Obesity, cardiovascular risk and healthcare resource utilization in the UK.

AIMS: Obesity and cardiovascular diseases (CVDs) often co-occur, likely increasing the intensity of healthcare resource utilization (HCRU). This retrospective, observational database study examined the joint effect of obesity and cardiovascular risk status on HCRU and compared HCRU between body mass index (BMI) categories and CVD-risk categories in the UK. METHODS: Patient demographics and data on CVD and BMI were obtained from the UK Clinical Practice Research Datalink. Cardiovascular risk status, calculated using the Framingham Risk Equation, was used to categorize people into high-risk and low-risk groups, while a CVD diagnosis was used to define the established CVD group. Patients were split into BMI categories using the standard World Health Organization classifications. For each CVD and BMI category, mean number and costs of general practitioner contacts, hospital admissions and prescriptions were estimated. RESULTS: The final study population included 1,600,709 patients. Data on CVD status were available on just over one-quarter of the sample (28.6%) and BMI data for just less than half (43.2%). The number of general practitioner contacts and prescriptions increased with increasing BMI category for each of the three CVD-risk groups. The group with established CVD had the greatest utilization of all components of healthcare resource, followed by high CVD risk then low CVD-risk groups. CONCLUSION: Increasing BMI category and CVD-risk status both affected several HCRU components. These findings highlight the importance of timely obesity management and treatment of CVD-risk factors as a means of preventing increasing HCRU.

All-Cause and Cardiovascular Mortality Among Insulin-Naïve People With Type 2 Diabetes Treated With Insulin Detemir or Glargine: A Cohort Study in the UK.

INTRODUCTION: Uncontrolled type 2 diabetes (T2D) is associated with an increased risk of micro- and macrovascular complications and mortality. The impact of basal insulins on the risks of mortality and cardiovascular mortality in people with T2D has not been thoroughly investigated in real-world settings. The aim of the present real-word study was to investigate differences in mortality among insulin-naïve people with T2D who initiated insulin detemir (detemir) and insulin glargine (glargine). METHODS: We assessed all-cause and cardiovascular mortality in people with T2D, aged ≥ 40 years and insulin-naïve at treatment initiation. People were identified from the United Kingdom Clinical Practice Research Datalink GOLD national database (2004-2019). Database information included prescribed medications, demographic and clinical variables and mortality. Cause of death was obtained from the Office for National Statistics (ONS). For mortality, 24 clinically relevant confounders were considered and adjusted for using Cox regression analyses. RESULTS: The total cohort included 12,847 people with T2D, including 3031 who commenced detemir and 9816 who commenced glargine. Median age was 66.8 years and median diabetes duration was 7.6 years. From the total cohort, 3231 deaths occurred during follow-up and 6897 people were eligible for linkage to the ONS for cardiovascular mortality data (528 cardiovascular deaths). The adjusted hazard ratio (HR) (95% confidence interval [CI]) was 0.86 (0.79; 0.95) for all-cause mortality and 0.83 (0.67; 1.03) for cardiovascular mortality, in favour of detemir versus glargine. These associations were more pronounced among people with obesity (body mass index ≥ 30 kg/m2), with HRs (95% CI) of 0.79 (0.69; 0.91) and 0.69 (0.50; 0.96) for all-cause and cardiovascular mortality, respectively. CONCLUSION: In this real-world observational study, there was an association between all-cause mortality and basal insulin choice in insulin-naïve people with T2D; the mortality risk was lower with detemir versus glargine after adjustment for potential confounders.

Diabetic retinopathy screening using digital non-mydriatic fundus photography and automated image analysis.

PURPOSE: To investigate the use of automated image analysis for the detection of diabetic retinopathy (DR) in fundus photographs captured with and without pharmacological pupil dilation using a digital non-mydriatic camera. METHODS: A total of 83 patients (165 eyes) with type 1 or type 2 diabetes, representing the full spectrum of DR, were photographed with and without pharmacological pupil dilation using a digital non-mydriatic camera. Two sets of five overlapping, non-stereoscopic, 45-degree field images of each eye were obtained. All images were graded in a masked fashion by two readers according to ETDRS standards and disagreements were settled by an independent adjudicator. Automated detection of red lesions as well as image quality control was made: detection of a single red lesion or insufficient image quality was categorized as possible DR. RESULTS: At patient level, the automated red lesion detection and image quality control combined demonstrated a sensitivity of 89.9% and specificity of 85.7% in detecting DR when used on images captured without pupil dilation, and a sensitivity of 97.0% and specificity of 75.0% when used on images captured with pupil dilation. For moderate non-proliferative or more severe DR the sensitivity was 100% for images captured both with and without pupil dilation. CONCLUSION: Our results demonstrate that the described automated image analysis system, which detects the presence or absence of DR, can be used as a first-step screening tool in DR screening with considerable effectiveness.