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.
RESUMO
BACKGROUND: Substance use continues to be on the rise in the United States and has been linked to new onset cardiovascular diseases (CVDs) and cerebrovascular disorders (CeVDs). We aimed to study the association between the types of substance use disorders (SUDs) with specific subtypes of CVDs and CeVDs among hospitalized patients using the National Inpatient Sample (NIS) Database. METHODS: A retrospective study of the NIS database (2016-2017) using the ICD-10-CM codes was performed. The hospitalizations with a secondary diagnosis of SUDs were identified. Weighted univariate analysis using the Chi-square test and multivariate survey logistic regression analysis was performed to evaluate for the incidence, prevalence, and odds of association between vascular events and SUDs. RESULTS: There were a total of 58,259,589 hospitalizations, out of which 21.42% had SUDs. SUDs were more common in the younger age group of 18-50, males, and the lower median household income group. We found a significant association of acute ischemic stroke (AIS) with amphetamine dependence (adjusted odds ratio, aOR 1.23, 95% confidence interval, CI 1.14-1.33), cocaine-related disorders (1.17, 1.12-1.23), and nicotine dependence (1.42, 1.40-1.43). There was a significant association between intracerebral hemorrhage with amphetamine dependence (2.58, 2.26-2.93), cocaine-related disorders (1.62, 1.46-1.79), and alcohol-related disorders (1.35, 1.01-1.82). The association of subarachnoid hemorrhage (SAH) was noted to be higher with amphetamine dependence (1.82, 1.48-2.24) and nicotine dependence (1.47, 1.39-1.55). The patients with nicotine dependence had greater odds of having a myocardial infarction (1.85, 1.83-1.87), those with cocaine-related disorders had higher odds of having angina pectoris (2.21, 1.86-2.62), and patients with alcohol-related disorders had higher odds of developing atrial fibrillation (1.14, 1.11-1.17) in comparison to non-SUDs. CONCLUSION: Our study demonstrates the variability of CVD and CeVD in patients hospitalized for SUD. Findings from our study may help promote increased awareness and early management of these events. Further studies are needed to evaluate the specific effects of frequency and dose on the incidence and prevalence of CVD and CeVD in patients with SUD.