ABSTRACT
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.
ABSTRACT
Introduction Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with multisystemic involvement. The clinical presentation and immunological findings of SLE patients from different regions in Saudi Arabia have been studied. There have been no studies on the clinical manifestations of SLE in patients in Saudi Arabia's southern region. This article aims to explore the clinical manifestations of SLE in a tertiary center in the southern region of Saudi Arabia. Methods A retrospective study was carried out on 108 SLE patients who were seen in the rheumatology clinic at Aseer Central Hospital over six months from January 2022 to June 2022. Patients' demographics, clinical and serological characteristics, and therapeutic data were reviewed. Results The male-to-female ratio was 1:12.5, with a mean age at presentation of 28.6 ± 10 years. The mean disease duration was 9.06 ± 5.96 years. Mucocutaneous and musculoskeletal manifestations were the most common, accounting for 76% and 57% of all cases, respectively. Neuropsychiatric involvement and lupus nephritis were present in 29% and 31% of patients, respectively. The hematological abnormalities that were present included anemia (60%), leukopenia (37%), and thrombocytopenia (15%). Antinuclear antibody (ANA) was detected in 100%, anti-double-stranded DNA (anti-dsDNA) antibody in 55%, anti-Smith antibody in 13%, and hypocomplementemia in 52% of patients. Hydroxychloroquine was received by 98% and oral steroids by 41% of the patients. Other drugs include azathioprine (23%), mycophenolate mofetil (15%), methotrexate (23%), belimumab (9%), cyclophosphamide (10%), and rituximab (6%). Conclusion The main clinical features of our patients were in parallel with previous studies in Saudi Arabia as well as in Arab countries. We found a lower prevalence of lupus nephritis, serositis, and anti-dsDNA antibody. Further multicenter studies are required to investigate the long-term outcome and survival of SLE patients.
