key: cord-0751919-yx8b2moc authors: Zhao, Xianxian; Zhang, Bili; Li, Pan; Ma, Chaoqun; Gu, Jiawei; Hou, Pan; Guo, Zhifu; Wu, Hong; Bai, Yuan title: Incidence, clinical characteristics and prognostic factor of patients with COVID-19: a systematic review and meta-analysis date: 2020-03-20 journal: nan DOI: 10.1101/2020.03.17.20037572 sha: 96227f572ef897844b59b1c8bb6c853b6162c547 doc_id: 751919 cord_uid: yx8b2moc Background: Recently, Coronavirus Disease 2019 (COVID-19) outbreak started in Wuhan, China. Although the clinical features of COVID-19 have been reported previously, data regarding the risk factors associated with the clinical outcomes are lacking. Objectives: To summary and analyze the clinical characteristics and identify the predictors of disease severity and mortality. Methods: The PubMed, Web of Science Core Collection, Embase, Cochrane and MedRxiv databases were searched through February 25, 2020. Meta-analysis of Observational Studies in Epidemiology (MOOSE) recommendations were followed. We extracted and pooled data using random-effects meta-analysis to summary the clinical feature of the confirmed COVID-19 patients, and further identify risk factors for disease severity and death. Heterogeneity was evaluated using the I2 method and explained with subgroup analysis and meta-regression. Results: A total of 30 studies including 53000 patients with COVID-19 were included in this study, the mean age was 49.8 years (95% CI, 47.5-52.2 yrs) and 55.5% were male. The pooled incidence of severity and mortality were 20.2% (95% CI, 15.1-25.2%) and 3.1% (95% CI, 1.9-4.2%), respectively. The predictor for disease severity included old age (≥ 50 yrs, odds ratio [OR] = 2.61; 95% CI, 2.29-2.98), male (OR =1.348, 95% CI, 1.195-1.521), smoking (OR =1.734, 95% CI, 1.146-2.626) and any comorbidity (OR = 2.635, 95% CI, 2.098-3.309), especially chronic kidney disease (CKD, OR = 6.017; 95% CI, 2.192-16.514), chronic obstructive pulmonary disease (COPD, OR = 5.323; 95% CI, 2.613-10.847) and cerebrovascular disease (OR = 3.219; 95% CI, 1.486-6.972). In terms of laboratory results, increased lactate dehydrogenase (LDH), C-reactive protein (CRP) and D-dimer and decreased blood platelet and lymphocytes count were highly associated with severe COVID-19 (all for P < 0.001). Meanwhile, old age (≥ 60 yrs, RR = 9.45; 95% CI, 8.09-11.04), followed by cardiovascular disease (RR = 6.75; 95% CI, 5.40-8.43) hypertension (RR = 4.48; 95% CI, 3.69-5.45) and diabetes (RR = 4.43; 95% CI, 3.49-5.61) were found to be independent prognostic factors for the COVID-19 related death. Conclusions: To our knowledge, this is the first evidence-based medicine research to explore the risk factors of prognosis in patients with COVID-19, which is helpful to identify early-stage patients with poor prognosis and adapt effective treatment. Coronaviruses are a family of viruses that widely exist in nature and can infect both humans and animals 1 Compared with two other types of coronaviruses, the present new coronavirus is spreading far more quickly and has higher contagiousness 5 . visualized the results with forest plots. Secondly, to identify the risk factors for severity, pooled odds ratios (ORs) with 95% CIs were estimated with the dichotomous method, and mean difference (MD) with 95% CIs between severe and non-severe cases were calculated with continuous method, Fixed effects model was used when I² < 50%, and random effects models otherwise. Regarding the COVID-19 related death, we conducted logistic regression model to calculate relative risks (RR) with 95% CIs using the data of Chinese Center for Disease Control, which included 44672 laboratory confirmed patients. Thirdly, to explore potential sources of heterogeneity, we conducted subgroup analysis and random-e ects meta-regression. Variables significant in univariable meta-regression (P < 0.05) were included in multivariable meta-regression. Next, sensitivity analyses were performed by systematically removing each study in turn to explore its effect on outcome 13 . Finally, to investigate the risk of publication bias, we applied the Begger test, Egger test and the test used by Peters et al and visually inspected the funnel plots 14 . All analyses were performed using Review We identified 854 studies, of which 30 were eligible for our analysis including 53,000 COVID-19 confirmed patients ( Figure 1 ) 1, 7, . All of them were retrospective, observational studies (19 single-center and 11 multi-center studies), which were performed between December 2019 and February 19, 2020. The majority of studies were conducted in Wuhan (13, 43 .3%) and other cities in China (11, 36 .7%), 2 from nationwide and 3 from other countries including United States, Australia and Korea. To avoid any overlap of cases, the nationwide study of Chinese Centers for Disease Control (CDC) including 44672 confirmed cases was only used for identifying COVID-19 related death risk factors. The male to female sex ratio was 1.25, with an overall average age of 49.8 years (95% CI, 47. 5-52.2) . Five studies included the information of COVID-19 infected medical staff ( Table 1) . 18 studies listed the number of severe cases, with pooled CSR 20.2% (95% CI, 15.1-25.2%, n = 18, I 2 = 92%). The proportion of severe illness in Wuhan subgroup was higher than outside of Wuhan in China (36.9%; [95% CI, .0%]; n = 7 vs. 10.9%; [95% CI, 6.7-15.1%]; n = 7, P < 0.001]). Of note, the overall case fatality rate (CFR) was 3.1% (95% CI, 1.9-4.2%, n = 23, I 2 = 75%). Subgroup analysis showed a significantly higher CFR in Wuhan than outside Wuhan (9.5%; [95% CI, .8%]; n = 10 vs. 0.2%; [95% CI, 0-0.5%]; n = 8, P < 0.001) ( Figure 1 ). All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . Univariate meta-regression showed that compared with Wuhan, CSR and CFR in other areas were significantly lower (all for P < 0.0001), which was consistent with the subgroup analysis. Although not statistically significant, CSR and CFR showed a decreasing trend over time. In addition, onset-to-admission time were identified closely correlation with CSR (4.99% per increase in days, P = 0.0047) and CFR (1.97% per increase in days, P < 0.0001), suggesting shortening the onset-to-admission time favored COVID-19 related outcomes. Multivariate meta-regression confirmed the close correlation between onset-to-admission time and CFR (1.27% per increase in days, P = 0.0263). ( Table 2 and Figure 3 ). Clinical and laboratory data from 26 studies, including 1374 severe and 4326 non-severe patients, were extracted for meta-analysis. Of this, 7.7% patients (95% CI, 3.6-11.8%) were medical staff. The pooled CFR of severe patients was significantly higher than non-severe patients (6.0%; [95% CI, 4.6-7.3%] vs. 0.1%; [95% CI, 0-0.2%], P < 0.001). The mean incubation period was 7.10 days (95% CI, 6.06-8.14 d), with no statistically difference between severe and non-severe cases. The mean time from symptom onset to hospital admission was 6.18 days (95% CI, 5.23-7.12 d), which is longer in severe cases than that in non-severe cases (6.56 d vs. 4.81d, P = 0.023) and in Wuhan than outside (7.23 d vs.4.86 d, All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. whereas digestive symptoms such as diarrhea (5.7%; 95%CI 3.9-7.5%), nausea or vomiting (2.0%; 95% CI, 1.0-2.9%) were relatively rare. The overall prevalence of any comorbidity was 37.1% (95% CI, 28.1-46.1%), with higher incidence rate in severe cases than non-severe cases (54.9% vs. 27.6%, P = 0.006), and higher in Wuhan than other areas (45.1% vs. 28.8%, P = 0.01). The most common comorbidities were hypertension (19.0%, 95% CI, 13.2-24.9%), followed by diabetes (8.2%, 95% CI, 6.3-10.0%) and cardiovascular diseases (CVD, 2.7%, 95% CI, 1.4-4.1%). Moreover, hypertension, diabetes, CVD, cerebrovascular diseases, chronic obstructive pulmonary disease (COPD) and chronic kidney disease (CKD) were significantly more common in severe cases as compared with non-severe cases (all for P < 0.05). The overall proportion of bilateral radiologic abnormalities was 87.2% (95% CI, 82.1-92.3%), with significant difference between inside and outside Wuhan (91.6% vs. 82.6%, P = 0.018). In terms of the laboratory index, several elevated indicators were observed as follows: C-reaction protein (CRP, 26.07 ng/mL). In contrast, the level albumin (37.31 g/L; 95% CI, 34.33-40.28 g/L) and lymphocytes count (1.18 × 10 /L; 95% CI, 1.00-1.36 × 10 /L) were below normal level. Of note, obvious differences in laboratory index were identified between severe and non-severe cases, as well as between Wuhan and outside Wuhan. Elevated level of CRP, LDH and D-dimer, together with reduced level of lymphocytes count and PLT count were the prominent features of severe cases (all for P < 0.001). Likewise, more elevated CRP, myoglobin, aspartate aminotransferase (AST) and ferritin, followed by decreased lymphocyte count and hemoglobin were observed in Wuhan patients than outside (all for P < 0.001) ( Table 2) . Among the baseline characteristics, disease severity was highly associated with old age (≥ 50 yrs, OR = 2.609; 95% CI, 2.288-2.976; n = 5; I 2 = 37%), male (OR =1.348; 95% CI, 1.195-1.521; n = 13; I 2 = 0%), smoking (OR =1.734; 95% CI, 1.146-2.626; n = 4; I 2 = 0%) and any All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . comorbidity (OR = 2.635; 95% CI, 2.098-3.309; n = 7; I 2 = 12%). Comorbidities with pooled OR larger than 2 included CKD (6.02; 95% CI, 2.19-16.51; n = 4; I 2 = 0), COPD (5.32; 95% CI, 2.61-10.85; n = 6; I 2 = 0%), cerebrovascular diseases (3.19 ; 95% CI, 1.51-6.77; n = 6; I 2 = 0%), tumor (3.21; 95% CI, 1.42-7.24; n = 4; I 2 = 30%), diabetes (2.49; 95% CI, 1.82-3.4; n = 10; I 2 = 44%) and hypertension (2.06; 95% CI, 1.61-2.62; n = 10; I 2 = 36%) ( Figure 4 , eFigure 5). In terms of laboratory results, there were obvious difference between severe and non-severe cases in PLT (MD = -30.654 Meanwhile, the ORs were calculated for several index including lymphocytopenia (OR = 4.23; 95% CI, 3.03-6.03; I 2 = 33%), thrombocytopenia (OR = 2.84; 95% CI, 2.00-4.04; I 2 = 49%), elevated D-dimer (OR = 3.17; 95% CI, 1.86-5.41; I 2 = 69%) and elevated CRP (OR = 4.23; 95% CI, 2.94-6.08; I 2 = 25%). ( Figure 5 , eFigure 6-7). The most common comorbidity was diabetes for both SARS (24.0%) and All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . MERS (68.0%), while hypertension for COVID-19 (19.0%). Fever and cough were the dominant symptoms for all three viruses, whereas digestive symptoms and chill were relatively rare for COVID-19. Regarding laboratory index, elevated LDH was common for three coronaviruses; higher incidence of lymphopenia, elevated AST or ALT was observed in COVID-19 and SARS than MERS 39,40 . (Table 4 ). Both old age and comorbidity proved the common risk factors for predicting death among three coronaviruses. In support, COVID-19 related death was associated with old age ( ≥ 60 yrs, RR = 9.45; 95% CI, 8.09-11.04), male (RR = 1.67, 95% CI, 1.47-1.89) and any comorbidity (5.86; 95% CI, ), most notably CVD (6.75; 95% CI, 5.40-8.43) followed by hypertension (4.48; 95% CI, ) and diabetes (4.43; 95% CI, ). Similar with COVID-19, male (RR = 1.6; 95% CI, 1.2-2.1) and CVD (OR = 3.5; 95% CI, 3.1-4.8) were also risk factors for MERS related death 41, 42 . In contrast, the most predominant risk factor for SARS related death was CKD (9.02; 95% CI, 3.81-21.36), and the risk of male gender was not statistically significant 3, 43, 44 . In addition, medical staff had a lower fatality rate than non-clinical staff for COVID-19 (RR = 0.12; 95% CI, 0.05-0.30) and MERS (RR = 0.1; 95% CI, 0.02-0.20), whereas the difference was not significant for SARS (RR = 0.76; 95% CI, 0.52-1.15). (Table 5) . All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . Leaving each trial out of the analysis one at a time revealed no meaningful differences in CSR and CFR (eFigure 8 in supplement). We observed no evidence of publication bias with inspection of the funnel plot or with the Begger test or the test used by Peters et al (eFigure 9 in supplement). The main findings of this present analysis are that: (1) Despite the high incidence rate, the distinctive feature of COVID-19 was low severity and mortality, showing a significant difference on the incidence of severity and mortality between Wuhan and outside of Wuhan; (2) The onset-to-admission time was closely related to mortality, which will be increased about 1.27% with every day of delay in admission; (3) SARS-CoV-2 has been reported to be higher contagious than previously discovered human coronaviruses 45 . Until now, more than 187, 361 confirmed cases and caused 7, 485 deaths in 151 countries on six continents were identified. Despite its high prevalence of COVID-19, the All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . pooled severe incidence and fatality rate is significantly lower compared with SARS and MERS, which may explain why the novel coronavirus has spread so widely 46 . Of note, there are regional and spatial differences in the incidence rate of COVID-19. In our research, the pooled severity rate and mortality caused by COVID-19 was found significantly higher in Wuhan than that of the infected outside of Wuhan (all for P < 0.01). On the other hand, disease incidence at the early stage of outbreak was higher than that at the late stage, which may be caused by the lack of recognitions and treatment experience for COVID-19. Moreover, the longer time from symptoms to hospitalization, the higher incidence rate of the mortality related to COVID-19, highlighting the importance of timely medical treatment 30 . In addition, among the patients with 2019-nCoV, the pooled infection rate of medical staff was 7.7%, which was lower than that of SARS (23%) and MERS (9.8%) 39 . high pathogenic coronaviruses, whereas each of which has its own clinical manifestation. In comparison to SARS-CoV (4.6 days) and MERS-CoV (5.2 days) 47 , COVID-19 has a longer latent period (7.1 days) and the initial manifestations are non-specific, making it more difficult to prevent and control at early stage. Similar to SARS and MERS, persons with COVID-19 often present initially with lower respiratory signs, including fever, coughing and fatigue. In the late All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . course of illnesses, infected persons are characterized by progressive breathing difficulty, tachypnea, acute respiratory distress syndrome, or life-threatening complications. In fact, SARS-CoV-2 has been isolated from respiratory secretions, feces, urine, blood, tears, and conjunctival secretions 48 , indicating that SARS-CoV-2 infection is not confined to the respiratory tract. Indeed, in our analysis, the pooled incidences rate of respiratory symptom was present in 79.1% of patients, followed by 7.7% with gastrointestinal disorders and 6.1% with neurological symptoms. Therefore, the patients with COVID-19 whose initial symptom were out of the lung should also be paid more attention, especially for those with the contact history of COVID-19. It should be noted that the pooled incidence of diarrhea symptoms (5.7%) is lower than previous data of patients with MERS-CoV (25%) or SARS-CoV (26%) infection. In terms of laboratory tests, the most common hematological abnormalities in patients with COVID-19 were lymphopenia (54.7%), suggesting aggressive effect on lymphocytes by COVID-19, which is similar to those previously observed in patients with SARS (68-85%). In addition, elevated levels of liver enzymes, LDH, myocardial enzymes, and depressed platelet count concomitant with the rise of D-dimer was observed in our study. Compare with MERS (36%) and SARS (45%), thrombocytopenia was relatively less frequent in patients infected with SARS-CoV-2 (12.8%) 39,47 . All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . Given the fact that the rapid progression to end-organ failure and even death was occurred in some patients, it is therefore essential to paid more attention to susceptible population of COVID-19 49 . Our results showed the majority of the SARS-CoV-2 infection were male patients (55.5%) similarly to the gender distribution of MERS (64.5%), while the predominance of female patients (43.0%) was observed in SARS. It is believed that the sex difference is probably related to the higher expression of ACE2 receptor in male than that in female and the lack of the protection of estrogen and X chromosome 50 . COVID-19 has affected persons in all age groups; in particular, 53.5% patients were found after more than 50 years, suggesting that the elderly patients are more likely to have weak immune function. Moreover, 10-30% of patients in SARS and 37.1% of patients in COVID-19 had at least one underlying disorder; patients with comorbidities such as diabetes mellitus, cardiovascular diseases, renal failure and chronic respiratory diseases are especially vulnerable to SARS-CoV-2 infection 7 . Owning to the pro-inflammatory state and the reduced immune response, the chronic conditions were also noted to have similar effects in the other two coronaviruses. Although the comorbidities identified in our study has been described previously, their value to predict the severity of COVID-19 has not yet been evaluated. A focus on risk factor affecting clinical outcome is critically important to identify high-risk patients and mitigate COVID-19 All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . complications. In the present study, people with old age, male, smoking, presence of comorbidity, CKD, COPD, cancer, hypertension, and diabetes were identified as predictors of severe disease from COVID-19 infection. Importantly, old age, male gender and presence of comorbidity, including hypertension, diabetes, cancer and respiratory disease, were identified predictor of disease severity as well as mortality related to COVID-19, suggesting that elderly patients with these underlying comorbidities should be given more attention and care. In line with previously published studies, the laboratory indicators including lymphocytes, CRP, LDL, PLT, D-dimer, ALT and CK levels were closely related to a poor prognosis, which provided key reference index of the prognosis of COVID-19. In particular, lymphopenia, thrombocytopenia and elevated D-dimer could act as effective predictors of the COVID-19 severity. However, it was worth noting that increased level of myoglobin and ferritin were observed in severe cases, but the predictive value could not be estimated limited by the number of related studies and further in-depth research is needed. Our meta-analysis has several potential limitations. Firstly, there was obvious heterogeneity among studies regarding CSR and its subgroups, because of differences in medical condition, study period, public All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . awareness and others. Nevertheless, we conducted meta-regression based on the observation duration and symptom onset to hospital admission time, which explained a large percent of heterogeneity. Secondly, studies published before February 25, 2020 and articles published in English only were included in our study, therefore there was lack of data from other countries. However, our meta-analysis involved 53000 confirmed patients based on the data during the early-to-mid period of disease outbreak in China, which will provide great referential value for global epidemic control. Thirdly, meta-analysis was conducted on the level of the studies and the characteristics of individual patients could not be retrieved, thus it was hard to provide reference for individualized diagnosis and treatment of COVID-19. Finally, all included studies were retrospective, as no randomized control trials and prospective studies related to 2019-nCoV finish till now, thus our results require to be confirmed by more high-quality clinical researches. COVID-19 is emerging all over the world and spreading at an unprecedented rate, resulting in significant impacts on global economies and public health. The present study successfully and systematically evaluated the prognostic predictors of COVID-19 by collecting published information on risk factors of the outcomes related to SARS-CoV-2 infections. Nevertheless, more investigations are needed to further All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . 38. COVID-19, Australia: Epidemiology Report 2 (Reporting week All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . Cell 2020. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted March 20, 2020. . https://doi.org /10.1101 /10. /2020 Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia Middle East Respiratory Syndrome The severe acute respiratory syndrome Covid-19: WHO declares pandemic because of "alarming levels" of spread, severity, and inaction Structure, Function, and treatment of COVID-19 Another Decade, Another Coronavirus Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group Prevalence of suicide attempts among Chinese adolescents: A meta-analysis of cross-sectional studies Measuring inconsistency in meta-analyses Improved tests for a random effects meta-regression with a single covariate COPD, chronic obstructive pulmonary disease CKD, chronic kidney disease CLD, chronic liver disease WBC, white blood cell count The ratio of neutrophils to lymphocytes; Hb, hemoglobin; PLT, platelet count; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate PCT, procalcitonin; LDH, lactate dehydrogenase; cTnI, hypersensitive troponin I