key: cord-0784508-2nnuplkd authors: Wang, Yadong; Feng, Ruo; Xu, Jie; Hou, Hongjie; Feng, Huifen; Yang, Haiyan title: An updated meta‐analysis on the association between tuberculosis and COVID‐19 severity and mortality date: 2021-06-09 journal: J Med Virol DOI: 10.1002/jmv.27119 sha: 35c4d46a366bcd07b0ba018ea26158683b436646 doc_id: 784508 cord_uid: 2nnuplkd OBJECTIVE This study aimed to investigate the association between tuberculosis and coronavirus disease 2019 (COVID-19) severity and mortality based on updated data. METHODS Electronic databases were systematically searched for eligible literatures. The pooled odds ratio (OR) and 95% confidence interval (95% CI) were estimated by a random-effects model. Begg's test, Egger's test and sensitivity analysis were also performed. RESULTS Thirty-six full-text articles with 60,103 COVID-19 patients were included in this study. Overall, we found that COVID-19 patients with tuberculosis tended to have an increased risk for the disease severity compared to those without tuberculosis (OR = 1.56, 95% CI: 1.13 to 2.16). When we restricted the outcomes to mortality, the significant association was still announced (OR = 1.94, 95% CI: 1.28 to 2.93). Sensitivity analysis demonstrated that our results were robust and stable. There was no potential publication bias detected in Begg's test or Egger's test. CONCLUSIONS Our updated meta-analysis demonstrated that tuberculosis was significantly associated with an increased risk for severity and mortality among COVID-19 patients. This article is protected by copyright. All rights reserved. Therefore, we performed this updated meta-analysis to clarify the association between tuberculosis and COVID-19 severity and mortality based on the latest data. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. 2 The electronic databases including PubMed, Web of Science, and EMBASE were systematically searched to identify the eligible studies published between January 1, 2020 and May 14, 2021. The keywords used were: "coronavirus disease 2019", "COVID-19", "severe acute respiratory syndrome coronavirus 2", "SARS-CoV-2", "2019-nCoV", and "tuberculosis". The outcomes of interest were severity (severe, critical, intensive care unit [ICU] admission, invasive mechanical ventilation [IMV], intubation or death), and mortality. All peer-reviewed articles written in the English language reporting the association between tuberculosis and COVID-19 severity and mortality were eligibly included. Accordingly, repeated articles, case reports, review papers, comments, errata, and studies without sufficient data were excluded. The pooled OR and 95% CI were estimated using a random-effects meta-analysis model. 3 Heterogeneity across studies was evaluated using the I 2 statistic. 4 Begg's test were conducted to assess publication bias. [6] [7] [8] Leaveone-out sensitivity analysis was performed to evaluate the stability of our results. 9 The statistical analyses were performed by R software (Version 3.6.3). Statistical significance was defined as p < 0.05. Thirty-six full-text articles with 60,103 COVID-19 patients were included in this study. Among them, 26 studies were from Asia (20 from China, three from Korea, and one each from Qatar, Turkey, and the Philippines), six studies were from Africa (two from Congo, two from South Africa, one from Ethiopia, and one from Nigeria), three studies came from Americas (two from Brazil and one from the United States) and one study was from multi-country. The baseline characteristics of the enrolled studies are summarized in Table 1 . Overall, we found that COVID-19 patients with tuberculosis tended to have an increased risk for the disease severity compared to those without tuberculosis (OR = 1.56, 95% CI: 1.13-2.16, Figure 1A ). When we restricted the outcomes to mortality, the significant association was still present (OR = 1.94, 95% CI: 1.28-2.93, Figure 1B ). Leave-one-out sensitivity analysis demonstrated that omitting each eligible study once had no obvious impacts on the overall results, which suggests that our results were robust and stable ( Figure 1C for severity and 1D for mortality). There was no potential publication bias detected in Begg's test (p = 0.558) or Egger's test (p = 0.293). There are several limitations in this current meta-analysis. First, the majority of the included studies are from Asia, especially from China. Thus, the findings of the present meta-analysis should be verified by future studies mainly from other regions. Second, the information on medications for tuberculosis is not available presently, thus we could not address the effects of medications on the association between tuberculosis and COVID-19 severity and mortality. Third, the association between tuberculosis and COVID-19 severity and mortality was estimated on the basis of crude OR. It is reported that age, gender, and several comorbidities had obvious effects on the clinical outcomes of COVID-19 patients, [10] [11] [12] therefore, a meta-analysis on this association based on risk factors adjusted-effect estimates should be performed to verify our findings in the future. Fourth, most of the included studies (n = 25) were retrospectively designed and only one study was prospectively designed. Therefore, well-designed studies with large sample-sized prospective articles are warranted to verify our findings in the future when more data are available. In conclusion, our updated meta-analysis demonstrated that tuberculosis was significantly associated with an increased risk for severity and mortality among COVID-19 patients. Thus, several preventive measures should be taken to protect individuals with tuberculosis from SARS-CoV-2 infection and more clinical intervention and treatment also should be allocated to COVID-19 patients with tuberculosis to prevent disease progression. We hope that the updated data will contribute to the more accurate elaboration and substantiation of the findings reported by Gao Association between tuberculosis and COVID-19 severity and mortality: a rapid systematic review and meta-analysis Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement Meta-analysis in clinical trials revisited Measuring inconsistency in meta-analyses Correspondence on 'Prevalence and clinical outcomes of COVID-19 in patients with autoimmune diseases: a systematic review and meta-analysis How to perform a meta-analysis with R: a practical tutorial Bias in metaanalysis detected by a simple, graphical test Operating characteristics of a rank correlation test for publication bias Clinical and radiographic outcomes of upper thoracic versus lower thoracic upper instrumented vertebrae for adult scoliosis: a meta-analysis Epidemiology of COVID-19: a systematic review and meta-analysis of clinical characteristics, risk factors, and outcomes The association of cerebrovascular disease with adverse outcomes in COVID-19 patients: a metaanalysis based on adjusted effect estimates The association of hypertension with the severity and mortality of COVID-19 patients: evidence based on adjusted effect estimates We would like to thank Ying Wang, Li Shi, Wenwei Xiao, Xuan Liang, Jian Wu, Peihua Zhang, and Yang Li (All are from the De- The authors declare that there are no conflict of interests. All data relevant to this study are included in this article.