RESUMO
Diabetes mellitus, a condition characterized by dysregulation of blood glucose levels, poses significant health challenges globally. This meta-analysis and systematic review aimed to evaluate the effectiveness of artificial intelligence (AI) in managing diabetes, underpinned by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review scrutinized articles published between January 2019 and February 2024, sourced from six electronic databases: Web of Science, Google Scholar, PubMed, Cochrane Library, EMBASE, and MEDLINE, using keywords such as "Artificial intelligence use in medicine, Diabetes management, Health technology, Machine learning, Diabetic patients, AI applications, and Health informatics." The analysis revealed a notable variance in the prevalence of diabetes symptoms between patients managed with AI models and those receiving standard treatments or other machine learning models, with a risk ratio (RR) of 0.98 (95% CI: 0.88-1.08, I2 = 0%). Sub-group analyses, focusing on symptom detection and management, consistently showed outcomes favoring AI interventions, with RRs of 0.97 (95% CI: 0.87-1.08, I2 = 0%) for symptom detection and 0.97 (95% CI: 0.56-1.57, I2 = 0%) for management, respectively. The findings underscore the potential of AI in enhancing diabetes care, particularly in early disease detection and personalized lifestyle recommendations, addressing the significant health risks associated with diabetes, including increased morbidity and mortality. This study highlights the promising role of AI in revolutionizing diabetes management, advocating for its expanded use in healthcare settings to improve patient outcomes and optimize treatment efficacy.
RESUMO
Background and objectives Burns represents a significant public health issue globally and in Saudi Arabia, disproportionately affecting vulnerable groups. Prompt, evidence-based first aid improves outcomes. This study assessed burn first aid understanding, self-assurance, and information sources among Aseer Region residents. Methods A cross-sectional online survey was distributed to 386 individuals using a validated questionnaire, assessing understanding via a 10-item scale and confidence through Likert scales. Associations between variables were examined statistically. Results Most participants (85%; n=330) demonstrated poor first-aid comprehension, and only (1%; n=2) exhibited excellent knowledge. A history of burn exposure correlated with higher knowledge (p=0.039). The Internet was the primary information source (48%; n= 185). Confidence in assisting burn victims was generally low. Conclusions Significant gaps in foundational burn first aid knowledge were identified, necessitating targeted educational interventions disseminated via multiple modalities to strengthen emergency response and optimize outcomes in this region.