RESUMO
E-cigarettes have been known to cause varied poor health outcomes prior to coronavirus disease 2019 (COVID-19), but after the impact of COVID-19, evidence came out that was, in some instances, not as expected regarding the severity of COVID-19 among e-cigarette users (vapers). A meta-analysis was performed on the available evidence to comprehensively find the effect of COVID-19 on existing or past e-cigarette users (vapers). The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were used to perform this meta-analysis. PubMed was searched for observational studies that described outcomes after COVID-19 positivity from December 1, 2019, to December 2023. Medical Subject Headings (MeSH) keywords were used for searching the relevant studies highlighting the relationship between COVID-19 and e-cigarette users. Calculations for pooled prevalence, 95% confidence interval (95% CI), weights for current e-cigarette users and vapers, and outcomes (events) were made. To analyze the data, Review Manager V.5.4 was used. The I² statistic was used to assess statistical heterogeneity. The I² statistic of >50% was considered significant heterogeneity. The "leave-one-out" method was used for sensitivity analysis. Out of 3231 studies, four studies reported data on vaping and non-vaping status and composite outcomes, resulting in a sample size of 653 COVID-19-positive cases. The pooled prevalence of being COVID-19 positive, having symptoms, or visiting an emergency room was 7.78% (653/8392). COVID-19 patients with current vaping status had decreased odds of poor outcomes compared to non-smokers, with a pooled odds ratio (OR) of 0.09 (95% CI 0.00-2.42; p>0.05) with heterogeneity between studies (I²=99%, p=0.15). Because of difficulties related to data collection and other factors, this meta-analysis was unable to conclusively establish the correlation between e-cigarette usage and severe COVID-19 outcomes such as hospitalization, admission to the intensive care unit, and fatality. Additional research using more detailed data is necessary to fully understand this correlation.