Objective: In this study, we utilized a large-scale clinical database to evaluate the relationship between polypharmacy and adverse outcomes among type 2 diabetes patients in rural Montana to inform strategies that improve adherence, reduce preventable complications, and promote equitable diabetes care in underserved regions. Research Design and Methods: 591 patients from the Big Sky Care Connect Database (BSCC) with type 2 diabetes and medication history were stratified into 3 cohorts based on prescribed number of medications: (1-4 medications, non-polypharmic), (5-9 medications, polypharmic), and ([≥]10 medications, hyperpolypharmic). Each cohort was examined for Major Adverse Cardiovascular Events (MACE) and Diabetes Complication Severity Index (DCSI). Descriptive statistics, multivariate logistic regressions, linear regression, and Poisson regression analyses were performed. Results: Medication count was associated with male gender (beta = -2.1341, p < 0.001). Both medication count (IRR 1.06 per additional medication, p < 0.001) and age (IRR 1.03 per year, p < 0.001) were significant predictors of MACE. Neuropathy and nephropathy prevalence was statistically significant (p < 0.001) across patient cohorts and increased with medication count.
Identifying needs in adult rehabilitation to support the clinical implementation of robotics and allied technologies: an Italian national survey
IntroductionRobotics and technological interventions are increasingly being explored as solutions to improve rehabilitation outcomes but their implementation in clinical practice remains very limited. Understanding patient