Introduction: Tobacco use is one of the most significant risk factors for stroke. Besides traditional cigarettes and combustible products, the use of e-cigarettes and electronic nicotine delivery products has been widespread among young adults in the recent era. Furthermore, the trend of vaping has increased over the last decade. However, the relationship between e-cigarettes and stroke is largely unknown. The aim of this study was to evaluate the prevalence and identify the relationship between e-cigarette smoking and stroke. Methods: A cross-sectional study was performed using the NHANES database of the US population. Adults with a history of smoking were considered in our study and divided into three groups, e-cigarette users, traditional, and dual smokers. The Chi-squared test, Wilcoxon rank-sum test, and multivariable logistic regression analysis were used to identify the prevalence and association of e-cigarette consumption and stroke. Results: Out of a total of 266,058 respondents from 2015 to 2018, we found 79,825 respondents who smoked e-cigarettes (9.72%) or traditional (29.37%) or dual smoking (60.91%). Stroke prevalence among e-cigarette smokers was 1.57%. Stroke was more prevalent among traditional smokers than among e-cigarette smokers. (6.75% vs. 1.09%; p < 0.0001) E-cigarette smokers had early onset of stroke in comparison with traditional smokers. (median age: 48 vs. 59 years; p < 0.0001). Among females with stroke, the prevalence of e-cigarette use was higher in comparison with traditional smoking (36.36% vs. 33.91%; p < 0.0001). Among the stroke population, the prevalence of e-cigarette use was higher among Mexican-Americans (21.21% vs. 6.02%) and other Hispanics (24.24% vs. 7.70%) compared with traditional smoking (p < 0.0001). The regression analysis found higher odds of stroke history among e-cigarette users than traditional smokers [aOR: 1.15; 95% CI: 1.15–1.16)]. Conclusion: Though stroke was more prevalent in traditional smokers, the incidence of stroke was early-in-onset and was strongly associated with e-cigarette use compared to traditional smokers. We have also identified vascular effects of e-cigarettes components as possible triggers for the stroke.

Few studies have thoroughly evaluated the neuro-invasive effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which may contribute to a wide range of sequelae from mild long-term effects like headaches and fatigue to severe events like stroke and arrhythmias. Our study aimed to evaluate the long-term neurological effects of coronavirus disease 2019 (COVID-19) among patients discharged from the hospital. In this systematic review and meta-analysis, we assessed the long-term neurocognitive effects of COVID-19. Post-COVID-19 neurological sequelae were defined as persistent symptoms of headache, fatigue, myalgia, anosmia, dysgeusia, sleep disturbance, issues with concentration, post-traumatic stress disorder (PTSD), suicidality, and depression long after the acute phase of COVID-19. Data from observational studies describing post-COVID-19 neurocognitive sequelae and severity of COVID-19 from September 1, 2019, to the present were extracted following the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol with a consensus of three independent reviewers. A systematic review was performed for qualitative evaluation and a meta-analysis was performed for quantitative analysis by calculating log odds of COVID-19 neurocognitive sequelae. The odds ratio (OR) and 95% confidence interval (CI) were obtained and forest plots were created using random effects models. We found seven studies, out of which three were used for quantitative synthesis of evidence. Of the 3,304 post-COVID-19 patients identified, 50.27% were male with a mean age of 56 years; 20.20% had post-COVID-19 symptoms more than two weeks after the acute phase of infection. Among persistence symptoms, neurocognitive symptoms like headache (27.8%), fatigue (26.7%), myalgia (23.14%), anosmia (22.8%), dysgeusia (12.1%), sleep disturbance (63.1%), confusion (32.6%), difficulty to concentrate (22%), and psychiatric symptoms like PTSD (31%), feeling depressed (20%), and suicidality (2%) had a higher prevalence. In meta-analysis, COVID-19 patients with severe symptoms had higher odds of headache (pooled OR: 4.53; 95% CI: 2.37-8.65; p<0.00001; I²: 0%) and myalgia (pooled OR: 3.36; 95% CI: 2.71-4.17; p<0.00001; I²: 0%). Anosmia, fatigue, and dysgeusia had higher but non-significant odds following COVID-19. Although we had sufficient data for headache and fatigue to identify higher rates and associations following COVID-19, we could not establish relationships with other post-COVID-19 neurocognitive séqueles. Long-term follow-up may mitigate the neurocognitive effects among COVID-19 patients as these symptoms are also associated with a poor quality of life.

Background: Upper gastrointestinal hemorrhage (UGIH) and lower gastrointestinal hemorrhage (LGIH) are 2 of the most common reasons for hospital admissions across the United States. The 30-day readmission after index admission poses a major burden on the health care infrastructure, and thus, it is important to assess the causes of 30-day readmission for patients with UGIH and LGIH. Methods: The study cohort was derived from the 2013 National Readmission Database. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) Volume 3 diagnosis codes were utilized to identify UGIH and LGIH patients from this data set. Patients who were readmitted to the hospital within 30 days within the same calendar year were further analyzed. Categorical variables and continuous variables were assessed by the χ² test and the student t test, respectively. The independent predictors of unplanned 30-day readmissions were recognized by multivariate logistic regression, adjusting for stratified cluster design of National Readmission Database. SAS 9.4 (SAS Institute Inc., Cary, NC) was used for data analysis. Results: The number of index admissions identified from the National Readmission Data 2013 were 82,290 for UGIH and 133,114 for LGIH. All-cause 30-day readmission rate for UGIH versus LGIH was 14.6% (readmitted N=12,046; 56.64% age 65 y and above) versus 14.4% (readmitted N=19,128; 70.21% age 65 y and above and 49.61% men). Gastrointestinal causes were most common (33.9% vs. 39.6%), followed by cardiac (13.3% vs. 15.3%), infectious (10.4% vs. 9.1%), and respiratory causes (7.8% vs. 7.1%) for 30-day readmission for UGIH and LGIH. Significant predictors of increased 30-day readmission (odds ratio, 95% confidence interval, P-value) included metastatic disease (2.15, 1.75-2.64, P<0.001), discharge against medical advice (1.85, 1.55-2.22, P3 days (1.50, 1.38-1.63, P<0.001). Predictors for 30-day readmission for LGIH included metastatic disease (1.75, 1.48-2.06, P<0.001), liver disease (1.59, 1.49-1.71, P<0.001), and drug abuse (1.38, 1.21-1.58, P<0.001). Conclusions: Most common reason for UGIH and LGIH readmission was related to gastrointestinal disease, followed by cardiac, infectious, and respiratory etiologies. By addressing these etiologies for readmission, it may be possible to reduce adverse outcomes.