There are nearly 500,000 people with undiagnosed diabetes mellitus in the UK. The incidental finding vascular calcification on plain radiographs in patients with undiagnosed diabetes has the potential to alter patient management in those presenting with pathology. We hypothesised that the presence of vascular calcification on plain radiographs of the foot may predict the diagnosis of diabetes. The primary aim of this case control study was to determine the positive predictive value of vascular calcification to diagnose diabetes. Secondary aims were to determine the odds of having diabetes dependent on other known risk factors for calcification. A retrospective case control study of 130 diabetic patients were compared to 130 non-diabetic patients that were matched for age and gender. The presence of vascular calcification in anterior, posterior or plantar vessels, and length of calcification were measured on plain radiographs. McNemar's Chi-squared test and positive predictive values were calculated. Conditional logistic regression models were used to estimate the association between calcification and diabetes.Introduction
Methods
Within the UK, around 70,000 patients suffer neck of femur (NOF) fractures annually. Patients presenting with this injury are often frail, leading to increased morbidity and a 30-day mortality rate of 6.1%. COVID-19 infection has a broad spectrum of clinical presentations with the elderly, and those with pre-existing comorbidities are at a higher risk of severe respiratory compromise and death. Further increased risk has been observed in the postoperative period. The aim of this study was to assess the impact of COVID-19 infection on the complication and mortality rates of NOF fracture patients. All NOF fracture patients presenting between March 2020 and May 2020 were included. Patients were divided into two subgroup: those with or without clinical and/or laboratory diagnosis of COVID-19. Data were collected on patient demographics, pattern of injury, complications, length of stay, and mortality.Aims
Methods
