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BackgroundFollowing blunt trauma, diagnosis of shoulder dislocation based on physical examination alone is difficult due to possible concurrent proximal humeral fractures. X-rays are therefore used to confirm diagnosis. Results from recent observational studies comparing diagnostic accuracy of point-of-care ultrasound (PoCUS) with X-rays for shoulder dislocation have been encouraging. The aim of this study was to determine whether PoCUS improves diagnostic accuracy when used with physical examination for the diagnosis of shoulder dislocation, proximal humeral fracture and ascertaining successful reduction in the ED.MethodsA prospective, single-centre, open, parallel randomised control study over a 6-month period was used to answer the research question and test the null hypothesis. Consecutive eligible adult patients attending the ED of Mater Dei Hospital in Malta were randomised to either the control (C) (physical examination only) or experimental group (E) (physical examination and a two-point PoCUS scan). The study objectives were to measure diagnostic accuracy for both examinations for detecting shoulder dislocation, any associated proximal humeral fractures and confirming reduction. X-rays were used as reference standard for both groups.Results1206 patients were enrolled in this study (C n=600, E n=606). 290 dislocations (C n=132 and E n=158), 332 proximal humeral fractures (C n=154 and E n=178) and 278 reductions (C n=130 and E n=148) were analysed. A statistically significant difference (pConclusionsThe addition of PoCUS to a physical examination significantly improves diagnostic accuracy for dislocations, proximal humeral fractures and reduction confirmation.Trial registration numberInternational Standard Randomised Controlled Trials Number Registry (ISRCTN17048126).

Introduction: Social factors might bring about health inequities. Vulnerable population groups, including those suffering from non-communicable diseases such as type 2 diabetes and depression, might be more prone to suffering the effects of such inequities. This study aimed to identify patients with type 2 diabetes with depression in a primary care setting, with the objective of describing health inequities among urban and suburban dwellers. Methods: A quantitative, retrospective and descriptive study was carried out among patients with diabetes attending public primary healthcare centres in different regions of Malta. Participants completed a self-administered questionnaire to identify patient and disease characteristics. Convenience sampling was used. Results: The logistic regression model predicting the likelihood of different factors occurring with suburban patients with diabetes as opposed to those residing in urban areas contained five independent variables (severity of depression, monthly income, blood capillary glucose readings, weight and nationality). The full model containing all predictors was statistically significant, c2 (5, n=400), p