Mortality risk in patients with obesity and COVID-19 infection: a systematic review and meta-analysis.

Obesity is a risk factor for severe respiratory diseases, including COVID-19 infection. Meta-analyses on mortality risk were inconsistent. We systematically searched 3 databases (Medline, Embase, CINAHL) and assessed the quality of studies using the Newcastle-Ottawa tool (CRD42020220140). We included 199 studies from US and Europe, with a mean age of participants 41.8-78.2 years, and a variable prevalence of metabolic co-morbidities of 20-80 %. Exceptionally, one third of the studies had a low prevalence of obesity of <20 %. Compared to patients with normal weight, those with obesity had a 34 % relative increase in the odds of mortality (p-value 0.002), with a dose-dependent relationship. Subgroup analyses showed an interaction with the country income. There was a high heterogeneity in the results, explained by clinical and methodologic variability across studies. We identified one trial only comparing mortality rate in vaccinated compared to unvaccinated patients with obesity; there was a trend for a lower mortality in the former group. Mortality risk in COVID-19 infection increases in parallel to an increase in BMI. BMI should be included in the predictive models and stratification scores used when considering mortality as an outcome in patients with COVID-19 infections. Furthermore, patients with obesity might need to be prioritized for COVID-19 vaccination.

Prevalence of Dry Eye Disease Among Medical Students and Its Association with Sleep Habits, Use of Electronic Devices and Caffeine Consumption: A Cross-Sectional Questionnaire.

Introduction: Dry eye disease (DED) is a common and multifactorial disease of the ocular surface which causes visual disturbance and feelings of discomfort among patients. The prevalence rate among medical students is an important issue to consider. This study investigates the relationship between caffeine consumption, sleeping habits, use of electronic devices, and DED among a convenient sample of medical students in Jordan. Methods: This cross-sectional online survey enrolled medical students from all six medical schools in Jordan. The questionnaire, which was shared via social media platforms, assessed socio-demographics, caffeine consumption amounts and patterns, sleep quality, and the use of electronic devices and their relation to ocular discomfort, DED, and related symptoms. The ocular surface disease index (OSDI) questionnaire was also administered to quantify the symptoms of DED. Results: A total of 1223 students participated in this study (RR=24.46%); 64% were females, and 43% were in their clinical placement years. Of the participants, 317 (25.92%) had normal eyes, and 906 (74.08%) had symptomatic DED. Of the students, 1206 (98.6%) used electronic devices directly before bed, and only 399 (32.62%) used blue-light-protective glasses. Lower DED risk was linked to male gender (OR=0.535, 95% CI 0.392-0.73, p <0.01), clinical years of medical school (OR=0.564, 95% CI 0.424-0.75, p<0.01). Poor sleep quality corresponded to more incidence of DED, regardless of sleeping for 5-6 hours (OR=3.046, 95% CI 1.299-7.139, p=0.01) or for less than 5 hours (OR=3.942, 95% CI 1.824-8.519, p<0.01). Also, caffeine consumption only marginally affected its incidence, but the results were statistically insignificant. Conclusion: Female gender, basic science years, and spending more than 6 hours looking at screens were significantly associated with symptomatic DED. Caffeine consumption did not pose any significant risk to the incidence of DED.

Artificial Intelligence in Medicine: A Multinational Multi-Center Survey on the Medical and Dental Students' Perception.

Background: The emerging field of artificial intelligence (AI) will probably affect the practice for the next generation of doctors. However, the students' views on AI have not been largely investigated. Methods: An anonymous electronic survey on AI was designed for medical and dental students to explore: (1) sources of information about AI, (2) AI applications and concerns, (3) AI status as a topic in medicine, and (4) students' feelings and attitudes. The questionnaire was advertised on social media platforms in 2020. Security measures were employed to prevent fraudulent responses. Mann-Whitney U-test was employed for all comparisons. A sensitivity analysis was also performed by binarizing responses to express disagreement and agreement using the Chi-squared test. Results: Three thousand one hundred thirty-three respondents from 63 countries from all continents were included. Most respondents reported having at least a moderate understanding of the technologies underpinning AI and of their current application, with higher agreement associated with being male (p < 0.0001), tech-savvy (p < 0.0001), pre-clinical student (p < 0.006), and from a developed country (p < 0.04). Students perceive AI as a partner rather than a competitor (72.2%) with a higher agreement for medical students (p = 0.002). The belief that AI will revolutionize medicine and dentistry (83.9%) with greater agreement for students from a developed country (p = 0.0004) was noted. Most students agree that the AI developments will make medicine and dentistry more exciting (69.9%), that AI shall be part of the medical training (85.6%) and they are eager to incorporate AI in their future practice (99%). Conclusion: Currently, AI is a hot topic in medicine and dentistry. Students have a basic understanding of AI principles, a positive attitude toward AI and would like to have it incorporated into their training.