Publications by authors named "Mostafa Rezai-Tavirani"

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Gastrointestinal symptoms in patients with mild and severe COVID-19: a scoping review and meta-analysis.

Gastroenterol Hepatol Bed Bench 2020 ;13(4):321-330

Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Aim: The current research aimed to analyze and summarize observational studies that compared the incidence of gastrointestinal symptoms in mild and severe COVID-19 infection.

Background: Coronavirus disease 2019 (COVID-19) has been identified as a public health threat worldwide. Previous studies, however, have reported contradictory results of COVID-19-related gastrointestinal symptoms in severe and mild forms.

Methods: A search of Medline, ISI Web of Science, EMBASE, and Cochrane Library databases was conducted for articles published up to May 2020. Data from each study was combined using the random-effects model to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs). Sensitivity was examined by sequentially excluding one study in each turn. Publication bias was evaluated using the Egger's and Begg's tests.

Results: Twenty studies (4,265 patients) were reviewed. It was found that the prevalence of diarrhea [OR (0.40), (95% CI 0.91, -2.16), p = 0.03, I2 = 88.1%, PHeterogenity = 0.00)] and nausea and vomiting [OR (0.27), (95% CI 0.07, 1.01), p = 0.05, I2 = 89.3%, PHeterogenity = 0.00)] increased significantly in the severe form compared to the mild form of COVID-19, while abdominal pain and anorexia had no significant increased prevalence in admitted and hospitalized COVID-19 patients. Moreover, COVID-19-related gastrointestinal symptoms were seen in higher rates in males [OR (1.42), (95% CI 1.23, 1.65), p < 0.05, I2= 18.4%, PHeterogenity = 0.23] than in females. No significant publication bias was observed in the meta-analysis. Sensitivity analyses showed a similar effect size while reducing the heterogeneity.

Conclusion: The data provides valuable information for the discovery of prognosis biomarkers to diagnosis more severe disease in the early stages of COVID-19.
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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682965PMC
January 2020