key: cord-0975197-j1kluyin authors: Yang, Haiyan; Liang, Xuan; Xu, Jie; Hou, Hongjie; Wang, Yadong title: Meta-analysis of Atrial Fibrillation in Patients with COVID-19 date: 2021-01-27 journal: Am J Cardiol DOI: 10.1016/j.amjcard.2021.01.010 sha: 7ec583bed230275d50a3ee3b4b140e1b772dc84e doc_id: 975197 cord_uid: j1kluyin nan A number of published papers have investigated the relation between atrial fibrillation (AF) and clinical outcomes of patients with coronavirus disease 2019 . However, the conclusions drawn from previous studies are not consistent. For instance, some studies observed that AF was significantly associated with an increased risk of mortality among COVID-19 patients, [1] [2] [3] while several other studies reported opposite results that there was no significant relation between AF and unfavorable outcomes of COVID-19 patients. [4] [5] [6] Several confounding factors such as gender, age and pre-existing medical disorders (diabetes, hypertension, autoimmune diseases, chronic kidney disease and chronic obstructive pulmonary disease, etc.) have been reported to significantly influence the clinical outcomes of COVID-19 patients, 7-13 suggesting that these factors might have significant impacts on the relation between AF and unfavorable outcomes of COVID-19 patients. In this meta-analysis, the pooled effect size was estimated on the basis of adjusted effect estimates reported in published papers. We systematically searched PubMed, Web of Science and EMBASE databases to identify all potential documents published between January 1, 2020 and December 24, 2020, using the following keywords and terms: "severe acute respiratory syndrome coronavirus-2" or "SARS-CoV-2" or "coronavirus disease 2019" or "COVID-19" or "2019 novel coronavirus" or "2019-nCoV" and "atrial fibrillation" and "severity" or "severe" or "critical" or "mortality" or "death" or "fatality" or "intensive care unit" or "mechanical ventilation". Studies were eligibly included if they met the following criteria: (1) studies reporting laboratory-confirmed COVID-19 patients; (2) articles should be peer-reviewed; (3) articles should be published in English; (4) the adjusted effect estimate on the relation between AF and unfavorable outcomes of COVID-19 patients are available. Accordingly, studies were excluded if they were: (1) repeated studies, review papers, comments, errata, protocols and case reports; (2) articles reporting crude effect size; (3) articles with insufficient data; (4) in vitro studies or animal studies. Two investigators independently extracted the basic characteristics including name of authors, country/region, number of cases, percentage of male, age (mean ± standard deviation (SD) or median (interquartile range (IQR))), study design, adjusted effect size and outcomes. In case of disagreement, a third investigator was consulted and made a final decision. Statistical analysis was carried out using Stata 12.1 software. I 2 statistic and Cochran's Q test were adopted in the assessment of heterogeneity among the included studies. The pooled effect size and 95% confidence interval (CI) were calculated to estimate the relation between AF and unfavorable outcomes of COVID-19 patients. A fixed-effects analysis was conducted if there was no heterogeneity (I 2 < 50% or P > 0.1), otherwise, a random-effects analysis was carried out (I 2 > 50% or P < 0.1). Leave-one-out sensitivity analysis was performed to assess the stability of our results. Publication bias was evaluated by Begg's rank correlation test and Egger's linear regression test. Subgroup analysis and meta-regression analysis were also performed to probe the source of heterogeneity. A P-value < 0.05 was deemed statistically significant. Nine hundred and sixteen potentially relevant studies were screened according to the inclusion and exclusion criteria. Finally, 23 studies with 108,745 COVID-19 patients 1-6,14-30 were eligibly included in the present quantitative meta-analysis. The study characteristics are summarized in Table 1 . 10 studies came from USA and 13 studies were from Europe (5 from UK, 4 from Italy, 2 from Spain and 1 each from Denmark and France). Results of our meta-analysis indicated that AF was significantly associated with an increased risk of unfavorable outcomes among COVID-19 patients (pooled effect size = 1.14, 95% CI: 1.03-1.26, P = 0.01; I 2 = 63.9%, random-effects analysis; Figure 1A ). When the clinical outcomes were limited to death, there was still a significant relation between AF and COVID-19 mortality (pooled effect size = 1.13, 95% CI: showed that our results were stable and reliable since omitting each study one by one had no obvious effects on the overall effect size ( Figure 1B) . There was no obvious publication bias assessed by Begg's test (P = 0.428, Figure 1C ) and Egger's test (P = 0.081, Figure 1D ). Meta-regression analysis exhibited that the tested variables such as sample size, age, percentage of male, region, study design and effect estimate might not be the source of heterogeneity (data not shown). In conclusion, our study demonstrates that AF was significantly associated with an increased risk of unfavorable outcomes among COVID-19 patients, especially for death. collecting data, and valuable suggestions for data analysis. 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