Self-reported hypoglycaemia in patients with type 2 diabetes treated with insulin in the Hoorn Diabetes Care System Cohort, the Netherlands: a prospective cohort study

Association of hypoglycaemia with the risks of arrhythmia and mortality in individuals with diabetes - a systematic review and meta-analysis

Background

Hypoglycaemia has been linked to an increased risk of cardiac arrhythmias by causing autonomic and metabolic alterations, which may be associated with detrimental outcomes in individuals with diabetes(IWD), such as cardiovascular diseases (CVDs) and mortality, especially in multimorbid or frail people. However, such relationships in this population have not been thoroughly investigated. For this reason, we conducted a systematic review and meta-analysis.

Methods

Relevant papers published on PubMed, Embase, Cochrane, Web of Knowledge, Scopus, and CINHAL complete from inception to December 22, 2022 were routinely searched without regard for language. All of the selected articles included odds ratio, hazard ratio, or relative risk statistics, as well as data for estimating the connection of hypoglycaemia with cardiac arrhythmia, CVD-induced death, or total death in IWD. Regardless of the heterogeneity assessed by the I2 statistic, pooled relative risks (RRs) and 95% confidence intervals (CI) were obtained using random-effects models.

Results

After deleting duplicates and closely evaluating all screened citations, we chose 60 studies with totally 5,960,224 participants for this analysis. Fourteen studies were included in the arrhythmia risk analysis, and 50 in the analysis of all-cause mortality. Hypoglycaemic patients had significantly higher risks of arrhythmia occurrence (RR 1.42, 95%CI 1.21-1.68), CVD-induced death (RR 1.59, 95% CI 1.24-2.04), and all-cause mortality (RR 1.68, 95% CI 1.49-1.90) compared to euglycaemic patients with significant heterogeneity.

Conclusion

Hypoglycaemic individuals are more susceptible to develop cardiac arrhythmias and die, but evidence of potential causal linkages beyond statistical associations must await proof by additional specifically well planned research that controls for all potential remaining confounding factors.

Different levels of hypoglycemia in patients with type 2 diabetes, their achieved mean HbA1c vs. all-cause and cardiovascular mortality

AIM

In patients with type 2 diabetes (T2D), levels of hypoglycemia and their risk of mortality are not well understood. The aim of this study was to ascertain the correlation among disparate levels of hypoglycemia and patients with T2D's achieved mean glycated hemoglobin A1c (HbA1c) with all-cause and cardiovascular mortality.

METHODS

27,932 T2D patients taking hypoglycemic medications at outpatient visits for more than 6 months between 2008 and 2018 were linked to Taiwan's National Death Registry. We determined the respective mortality rates with Poisson assumption, and explored the relative risks of all-cause and cardiovascular mortality according to dissimilar levels of hypoglycemia with their achieved mean HbA1c by Cox proportional hazard regression model with adjustment of potential confounders.

RESULTS

T2D patients with level 3 hypoglycemia had the highest rates of all-cause and cardiovascular mortality. Compared with those who never encountered hypoglycemia, study subjects with level 1 and level 2 hypoglycemia did not show excessive risks of either all-cause or cardiovascular mortality. Only those with level 3 hypoglycemia revealed marginal risk of all-cause (Hazard ratio [HR]: 1.18; 95% Confidence Interval [CI] 1.04-1.33) but not cardiovascular mortality (HR: 1.16; 95% CI 0.88-1.53). In T2D patients with hypoglycemia, only those with mean HbA1c ≥9.0% increased all-cause mortality in level 3 hypoglycemia, and cardiovascular mortality in level 1 hypoglycemia.

CONCLUSIONS

Elevated risk of all-cause mortality was exclusively found in patients with level 3 hypoglycemia. In T2D patients with hypoglycemia, mean HbA1c ≥ 9% increased all-cause or cardiovascular mortality. Aggressive treatment of accompanying serious illness in severe hypoglycemia may help reduce mortality in patients with T2DM.

Development and Validation of an Electronic Health Record-Based Risk Assessment Tool for Hypoglycemia in Patients With Type 2 Diabetes Mellitus

BACKGROUND

The recent availability of high-quality data from clinical trials, together with machine learning (ML) techniques, presents exciting opportunities for developing prediction models for clinical outcomes.

METHODS

As a proof-of-concept, we translated a hypoglycemia risk model derived from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study into the HypoHazardScore, a risk assessment tool applicable to electronic health record (EHR) data. To assess its performance, we conducted a 16-week clinical study at the University of Minnesota where participants (N = 40) with type 2 diabetes mellitus (T2DM) had hypoglycemia assessed prospectively by continuous glucose monitoring (CGM).

RESULTS

The HypoHazardScore combines 16 risk factors commonly found within the EHR. The HypoHazardScore successfully predicted (area under the curve [AUC] = 0.723) whether participants experienced least one CGM-assessed hypoglycemic event (glucose <54 mg/dL for ≥15 minutes from two CGMs) while significantly correlating with frequency of CGM-assessed hypoglycemic events (r = 0.38) and percent time experiencing CGM-assessed hypoglycemia (r = 0.39). Compared to participants with a low HypoHazardScore (N = 19, score <4, median score of 4), participants with a high HypoHazardScore (N = 21, score ≥4) had more frequent CGM-assessed hypoglycemic events (high: 1.6 ± 2.2 events/week; low: 0.3 ± 0.5 events/week) and experienced more CGM-assessed hypoglycemia (high: 1.4% ± 2.0%; low: 0.2% ± 0.4% time) during the 16-week follow-up.

CONCLUSIONS

We demonstrated that a hypoglycemia risk model can be successfully adapted from the ACCORD data to the EHR, with validation by a prospective study using CGM-assessed hypoglycemia. The HypoHazardScore represents a significant advancement toward implementing an EHR-based decision support system that can help reduce hypoglycemia in patients with T2DM.

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.

Type 2 diabetes patients' views on prevention of hypoglycaemia - a mixed methods study investigating self-management issues and self-identified causes of hypoglycaemia

Background

Hypoglycaemia is a common and potentially avoidable adverse event in people with type 2 diabetes (T2D). It can reduce quality of life, increase healthcare costs, and reduce treatment success. We investigated self-management issues associated with hypoglycaemia and self-identified causes of hypoglycaemia in these patients.

Methods

In this mixed methods study qualitative semi-structured interviews were performed, which informed a subsequent quantitative survey in T2D patients. All interviews were audio recorded, transcribed verbatim and coded independently by two coders using directed content analysis, guided by the Theoretical Domains Framework. Descriptive statistics were used to quantify the self-management issues and causes of hypoglycaemia collected in the survey for the respondents that had experienced at least one hypoglycaemic event in the past.

Results

Sixteen participants were interviewed, aged 59–84 years. Participants perceived difficulties in managing deviations from routine, and they sometimes lacked procedural knowledge to adjust medication, nutrition or physical activity to manage their glucose levels. Grief and loss of support due to the loss of a partner interfered with self-management and lead to hypoglycaemic events. Work ethic lead some participant to overexerting themselves, which in turn lead to hypoglycaemic events. The participants had difficulties preventing hypoglycaemic events, because they did not know the cause, suffered from impaired hypoglycaemia awareness and/or did not want to regularly measure their blood glucose. When they did recognise a cause, they identified issues with nutrition, physical activity, stress or medication. In total, 40% of respondents reported regular stress as an issue, 24% reported that they regularly overestimated their physical abilities, and 22% indicated they did not always know how to adjust their medication. Around 16% of patients could not always remember whether they took their medication, and 42% always took their medication at regular times. Among the 83 respondents with at least one hypoglycaemic event, common causes for hypoglycaemia mentioned were related to physical activity (67%), low food intake (52%), deviations from routine (35%) and emotional burden (28%). Accidental overuse of medication was reported by 10%.

Conclusion

People with T2D experience various issues with self-managing their glucose levels. This study underlines the importance of daily routine and being able to adjust medication in relation to more physical activity or less food intake as well as the ability to reduce and manage stress to prevent hypoglycaemic events.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-021-01466-0.

Documentation of hypoglycemia assessment among adults with diabetes during clinical encounters in primary care and endocrinology practices

PURPOSE

To examine the proportion of diabetes-focused clinical encounters in primary care and endocrinology practices where the evaluation for hypoglycemia is documented; and when it is, identify clinicians' stated actions in response to patient-reported events.

METHODS

A total of 470 diabetes-focused encounters among 283 patients nonpregnant adults (≥18 years) with type 1 or type 2 diabetes mellitus in this retrospective cohort study. Participants were randomly identified in blocks of treatment strategy and care location (95 and 52 primary care encounters among hypoglycemia-prone medications (i.e. insulin, sulfonylurea) and others patients, respectively; 94 and 42 endocrinology encounters among hypo-treated and others, respectively). Documentation of hypoglycemia and subsequent management plan in the electronic health record were evaluated.

RESULTS

Overall, 132 (46.6%) patients had documentation of hypoglycemia assessment, significantly more prevalent among hypo-treated patients seen in endocrinology than in primary care (72.3% vs. 47.4%; P = 0.001). Hypoglycemia was identified by patient in 38.2% of encounters. Odds of hypoglycemia assessment documentation was highest among the hypo-treated (OR 13.6; 95% CI 5.5-33.74, vs. others) and patients seen in endocrine clinic (OR 4.48; 95% CI 2.3-8.6, vs. primary care). After documentation of hypoglycemia, treatment was modified in 30% primary care and 46% endocrine clinic encounters; P = 0.31. Few patients were referred to diabetes self-management education and support (DSMES).

CONCLUSIONS

Continued efforts to improve hypoglycemia evaluation, documentation, and management are needed, particularly in primary care. This includes not only screening at-risk patients for hypoglycemia, but also modifying their treatment regimens and/or leveraging DSMES.

Hypoglycemia Among Patients with Type 2 Diabetes: Epidemiology, Risk Factors, and Prevention Strategies

PURPOSE OF REVIEW

Hypoglycemia is the most common and often treatment-limiting serious adverse effect of diabetes therapy. Despite being potentially preventable, hypoglycemia in type 2 diabetes incurs substantial personal and societal burden. We review the epidemiology of hypoglycemia in type 2 diabetes, discuss key risk factors, and introduce potential prevention strategies.

RECENT FINDINGS

Reported rates of hypoglycemia in type 2 diabetes vary widely as there is marked heterogeneity in how hypoglycemia is defined, measured, and reported. In randomized controlled trials, rates of severe hypoglycemia ranged from 0.7 to 12 per 100 person-years. In observational studies, hospitalizations or emergency department visits for hypoglycemia were experienced by 0.2 (patients treated without insulin or sulfonylurea) to 2.0 (insulin or sulfonylurea users) per 100 person-years. Patient-reported hypoglycemia is much more common. Over the course of 6 months, 1-4% non-insulin users reported need for medical attention for hypoglycemia; 1-17%, need for any assistance; and 46-58%, any hypoglycemia symptoms. Similarly, over a 12-month period, 4-17% of insulin-treated patients reported needing assistance and 37-64% experienced any hypoglycemic symptoms. Hypoglycemia is most common among older patients with multiple or advanced comorbidities, patients with long diabetes duration, or patients with a prior history of hypoglycemia. Insulin and sulfonylurea use, food insecurity, and fasting also increase hypoglycemia risk. Clinical decision support tools may help identify at-risk patients. Prospective trials of efforts to reduce hypoglycemia risk are needed, and there is emerging evidence supporting multidisciplinary interventions including treatment de-intensification, use of diabetes technologies, diabetes self-management, and social support. Hypoglycemia among patients with type 2 diabetes is common. Patient-centered multidisciplinary care may help proactively identify at-risk patients and address the multiplicity of factors contributing to hypoglycemia occurrence.