RESUMO
Chest X-ray (CXR) is a common tool used in medical practice. Medical students and interns should acquire knowledge of CXR interpretation, as it is an essential diagnostic tool for a large spectrum of diseases. This systematic review aimed to compare the effect of different intervention techniques on the competency of medical students and interns to demonstrate the level of confidence and competence in interpreting common presentations of CXRs. The population, intervention, comparison, and outcomes (PICO) framework was used to formulate the review question. All related articles in five databases (PubMed, Web of Science, Scopus, Medline, and Embase) were retrieved and the search was completed in March 2023 with no limiters on date and time. The number of relevant studies was 469. A multi-level approach through the Rayyan platform was used for the screening and exclusion processes. Eleven articles were included in the systematic review consisting of eight randomized controlled trials, one quasi-experimental study, one cross-sectional study, and one interventional cohort. Results showed significant effects of teaching methods utilizing deductive or inductive approach, clinical history, patient care comfort survey, and SAFMEDS (Say-All-Fast-Minute-Every-Day-Shuffled). Contrarily, no significant effect was shown by flipped classroom models and mixed and blocked practice, peer-assisted learning vs. expert-assisted learning, and Chester, an artificial intelligence tool. This review identified beneficial approaches that may enhance the learning outcomes of interpreting CXRs for medical students and interns, highlighting the remarkable impact of SAFMEDS on medical students' ability to identify CXR findings as well as the availability and practicality of online and e-learning resources for students.
RESUMO
Background: Coronavirus disease 2019 (COVID-19) is a rapidly spreading infection that is on the rise. New variants are continuously appearing with variable degrees of lethality and infectivity. The extensive work since the start of the pandemic has led to the evolution of COVID-19 vaccines with varying mechanisms. We aim to determine real-world data by looking at the different clinical outcomes associated with COVID-19 vaccination, focusing on the rate of hospitalization, severity, and mortality. Methodology: A retrospective observational study included 624 patients with COVID-19 infection who were hospitalized at King Fahad Hospital of the University and King Fahad Military Medical City between April and July 2021. The cohort was divided into 3 groups: unvaccinated, partially vaccinated (PV), and fully vaccinated (FV). The severity and outcome of COVID-19 disease were compared among the three groups. Among the vaccinated group, we studied the effect of vaccine type on the severity and outcome of COVID-19 disease. Results: We found that 70.4% of patients with COVID-19 disease who required hospitalization were unvaccinated. Un-vaccination was a significant predictor of critical COVID-19 disease (OR 2.31; P <0.001), whereas full vaccination was associated with significantly milder disease severity (OR 0.36; P 0.01). Moreover, un-vaccination status was an independent predictor of longer hospitalization (OR 3.0; P <0.001), a higher requirement for ICU admission (OR 4.7; P <0.001), mechanical ventilation (OR 3.6; P <0.001), and death (OR 4.8; P <0.001), whereas the FV group had a lower risk of ICU admission (OR 0.49; P 0.045). Unvaccinated patients with comorbidities had worse severity and outcome of COVID-19 infection (P<0.05). Both vaccine types (Pfizer and AstraZeneca) had similar protective effects against the worst outcomes of COVID-19 disease. Conclusion: COVID-19 vaccination has been shown to be effective in reducing hospitalization, the severity of COVID-19 infection, and improving outcomes, especially in high-risk group patients. COVID-19 vaccination programs should continue to improve the outcome of such a disease.
