British Journal of Medical and Health Research

Background: Traumatic spinal injuries (TSI) are a significant cause of morbidity, disability, and socioeconomic burden, particularly in low- and middle-income countries where access to specialized care and rehabilitation remains limited. This study evaluated theclinical presentation, injury patterns, and management ofTSI at Moi Teaching and Referral Hospital (MTRH), Eldoret, Kenya. A prospective descriptive study was conducted among 28 patients with TSI recruited Methods: through consecutive sampling. Data collected included demographics, injury mechanisms, anatomical levels, neurological severity, associated injuries, treatment modalities, complications, and functional outcomes. Neurological assessments was performed using the ASIA Impairment Scale. Results : The mean age was 37.9 years (SD 12.4), with males comprising 85.7% of participants. Farmers (25%) and casual labourers (17.9%) were the most represented occupational groups. Falls were the leading mechanism of injury, while the lumbar spine was the most frequently affected region. Most patients (89.3%) had incomplete or no neurological impairment (ASIA D/E). Surgical intervention was performed in 67.9% of patients, with a mean time to surgery of 3.8days (SD3.22). The mean hospitalstay was 12.8days (SD10.9). Conclusion: TSI predominantly affected economically active males, with falls being the leading cause. Strengthening occupational injury prevention, prehospital spinal care, timely referral, and comprehensive rehabilitation services may improve patient management in resource-limited settings. Keywords: Traumatic spinal injuries; Spinal trauma; Neurological impairment; Surgical management;Kenya.

Artificial intelligence (AI) is increasingly influencing modern orthodontic practice by facilitating more precise diagnosis, individualized treatment planning, and improved prediction of treatment outcomes. This review explores the clinical applications of AI in orthodontics, focusing on the contributions of machine learning and deep learning to contemporary diagnostic and therapeutic procedures. AI-driven technologies enable automated interpretation of radiographs, facial photographs, and digital dental models, supporting cephalometric analysis, cervical vertebral maturation assessment, and anatomical landmark identification. Their applications also encompass extraction decision-making, bracket positioning, fixed appliance therapy, clear aligner treatment, and orthognathic surgical planning. In clear aligner therapy, AI facilitates virtual treatment simulation, prediction of tooth movement, optimization of aligner staging, digital fabrication, and remote monitoring of treatment progress. Furthermore, predictive algorithms may assist in evaluating treatment complexity and anticipating postoperative soft tissue changes. Despite these advances, clinical implementation remains constrained by limitations in training data quality, algorithmic bias, generalizability, data security, regulatory frameworks, and implementation costs. Establishing the reliability of AI-based systems requires standardized assessment protocols and robust validation across diverse patient populations. Consequently, AI should currently be integrated as an adjunct to, rather than a substitute for, the clinical judgment and expertise of orthodontists. With continued technological development, rigorous clinical evaluation, and appropriate ethical safeguards, AI has the potential to strengthen evidence-based decision-making and advance efficient, predictable, and patient-centered orthodontic care.

Background: Rheumatoid arthritis is a long-term illness where medicines that change the course of the disease lower inflammation and stop damage from happening while exercise helps with being out of shape, weak muscles, trouble moving and heart problems. It is not clear if medicines that work on the system and exercise together have better results than either one on its own. Methods: This paper uses a way of looking at all the information called a scoping review. It brings together guidelines and published information about medicines, exercise and studies that look at both together. The draft does not say that a full search of all information has been done; the final people who write the paper should do the search check the information and record what they find before they submit it. Results: There is evidence that exercise works with regular care for rheumatoid arthritis especially for heart fitness, muscle strength, how well they can move and parts of feeling good. A study that looked at exercise with medicines found results on how active the disease was: some studies said the combination was better others showed no big difference and the way the studies were done stopped clear conclusions about a good combination. There is not information that is split up by the type of medicine. Exercise should usually go with not take the place of, medicine that tries to get the disease under control. The idea that exercise and the newer medicines work better together needs studies with clear plans for checking this standard ways to plan the exercise and important results that matter to people.