation or high-flow nasal cannula. Additionally, 88 and 15 patients were treated with invasive mechanical ventilation and invasive mechanical ventilation or extra-corporeal membrane oxygenation (ECMO), the pooled incidence were 8% and 2% (Table 2). Three articles had no detailed data on oxygen therapy [12, 55]. There were 23 patients who used continuous renal replacement therapy, the pooled incidence was 6% (95% CI: 0.01, 0.13) for five studies. 3.6. Laboratory characteristics 3.9. Clinical outcomes Among been reported laboratory characteristics, white blood cells were decreased in 180 patients (the pooled incidence rate was 21%, I2 ¼ 70.65, P ¼ 0.00) and increased in 109 patients (the pooled incidence rate was 14%, I2 ¼ 84.85, P ¼ 0.00) (Table 3). Lymphocyte were decreased in 826 patients (the pooled incidence rate was 58%, I2 ¼ 97.86, P ¼ 0.00) and increased in 9 patients (the pooled incidence rate was 14%, I2 ¼ 0.00, P ¼ 0.00) (Table 2). The increased neutrophils observed in 67 patients, evidence of heterogeneity was present in it (I2 ¼ 92.34%, P ¼ 0.00). Albumin were decreased in 121 patients (the pooled incidence rate was 54%, I2 ¼ 99.38, P ¼ 0.00). The D-Dimer and thromboplastin time were increased in 254 and 72 patients (the pooled incidence rates were 48%; 20%, I2 ¼ 99.24; 94.02, P ¼ 0.00). Procalcitonin, C-reactive protein, alanine aminotransferase, aspartate aminotransferase, Lactate Dehydrogenase and creatine kinase were increased in 276, 865, 65, 135, 300 and 32 patients (the pooled incidence rates were 60%, 72%, 18%, 29%, 69% and 12%, P ¼ 0.00) (Table 3). Prothrombin time were decreased in 35 patients (the pooled incidence rate was 10%, I2 ¼ 95.30, P ¼ 0.00) and increased in 177 patients (the pooled incidence rate was 44%, I2 ¼ 99.44, P ¼ 0.00) (Table 2). Among been reported clinical outcomes, unfortunately, 151 died cases were reported, the pooled incidence of mortality was 53% with significant heterogeneity (I2 ¼ 89.08%, P ¼ 0.00). Subsequently the course of treatment of patients is about several weeks until some articles published, some patients still staying in the hospital, the statistics on mortality may be inaccurate. Incidence rate correlation is shown in Table 4. In addition, 1791 and 788 cases were reported as staying in hospital and recovered with significant heterogeneity (I2 ¼ 97.93%; 98.63, P ¼ 0.00) (Table 2). Pooled incidence rate for characters is shown in Fig. 2. 3.5. Clinical characteristics 4. Discussion 2019-nCoV is one type of coronaviruses are enveloped nonsegmented positive-sense RNA viruses belonging to the β-coronavirus cluster like SARS and Middle East respiratory syndrome (MERS) and now it had diseased more than half millions of people worldwide [12, 13,55,56]. It is assumed that 2019-nCoV to be a recombinant virus between bat coronavirus and coronavirus of another unknown origin [57]. Up to now, unfortunately, there is no detailed and precise treatments presented for 2019-nCoV. Symptomatic and supportive treatment is the basis of therapy for patients infected by 2019-nCoV. Our meta-analysis was based on data from 50 retrospective studies in 8815 patients of 2019-nCoV. The Most of the cases were from hospitals in China. Several clinical predictors of mortality were found including increased age, male sex and underlying illness, including hypertension, diabetes, renal disease, heart disease and respiratory disease. In our meta-analysis, the frequency of males more than females (52.7% vs 47.3%). The similar findings with the gender distribution have been reported in MERS and SARS [13,15]. It may be related to the occupational risk factors for males [4]. There are some possible reasons in the reduced susceptibility of females to 2019-nCoV such as Gender-specific effects and X chromosome in infectious disease susceptibility, and their more strong immune responses [58,59]. Although, a recent study that revealed there was no divergence with the gender distribution of males and females between ICU patients and 3.7. Radiological characteristics The radiological characteristics of 2019-nCoV infected patients were described differently. By reviewing the literature, there are different common manifestations as follows: multiple mottling and ground-glass opacity, bilateral pneumonia, consolidation, and bilateral or local patchy shadowing. Among been reported radiological characteristics, evidence of heterogeneity were reported in the multiple mottling and ground-glass opacity (60%, I2 ¼ 95.37, P ¼ 0.00), bilateral pneumonia (70%, I2 ¼ 90.99, P ¼ 0.00), consolidation (37%, I2 ¼ 94.74, P ¼ 0.00), and bilateral patchy shadowing (50%, I2 ¼ 40.60, P ¼ 0.17). Additionally, pneumothorax happened in one patient [13]. 3.8. Treatment Among been reported treatment, 1374, 1094 patients were treated 6 11 8 0.0004 *** Yes 0.0027 ** Yes 0.0311 * Yes 7 19 0.56 0.0002 *** Yes 0.8801 0.5938 to 0.9686 0.7747 0.8951 0.5158 to 0.9810 0.8012 0.7989 0.1152 to 0.9690 0.6383 8 20 30 35 0.0228 * Yes 0.02 * Yes 0.0411 * Yes 0.0003 *** Yes 0.6065 0.3345 0.5784 0.3037 to 0.7643 0.3752 0.01724 to 0.6479 0.1408 0.5155 0.09454 to 0.7801 0.2657 0.7788 0.9578 to 0.1643 0.7483 0.4456 to 0.8975 non-ICU patients [34]. However, we suggest that more investigations are required in order to identify potential risk factors, their relation to different populations, and their mechanisms involved. Older adults and severe patients with comorbidities are as high-risk group to 2019-nCoV [45]. A study performed on influenza illness demonstrated the higher risk of mortality for severe patients with chronic obstructive pulmonary disease (COPD) (OR 1.49, 95% CI: 1.10–2.01), cardiovascular disease (OR 2.92, 95% CI: 1.76–4.86), hypertension (OR 1.49, 95% CI: 1.10–2.10) [60]. The comorbidities effect had also been observed to have similar effects in 2019-nCoV and MERS [61]. Age and comorbidities are major predictors of numerous adverse outcomes in SARS [62]. SARS cases were mostly occurred in younger people; while half of the cases of MERS infection seen in people older than 50 years [63]. Compared with SARS patients, comorbidities, such as diabetes, hypertension, chronic heart disease and chronic pulmonary disease, were more common in MERS cases [64]. Based on to the outcomes of meta-analysis, incidence rates of clinical characteristic includes fever, cough, myalgia or fatigue, and sputum production were 83, 59, 31, and 29% respectively. The incidence of ARDS was 22%, and the case mortality rate of patients with 2019-nCoV infection was 5% which is lower than to SARS and MERS [65]. Several reports propose that pulmonary fibrosis will become one of the severe problems in cases with 2019-nCoV infection [66–68]. How to stop and decrease the incidence of pulmonary fibrosis in cases with 2019-nCoV infection are crucial complications in the treatment of 2019-nCoV [66–68]. Additionally, we observed that hemoptysis, vomiting, diarrhea rhinorrhea, headache chest pain and sore throat are less than occurred in patients with 2019-nCoV. Air-space opacities (unilateral focal and both unilateral multifocal or bilateral involvement) are the key radiological characters in SARS cases [69,70]. Although, ground–glass opacities and consolidation were the most frequent radiological characters in MERS patients [71,72]. Guan W and colleagues [17] observed that the frequent radiographic features were ground-glass opacity (50%) and bilateral patchy shadowing (46%) in 1099 cases with 2019-nCoV infection. Huang C and colleagues [4] reported that the normal radiographic feature of severe patients with 2019-nCoV were bilateral multiple lobular and subsegmental areas of consolidation. The pooled incidences of the bilateral pneumonia multiple mottling and ground-glass opacity bilateral patchy shadowing and consolidation were 70%, 60%, 50%, and 37%. Based on the laboratory characters, the pooled incidence rate of lymphocytes decrease and increase were 58% and 14%. Otherwise, the pooled incidence rate of increasing and decreasing Neutrophils was 17% and 16%. These defects are comparable to those previously detected in cases with MERS and SARS infection [73]. These outcomes more endorse that lymphocytes decrease along with increasing neutrophils was a characteristic of SARS, and 2019-nCoV might primarily effect on lymphocytes, especially T lymphocytes [74]. Additionally, the administration of glucocorticosteroids cause immunosuppression, decreasing the function and/or numbers of lymphocytes, and deregulated lymphocyte responses. Therefore, treatment with glucocorticoids difficult the concern about Lymphopenia [75]. On the other hand, immune insufficiency may be also a risk factor for poor outcome in patients with 2019-nCoV. Currently, outcomes on the death of 2019-nCoV are varying. The recent four reports include 138, 41, 507 and 41 cases, the mortality was 4.3%, 15%, 7.9% and 14.6% respectively [4,34,52,56]. However, the mortality rates of SARS (10%) and MERS (35%) are higher than to 2019-nCoV [76]. In our meta-analysis, the pooled incidence death was 5% respectively. Although, this result higher than the death reported by the previous reports [52,56]. The cause for this occurrence may be related with the absence of identifying information on data, and also deficient data on diagnosis approaches and treatment practices about 2019-nCoV. However, there were also some limitations of our meta-analysis: (1) all reports included had retrospective designed with high statistic heterogeneity (large variation in the sample size among studies; (2) often cases in 0.03390 0.2882 0.0391 * Yes 15 0.5376 0.2383 to 0.7437 0.289 0.0013 ** Yes 33 r 95% confidence interval R squared P value P (two-tailed) P value summary Significant? (alpha ¼ 0.05) Number of XY Pairs 0.5368 0.8228 to Death vs. Fever (37⋅3  C) or (38  C) Death vs. Age mean Death vs. History of travel from china (Wuhan and …) Indian Journal of Medical Microbiology xxx (xxxx) xxx Pearson r Table 4 Summary of Pearson Correlation Coefficient Values between deaths with other variable. Death vs. Cough Death vs. Diarrhea Death vs. thromboplastin time (Increase) Death vs. lymphocyte (Normal) Death vs. Cavitation Death vs. Linear Death vs. Antiviral therapy E. Kouhsari et al. 7 E. Kouhsari et al. Indian Journal of Medical Microbiology xxx (xxxx) xxx Fig. 2. Pooled incidence rate for characters in the study. 8 E. Kouhsari et al. Indian Journal of Medical Microbiology xxx (xxxx) xxx Fig. 2. (continued). 9 E. Kouhsari et al. Indian Journal of Medical Microbiology xxx (xxxx) xxx Fig. 2. (continued). still requisite to be warranted by more careful design, larger sample size multivariate studies to corroborate the results of this meta-analysis. this meta-analysis are Chinese; (3) large variation in lengths of follow-up led to some cases may be still stating in hospital in the included studies. In conclusion, the outcomes of our systemic review and meta-analysis provide a quantitative pooled incidence rate of clinical, epidemiological, laboratory, and radiological features of 2019-nCoV and has great potential to develop diagnosis and patient's stratification in 2019-nCoV. However, this conclusions of this study Source(s) of support None. 10 E. Kouhsari et al. Indian Journal of Medical Microbiology xxx (xxxx) xxx Declaration of competing interest [24] Li Y, Wang W, Lei Y, Zhang B, Yang J, Hu J, et al. Comparison of the clinical characteristics between RNA positive and negative patients clinically diagnosed with 2019 novel coronavirus pneumonia. 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