Prevalence and management of diabetes among the uninsured: A multicenter study in Tampa Bay, FL.

AIMS: This study describes the prevalence and management of uninsured patients with diabetes in free clinics around the Tampa Bay area. METHODS: A retrospective chart review collected data from uninsured patients who visited nine free clinics from January 2016 to December 2017. The data included sociodemographics, chronic disease diagnoses and treatments, and social history. Statistical analysis including chi-square tests and logistic regression were used to describe patients with diabetes. RESULTS: With a prevalence of 19.41% among 6815 uninsured patients and a mean HbA1c of 7.9% (63 mmol/mol), patients with diabetes were more likely to be White, women, obese, unemployed, and have hypertension and depression compared to patients without diabetes. There were no significant differences in sociodemographic variables between those with controlled and uncontrolled diabetes. Among the variables studied by logistic regression, unemployment was found to be a significant predictor of poor glycemic control among men. CONCLUSIONS: Diabetes is a challenging chronic disease among the uninsured of Tampa Bay due to its prevalence and suboptimal glycemic control. Obesity and unemployment represent significant challenges that increase the burden of diabetes among the uninsured. Free clinics may benefit from additional resources and intervention programs, with future research assessing their effects on care outcomes

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population.The aim of this study was to inform vaccination prioritization by modelling the impact of vaccination on elective inpatient surgery. The study found that patients aged at least 70 years needing elective surgery should be prioritized alongside other high-risk groups during early vaccination programmes. Once vaccines are rolled out to younger populations, prioritizing surgical patients is advantageous