Hypoglycaemia and its management in primary care setting

How should we differentiate hypoglycaemia in non-diabetic patients?

Hypoglycaemic syndromes are rare in apparently healthy individuals and their diagnosis can be a difficult challenge for clinicians as there are no shared guidelines that suggest how to approach patients with a suspect hypoglycaemic disorder. Since hypoglycaemia symptoms are common and nonspecific, it's necessary to document the Whipple Triad (signs and/or symptoms compatible with hypoglycaemia; relief of symptoms following glucose administration; low plasma glucose levels) before starting any procedure. Once the triad is documented, a meticulous anamnesis and laboratory tests (blood glucose, insulin, proinsulin, C-peptide, β-hydroxybutyrate and anti-insulin antibodies) should be performed. Results can guide the physician towards further specific tests, concerning the suspected disease. In this review, we consider all current causes of hypoglycaemia, including rare diseases such as nesidioblastosis and Hirata's syndrome, describe appropriate tests for diagnosis and suggest strategies to differentiate hypoglycaemia aetiology.

Assessing the impact of body composition, metabolic and oxidative stress parameters on insulin resistance as a prognostic marker for reactive hypoglycemia: a cross-sectional study in overweight, obese, and normal weight individuals

Oxidative stress (OS) plays a pivotal role in the pathogenesis of insulin resistance (IR), particularly in its association with obesity. This study evaluate both the diagnostic and clinical significance of assessing oxidative status in patients affected by overweight and obesity displaying IR, especially with reactive hypoglycemic episodes (RH). A comprehensive examination of OS biomarkers was carried out, encompassing measurements of total oxidative capacity (TOC) and total antioxidant capacity (TAC). Our analysis results reveal noteworthy connections between OS levels and the severity of IR in overweight and obese patients. Moreover, in the study, we demonstrated the diagnostic utility of serum concentrations of TAC and TOC as indicators of the risk of RH, the occurrence of which, even at the stage of overweight, may be associated with increased OS and further development of obesity. Our findings imply that the evaluation of oxidative status could serve as a crucial diagnostic and prognostic tool for patients observed with IR and overweight and obesity. In conclusion, our study underscores the potential utility of assessing oxidative status in the context of IR and highlights the possibility of identifying novel therapeutic targets for the treatment of overweight and obese patients.

Association of Continuous Glucose Monitor Receipt and Diabetes Care Provider Type: A Cohort Study of West Virginia Medicaid Beneficiaries With Type 1 Diabetes

OBJECTIVE

To compare the prevalence of West Virginia Medicaid (WVM) beneficiaries with type 1 diabetes (T1D) with a WVM administrative claim for continuous glucose monitoring (CGM) supplies by whether they received medical care from a board-certified endocrinologist.

METHODS

A total of 1494 WVM beneficiaries aged 20-64 with T1D were retrospectively followed from May 2018 to April 2020. The sample consisted of 2 groups: those receiving medical care from board-certified endocrinologists and those receiving medical care from other providers. CGM prevalence is compared before and after WVM started providing insurance coverage for beneficiaries with T1D to use CGM systems in May 2019 using linear regression with and without adjustments for patient characteristics.

RESULTS

Thirty-five percent of beneficiaries received care from a board-certified endocrinologist at any point during the sample period. Post-May 2019, the prevalence of WVM administrative claims for CGM supplies was significantly higher among beneficiaries receiving care from an endocrinologist compared with other providers.

CONCLUSIONS

Receiving diabetes care from a board-certified endocrinologist is positively associated with having administrative claims for CGM supplies.

Real-World Evidence Supporting Tandem Control-IQ Hybrid Closed-Loop Success in the Medicare and Medicaid Type 1 and Type 2 Diabetes Populations

Background: The Tandem Control-IQ (CIQ) system has demonstrated significant glycemic improvements in large randomized controlled and real-world trials. Use of this system is lower in people with type 1 diabetes (T1D) government-sponsored insurance and those with type 2 diabetes (T2D). This analysis aimed to evaluate the performance of CIQ in these groups. Methods and Materials: A retrospective analysis of CIQ users was performed. Users age ≥6 years with a t:slim X2 Pump and >30 days of continuous glucose monitoring (CGM) data pre-CIQ and >30 days post-CIQ technology initiation were included. Results: A total of 4243 Medicare and 1332 Medicaid CIQ users were analyzed among whom 5075 had T1D and 500 had T2D. After starting CIQ, the Medicare beneficiaries group saw significant improvement in time in target range 70-180 mg/dL (TIR; 64% vs. 74%; P < 0.0001), glucose management index (GMI; 7.3% vs. 7.0%; P < 0.0001), and the percentage of users meeting American Diabetes Association (ADA) CGM Glucometrics Guidelines (12.8% vs. 26.3%; P < 0.0001). The Medicaid group also saw significant improvement in TIR (46% vs. 60%; P < 0.0001), GMI (7.9% vs. 7.5%; P < 0.0001), and percentage meeting ADA guidelines (5.7% vs. 13.4%; P < 0.0001). Patients with T2D and either insurance saw significant glycemic improvements. Conclusions: The CIQ system was effective in the Medicare and Medicaid groups in improving glycemic control. The T2D subgroup also demonstrated improved glycemic control with CIQ use. Glucometrics achieved in this analysis are comparable with those seen in previous randomized controlled clinical trials with the CIQ system.

Effectiveness of Sodium-Glucose Cotransporter-2 Inhibitors vs. Dipeptidyl Peptidase-4 Inhibitors in Frail People With Diabetes Who Were Recently Hospitalized

Introduction: Sodium-glucose cotransporter-2 inhibitors (SGLT-2Is) reduce heart failure (HF) hospitalizations and major adverse cardiovascular events (MACE) in general type 2 diabetes populations. The objective of this study was to determine whether SGLT-2Is vs. dipeptidyl peptidase-4 inhibitors (DPP-4Is) are associated with reductions in MACE, HF hospitalizations and mortality in frail people with type 2 diabetes.

Methods: We conducted a cohort study of all patients aged ≥30 years with type 2 diabetes discharged from a hospital in Victoria, Australia between January 2014 and March 2018 who received SGLT-2Is or DPP-4Is within 60 days of discharge. Follow-up commenced 60 days after initial discharge, and MACE, HF hospitalization and mortality were recorded. Cox proportional hazards regression with competing risks and stabilized inverse probability of treatment weights (IPTWs), was used to generate subdistribution hazard ratios (sHRs) with 95% confidence intervals (CIs). Analyses were stratified into frailty quartiles according to Hospital Frailty Risk Scores (HFRS).

Results: Of the 32,043 patients, (41.9% female and 5.9% ≥80 years) in the cohort, 5,152 (16.1%) received SGLT-2Is. Overall, SGLT-2I versus DPP-4I recipients had lower rates of MACE (sHR 0.51; 95% CI 0.46–0.56), HF hospitalization (sHR 0.42; 95% CI 0.36–0.49) and mortality (HR 0.38; 95% CI 0.33–0.43). People with HFRSs in the fourth quartile who received SGLT-2Is versus DPP-4Is also had reduced rates of MACE (sHR 0.37; 95% CI 0.29–0.46), HF hospitalization (sHR 0.43; 95% CI 0.33–0.56) and mortality (HR 0.32; 95% CI 0.25–0.41).

Conclusion: SGLT-2Is may be preferred to DPP-4Is for preventing MACE, HF hospitalizations and mortality in frail people with type 2 diabetes.

Identifying patients at increased risk of hypoglycaemia in primary care: Development of a machine learning-based screening tool

INTRODUCTION

In primary care, identifying patients with type 2 diabetes (T2D) who are at increased risk of hypoglycaemia is important for the prevention of hypoglycaemic events. We aimed to develop a screening tool based on machine learning to identify such patients using routinely available demographic and medication data.

METHODS

We used a cohort study design and the Groningen Initiative to ANalyse Type 2 diabetes Treatment (GIANTT) medical record database to develop models for hypoglycaemia risk. The first hypoglycaemic event in the observation period (2007-2013) was the outcome. Demographic and medication data were used as predictor variables to train machine learning models. The performance of the models was compared with a model using additional clinical data using fivefold cross validation with the area under the receiver operator characteristic curve (AUC) as a metric.

RESULTS

We included 13,876 T2D patients. The best performing model including only demographic and medication data was logistic regression with least absolute shrinkage and selection operator, with an AUC of 0.71. Ten variables were included (odds ratio): male gender (0.997), age (0.990), total drug count (1.012), glucose-lowering drug count (1.039), sulfonylurea use (1.62), insulin use (1.769), pre-mixed insulin use (1.109), insulin count (1.827), insulin duration (1.193), and antidepressant use (1.05). The proposed model obtained a similar performance to the model using additional clinical data.

CONCLUSION

Using demographic and medication data, a model for identifying patients at increased risk of hypoglycaemia was developed using machine learning. This model can be used as a tool in primary care to screen for patients with T2D who may need additional attention to prevent or reduce hypoglycaemic events.

Hypoglycaemia detection and prediction techniques: A systematic review on the latest developments

The main objective of diabetes control is to correct hyperglycaemia while avoiding hypoglycaemia, especially in insulin-treated patients. Fear of hypoglycaemia is a hurdle to effective correction of hyperglycaemia because it promotes under-dosing of insulin. Strategies to minimise hypoglycaemia include education and training for improved hypoglycaemia awareness and the development of technologies to allow their early detection and thus minimise their occurrence. Patients with impaired hypoglycaemia awareness would benefit the most from these technologies. The purpose of this systematic review is to review currently available or in-development technologies that support detection of hypoglycaemia or hypoglycaemia risk, and identify gaps in the research. Nanomaterial use in sensors is a promising strategy to increase the accuracy of continuous glucose monitoring devices for low glucose values. Hypoglycaemia is associated with changes on vital signs, so electrocardiogram and encephalogram could also be used to detect hypoglycaemia. Accuracy improvements through multivariable measures can make already marketed galvanic skin response devices a good noninvasive alternative. Breath volatile organic compounds can be detected by dogs and devices and alert patients at hypoglycaemia onset, while near-infrared spectroscopy can also be used as a hypoglycaemia alarms. Finally, one of the main directions of research are deep learning algorithms to analyse continuous glucose monitoring data and provide earlier and more accurate prediction of hypoglycaemia. Current developments for early identification of hypoglycaemia risk combine improvements of available 'needle-type' enzymatic glucose sensors and noninvasive alternatives. Patient usability will be essential to demonstrate to allow their implementation for daily use in diabetes management.

Glucose-lowering pharmacotherapies in Chinese adults with type 2 diabetes and cardiovascular disease or chronic kidney disease. An expert consensus reported by the Chinese Diabetes Society and the Chinese Society of Endocrinology

Patients with type 2 diabetes mellitus (T2DM) are at risk of developing atherosclerotic cardiovascular disease (ASCVD) and chronic kidney disease (CKD), which are important causes of disabling and death in patients with T2DM. For the prevention and management of ASCVD or CKD, cardiovascular risk factors should be systematically evaluated, and ASCVD and CKD should be screened in patients with T2DM. In this consensus, we recommended that metformin should be used as the first-line therapy for patients with T2DM and ASCVD or very high cardiovascular risk, heart failure (HF) or CKD, and should be retained in the treatment regimen unless contraindicated or not tolerated. In patients with T2DM and established ASCVD or very high cardiovascular risk, addition of a glucagon-like peptide 1 receptor agonist (GLP-1RA) or sodium-glucose cotransporter type 2 (SGLT2) inhibitor with proven cardiovascular benefits should be considered independent of individualised glycated haemoglobin (HbA_1C ) targets. In patients with T2DM and HF, an SGLT2 inhibitor should be preferably added regardless of HbA_1C levels. In patients with T2DM and CKD, SGLT2 inhibitors should be preferred for the combination therapy independent of individualised HbA_1C targets, and GLP-1RAs with proven renal benefits would be alternative if SGLT2 inhibitors are contraindicated. Moreover, the prevention of hypoglycaemia and management of multiple risk factors by comprehensive regimen, including lifestyle intervention, antihypertensive therapies, lipid-lowering treatment and antiplatelet therapies, should be kept in mind in treating patients with T2DM and ASCVD, HF or CKD.

Nocturnal Hypoglycaemia in Patients with Diabetes Mellitus: Database Analysis of a Cohort Using Telemedicine Support for Self-Monitoring of Blood Glucose over a 10-Year-Long Period

Background and Objectives: In patients with diabetes mellitus, hypoglycaemic episodes, especially during night hours, carry a significant risk. Data about the occurrence of nocturnal hypoglycaemia in real-world settings are of clinical importance. The aim of our study was to evaluate the occurrence of nocturnal hypoglycaemia among patients with diabetes using self-monitoring of blood glucose (SMBG) with telemedicine support. Materials and Methods: We retrospectively analysed the central database of an internet-based supportive system between 2010 and 2020 when 8190 SMBG users uploaded nearly 10 million capillary blood glucose values. Nocturnal hypoglycaemia was defined as capillary blood glucose < 3.0 mmol/L measured between 00:00 and 05:59 h. Results: The database contained 914,146 nocturnal blood glucose values from 7298 users; 24,623 (2.7%) glucose values were below the hypoglycaemic threshold and 2363 patients (32.4%) had at least one hypoglycaemic glucose value. Nocturnal hypoglycaemia was more often found in patients with type 1 vs. type 2 diabetes (n = 1890 (80.0%) vs. n = 387 (16.4%), respectively). Hypoglycaemic blood glucose values were most frequently observed in the age group of 10.0–19.9 years (n = 481 (20.4%)). Patients with nocturnal hypoglycaemia were mostly on insulin treatment (1854 (78.5%) patients with 20,727 (84.1%) hypoglycaemic glucose values). Only 356 patients (15.1%) with nocturnal hypoglycaemia performed a retest within 120 min. Within a one-day-long (1440 min) timeframe, the elapsed median time until a retest, yielding a safe blood glucose value (>3.9 mml/L), was 273 min (interquartile range: 157–300 min). Conclusions: Nocturnal hypoglycaemia should be considered as a persisting challenge to antihyperglycaemic treatment in patients living with diabetes. Continuous efforts are needed to improve both antihyperglycaemic treatment and patient education for preventing nocturnal hypoglycaemia, and to act adequately if hypoglycaemic values are detected.

Glucagon for hypoglycaemia treatment in type 1 diabetes

To achieve strict glycaemic control and avoid chronic diabetes complications, individuals with type 1 diabetes (T1D) are recommended to follow an intensive insulin regimen. However, the risk and fear of hypoglycaemia often prevent individuals from achieving the treatment goals. Apart from early insulin suspension in insulin pump users, carbohydrate ingestion is the only option for preventing and treating non-severe hypoglycaemic events. These rescue treatments may give extra calories and cause overweight. As an alternative, the use of low-dose glucagon to counter hypoglycaemia has been proposed as a tool to raise glucose concentrations without adding extra calories. Previously, the commercially available glucagon formulations required reconstitution from powder to a solution before being injected subcutaneously or intramuscularly-making it practical only for treating severe hypoglycaemia. Several companies have developed more stable formulations that do not require the time-consuming reconstitution process before use. As well as treating severe hypoglycaemia, non-severe and impending hypoglycaemia can also be treated with lower doses of glucagon. Once available, low-dose glucagon can be either delivered manually, as an injection, or automatically, by an infusion pump. This review focuses on the role and perspectives of using glucagon to treat and prevent hypoglycaemia in T1D.