METHODS: A total of 1028 confirmed cases of COVID-19 from Africa with definite survival outcomes were identified retrospectively from an open-access individual-level worldwide COVID-19 database. The live version of the dataset is available at https://github.com/beoutbreakprepared/nCoV2019 . Multivariable logistic regression was conducted to determine the risk factors that independently predict mortality among patients with COVID-19 in Africa.
RESULTS: Of the 1028 cases included in study, 432 (42.0%) were females with a median (interquartile range, IQR) age of 50 (24) years. Older age (adjusted odds ratio {aOR} 1.06; [95% confidence intervals {95% CI}, 1.04-1.08]), presence of chronic disease (aOR 9.63; [95% CI, 3.84-24.15]), travel history (aOR 2.44; [95% CI, 1.26-4.72]), as well as locations of Central Africa (aOR 0.14; [95% CI, 0.03-0.72]) and West Africa (aOR 0.12; [95% CI, 0.04-0.32]) were identified as the independent risk factors significantly associated with increased mortality among the patients with COVID-19.
CONCLUSIONS: The COVID-19 pandemic is evolving gradually in Africa. Among patients with COVID-19 in Africa, older age, presence of chronic disease, travel history, and the locations of Central Africa and West Africa were associated with increased mortality. A regional response should prioritize strategies that will protect these populations. Also, conducting a further in-depth study could provide more insights into additional factors predictive of mortality in COVID-19 patients.
METHODS AND RESULTS: We estimated the durations of total daily sleep and daytime naps based on the amount of time in bed and self-reported napping time and examined the associations between them and the composite outcome of deaths and major cardiovascular events in 116 632 participants from seven regions. After a median follow-up of 7.8 years, we recorded 4381 deaths and 4365 major cardiovascular events. It showed both shorter (≤6 h/day) and longer (>8 h/day) estimated total sleep durations were associated with an increased risk of the composite outcome when adjusted for age and sex. After adjustment for demographic characteristics, lifestyle behaviours and health status, a J-shaped association was observed. Compared with sleeping 6-8 h/day, those who slept ≤6 h/day had a non-significant trend for increased risk of the composite outcome [hazard ratio (HR), 1.09; 95% confidence interval, 0.99-1.20]. As estimated sleep duration increased, we also noticed a significant trend for a greater risk of the composite outcome [HR of 1.05 (0.99-1.12), 1.17 (1.09-1.25), and 1.41 (1.30-1.53) for 8-9 h/day, 9-10 h/day, and >10 h/day, Ptrend < 0.0001, respectively]. The results were similar for each of all-cause mortality and major cardiovascular events. Daytime nap duration was associated with an increased risk of the composite events in those with over 6 h of nocturnal sleep duration, but not in shorter nocturnal sleepers (≤6 h).
CONCLUSION: Estimated total sleep duration of 6-8 h per day is associated with the lowest risk of deaths and major cardiovascular events. Daytime napping is associated with increased risks of major cardiovascular events and deaths in those with >6 h of nighttime sleep but not in those sleeping ≤6 h/night.
Methods: We adopted a comparative cross-sectional study on pre-clinical medical students who appeared in two different admission tests. The stress, anxiety, and depression levels of students were measured by the depression, anxiety, stress scale (DASS-21), and their burnout level was measured by the Copenhagen Burnout Inventory.
Results: The stress, anxiety, and depression scores between MMI and PI were not significantly different (p-value > 0.05). The personal, work and client burnout scores between MMI and PI were not significantly different (p-value > 0.05). The prevalence of stress (MMI = 39%, PI = 36.9%), anxiety (MMI = 78%, PI = 67.4%), depression (MMI = 41%, PI = 36.2%) and burnout (MMI = 29%, PI = 31.9%) between MMI and PI cohorts was not significantly different (p-value > 0.05). These results showed similar levels of stress, anxiety, depression, and burnout in students at the end of the pre-clinical phase.
Conclusions: This study showed similar psychological health status of the pre-clinical students who were enrolled by two different admission tests. The prevalence of stress, anxiety, burnout, and depression among the pre-clinical medical students was comparable to the global prevalence. The results indicate that medical schools can consider implementing either MMI or PI to recruit suitable candidates for medical training.