Incidence of severe hypoglycemia and its association with serum adiponectin in Japanese patients with type 1 and insulin-treated type 2 diabetes: The Fukuoka Diabetes Registry

Risk factors and prediction of hypoglycaemia using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials

AIMS/HYPOTHESIS

The objective of the Hypoglycaemia REdefining SOLutions for better liVES (Hypo-RESOLVE) project is to use a dataset of pooled clinical trials across pharmaceutical and device companies in people with type 1 or type 2 diabetes to examine factors associated with incident hypoglycaemia events and to quantify the prediction of these events.

METHODS

Data from 90 trials with 46,254 participants were pooled. Analyses were done for type 1 and type 2 diabetes separately. Poisson mixed models, adjusted for age, sex, diabetes duration and trial identifier were fitted to assess the association of clinical variables with hypoglycaemia event counts. Tree-based gradient-boosting algorithms (XGBoost) were fitted using training data and their predictive performance in terms of area under the receiver operating characteristic curve (AUC) evaluated on test data. Baseline models including age, sex and diabetes duration were compared with models that further included a score of hypoglycaemia in the first 6 weeks from study entry, and full models that included further clinical variables. The relative predictive importance of each covariate was assessed using XGBoost's importance procedure. Prediction across the entire trial duration for each trial (mean of 34.8 weeks for type 1 diabetes and 25.3 weeks for type 2 diabetes) was assessed.

RESULTS

For both type 1 and type 2 diabetes, variables associated with more frequent hypoglycaemia included female sex, white ethnicity, longer diabetes duration, treatment with human as opposed to analogue-only insulin, higher glucose variability, higher score for hypoglycaemia across the 6 week baseline period, lower BP, lower lipid levels and treatment with psychoactive drugs. Prediction of any hypoglycaemia event of any severity was greater than prediction of hypoglycaemia requiring assistance (level 3 hypoglycaemia), for which events were sparser. For prediction of level 1 or worse hypoglycaemia during the whole follow-up period, the AUC was 0.835 (95% CI 0.826, 0.844) in type 1 diabetes and 0.840 (95% CI 0.831, 0.848) in type 2 diabetes. For level 3 hypoglycaemia, the AUC was lower at 0.689 (95% CI 0.667, 0.712) for type 1 diabetes and 0.705 (95% CI 0.662, 0.748) for type 2 diabetes. Compared with the baseline models, almost all the improvement in prediction could be captured by the individual's hypoglycaemia history, glucose variability and blood glucose over a 6 week baseline period.

CONCLUSIONS/INTERPRETATION

Although hypoglycaemia rates show large variation according to sociodemographic and clinical characteristics and treatment history, looking at a 6 week period of hypoglycaemia events and glucose measurements predicts future hypoglycaemia risk.

Risk factors of severe hypoglycemia among patients with type 2 diabetes mellitus in outpatient clinic of tertiary hospital in Indonesia

This study aimed to describe risk factors of severe hypoglycemia in type 2 diabetes mellitus (T2DM) patients in a tertiary care hospital in Indonesia. This study was a retrospective cohort study in the Endocrinology Outpatient Clinic of Dr. Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia. All subjects more than 18 years old who had been visiting the clinic for at least a year were included. Subjects were interviewed whether they had any severe hypoglycemia events within the past year, while data on risk factor variables of severe hypoglycemia was taken from medical records one year before data collection. We recruited 291 subjects, among whom 25.4% suffered at least one episode of severe hypoglycemia within one year. History of severe hypoglycemia (OR 5.864, p ≤ 0.001), eGFR less than 60 mL/min/1.73m2 (OR 1.976, p = 0.028), and insulin use (OR 2.257, p = 0.021) were associated with increased risk of severe hypoglycemia. In conclusion, history of previous severe hypoglycemia, eGFR less than 60 mL/min/1.73m2, and insulin use were associated with severe hypoglycemia.

Novel Insight into the Mechanism of Metabolic Surgery Causing the Diversity in Glycemic Status in Type 2 Diabetes

Metabolic surgery results in diverse glycemic status in patients with type 2 diabetes (T2D), including hyperglycemia without remission, significant amelioration of hyperglycemia with partial remission, complete restoration of euglycemia, or with prolonged remission, hyperglycemia recurrence in relapses after remission, or post-bariatric hypoglycemia. Unfortunately, it is not known how metabolic surgery leads to this diverse consequence. Here, we discuss the diversity of glycemic status associated with metabolic surgery and the potential mechanisms of T2D remission. We also highlight the relationship between the change in low-grade inflammation and T2D remission after metabolic surgery. We hypothesize that the level of inflammatory and anti-inflammatory cytokines controls the efficacy of metabolic surgery in patients with T2D. This hypothesis may provide further insight into the mechanism of the beneficial effects of metabolic surgery patients with T2D.

Sudden Death Associated with Severe Hypoglycemia in a Diabetic Patient During Sensor-Augmented Pump Therapy with the Predictive Low Glucose Management System

BACKGROUND Hypoglycemia is a frequent complication observed in diabetic patients under treatment. This metabolic complication is associated with an increased mortality rate in diabetic patients. The use of sensor-augmented pump therapy with predictive low glucose management systems has improved blood glucose level control and reduced the incidence of hypoglycemic attacks. However, this therapy may be associated with adverse events. CASE REPORT A 65-year-old Japanese woman with type 1 diabetes mellitus underwent hemodialysis with end-stage renal failure due to diabetic nephropathy. The patient received sensor-augmented pump therapy with the predictive low glucose management system to prevent recurrent severe hypoglycemia. Hypoglycemia was infrequent when the sensor-augmented pump therapy with a predictive low-glucose management system was properly working. However, the patient suddenly died 3 months after starting the treatment. A record of continuous glucose monitoring showed that hypoglycemia occurred before the sudden death of the patient. CONCLUSIONS The current case shows that sudden death associated with severe hypoglycemia may also occur during sensor-augmented pump therapy with a predictive low glucose management system. This case report underscores the need for close follow-up of diabetic patients receiving sensor-augmented pump therapy with the predictive low glucose management system and the critical importance of patient education on diabetes technology in high-risk patients.