Closing the policy gap in diabetes care for individuals with advanced CKD.

AIM: The co-existence of diabetes and CKD poses significant challenges to healthcare systems, current frameworks often inadequately address the complex needs of individuals with both conditions. Recognising these gaps, we introduced a new diabetes care model for people with advanced CKD in renal satellite units.This paper aims to evaluate this new diabetes model care. METHOD: We conducted a prospective audit of a new integrated diabetes kidney care model. Data were presented as mean ± SD or counts/percentages, and pre- and post-intervention differences were assessed using paired samples t-tests. RESULTS: A total of 291 individuals with diabetes and advanced CKD stages 4 or 5, or undergoing haemodialysis, were included. The mean age was 68.5 (±13.0) years, 58.4% were males. Nearly half of the cohort had four or more long-term conditions, while two-thirds experienced mild/severe frailty. Only 6% were receiving ongoing diabetes care from secondary care diabetes specialist services. For patients with CKD not receiving dialysis, comparing pre- and post-intervention, there were improvements in HbA1c (-13.0 mmol/mol, p < 0.001), SBP (-13.7 mm Hg, p < 0.0001), and weight (-2.9 kg, p < 0.0001). Furthermore, there was an increase in guideline-directed therapies, with notable usage of SGLT2i (62.9%) and GLP1-RA (28.4%), while access to diabetes technology increased to 89%. CONCLUSION: This new model of care resulted in improved metabolic outcomes, increased utilisation of guideline-directed therapies, and enhanced access to diabetes technologies. However, the model also revealed significant unmet clinical needs in areas such as access to diabetes care, diabetes eye screening and foot surveillance.

Burden of impaired awareness of hypoglycemia in people with diabetes undergoing hemodialysis.

INTRODUCTION: Impaired awareness of hypoglycemia (IAH) refers to a diminished capacity to detect hypoglycemia. IAH can result in severe and even life-threatening outcomes for individuals with diabetes, especially those in advanced stages of the disease. This study aimed to assess the prevalence of IAH in people with diabetes on hemodialysis. RESEARCH DESIGN AND METHODS: We conducted a single-center audit to assess the prevalence of IAH using the Clarke questionnaire. Simultaneously, we measured fear of hypoglycemia with an adapted version of the Hypoglycemia Survey and recorded the incidence of severe hypoglycemia. Data were presented as mean±SD or counts/percentages. Logistic regression was then employed to analyze the association between IAH and various sociodemographic and clinical factors. RESULTS: We included 56 participants with diabetes on hemodialysis, with a mean age of 67.2 years (±12.9), of whom 51.8% were male. The ethnic distribution was 23.2% white, 23.2% black, 19.6% Asian, and 33.9% unspecified. The mean HbA1c was 52 mmol/mol (±18.6). The majority (91.1%) had a diagnosis of type 2 diabetes, and 55.4% of those were treated with insulin. The use of diabetes technology was low, with 2.8% of the participants using a continuous glucose monitor. IAH prevalence was 23.2%, and among the 57 participants, 23.6% had a history of severe hypoglycemia, and 60.6% reported fear of hypoglycemia. There were no significant differences in sociodemographic and clinical characteristics between those with IAH and normal hypoglycemia awareness. CONCLUSIONS: We observed that 23.2% of individuals with diabetes undergoing hemodialysis had IAH. IAH was more prevalent in people who reported a fear of hypoglycemia and had a history of severe hypoglycemia episode. The study highlights the unmet needs and disparities in access to diabetes technology within this population.

Glycaemic variability and progression of chronic kidney disease in people with diabetes and comorbid kidney disease: Retrospective cohort study.

AIM: To investigate the association between glycaemic variability and the development of End-Stage-Kidney-Disease (ESKD) among individuals with diabetes and chronic kidney disease. METHODS: A cohort study using UK electronic primary care health records from the Clinical Practice Research Datalink. Glycaemic variability was assessed using a variability score and intra-individual coefficient of variation (CV) of HbA1c. We calculated sub-distribution hazard ratios (sHR) for developing ESKD using competing risk regression analysis. RESULTS: There were 37,222 eligible participants (45.5 % male), with a mean age of 76.4 years (SD ± 9.2), and a mean baseline eGFR 40.7 (±10.7) ml/min/1.73 m2. There were 5,086 incidents of ESKD in the follow-up period. The adjusted sHR (95 %CI) for each variability score group, were as follows: 21-40, 1.38 (1.27-1.50); 41-60, 1.54 (1.41-1.68); 61-80, 1.61 (1.45-1.79); and 81-100, 1.42 (1.19-1.68), compared with the group (score 0-20) with least variability. The adjusted sHR for CV were as follows: 6.7-9.9, 1.29 (1.15-1.45); 10.0-13.9, 1.55 (1.39-1.74); 14.0-20.1, 1.79 (1.60-2.01) and ≥20.2, 2.10 (1.88-2.34) compared to reference group 0-6.6. CONCLUSIONS: Glycaemic variability was strongly associated with the development of ESKD in people with diabetes and CKD.