Hypoglycemic and Hyperglycemic Crises Among U.S. Adults With Diabetes and End-stage Kidney Disease: Population-Based Study, 2013-2017

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.

Impact of Charlson Comorbidity Index on in-hospital mortality of patients with hyperglycemic crises: A propensity score matching analysis

AIM

This study was designed to investigate the association between Charlson Comorbidity Index (CCI) and in-hospital mortality and other clinical outcomes among patients with hyperglycemic crises.

METHOD

This retrospective cohort study was conducted using data from electric medical records. A total of 1668 diabetic patients with hyperglycemic crises from six tertiary hospitals met the inclusion criteria. CCI < 4 was defined as low CCI and CCI ≥ 4 was defined as high CCI. Propensity score matching (PSM) with the 1:1 nearest neighbour matching method and the caliper value of 0.02 was used to match the baseline characteristics of patients with high CCI and low CCI to reduce the confounding bias. In-hospital mortality, ICU admission, hypoglycemia, hypokalemia, acute kidney injury, length of stay (LOS), and hospitalisation expense between low CCI and high CCI were compared and assessed. Univariate and multivariate regression were applied to estimate the impact of CCI on in-hospital and other clinical outcomes.

OUTCOME

One hundred twenty-one hyperglycemic crisis (HC) patients died with a mortality rate of 7.3%. After PSM, compared with low CCI, patients with high CCI suffered higher in-hospital mortality, ICU admission, LOS, and hospitalisation expenses. After multivariate regression, age (aOR: 1.12, 95% confidence interval [CI]: 1.06-1.18, p < 0.001), CCI(aOR: 4.42, 95% CI: 1.56-12.53, p = 0.005), uninsured (aOR: 22.32, 95% CI: 4.26-116.94, p < 0.001), shock (aOR: 10.57, 95% CI: 1.41-79.09, p = 0.022), mechanical ventilation (aOR: 75.29, 95% CI: 12.37-458.28, p < 0.001), and hypertension (aOR: 4.34, 95% CI: 1.37-13.82, p = 0.013) were independent risk factors of in-hospital mortality of HC patients. Besides, high CCI was an independent risk factor for higher ICU Admission (aOR: 5.91, 95% CI: 2.31-15.08, p < 0.001), hypoglycemia (aOR: 2.19, 95% CI:1.01-4.08, p = 0.049), longer LOS (aOR: 1.23, 95% CI: 1.19-2.27, p = 0.021), and higher hospitalisation expense (aOR: 2089.97, 95% CI: 193.33-3988.61, p = 0.031) of HC patients.

CONCLUSION

CCI is associated with in-hospital mortality, ICU admission, hypoglycemia, LOS, and hospitalisation expense of HC patients. CCI could be an ideal indicator to identify, monitor, and manage chronic comorbidities among HC patients.

Continuous Glucose Monitoring and Reduced Diabetes-Related Hospitalizations in Patients with Type 2 Diabetes and CKD

Key Points

Patients with diabetes and CKD have a heightened risk of glycemic variability, which can lead to severe hypoglycemic or hyperglycemic events, potentially resulting in hospitalization. This study describes the results of a retrospective claims analysis of people with insulin-requiring type 2 diabetes and stage 3–5 CKD who initiated continuous glucose monitoring. Continuous glucose monitoring could help patients with type 2 diabetes and CKD control their glucose and avoid potentially dangerous glycemic events.

Background

There is a heightened risk of glycemic variability in patients with diabetes and CKD. This glycemic variability could lead to hypoglycemic or hyperglycemic crises. We hypothesized that initiation of continuous glucose monitoring (CGM), which provides a glucose measurement every 1–5 minutes, could reduce the incidence of hospitalizations for patients with type 2 diabetes (T2D) and CKD.

Methods

A retrospective analysis of US administrative claims data from the Optum Clinformatics database was conducted. People with T2D, using insulin, not receiving dialysis, and living with stage 3–5 CKD who initiated CGM between January 1, 2016, and March 31, 2022, were identified. National Drug Codes and Healthcare Common Coding Procedure System codes were used to identify CGM device use, and International Classification of Diseases 10th revision codes were used to identify CKD diagnosis and categorize health care encounters. Rates of diabetes-related hospitalizations were obtained, and multivariable logistic regression analyses revealed predictors of hypoglycemic and hyperglycemic encounters.

Results

A total of 8,959 insulin-using patients with T2D and CKD were identified. Most were White (72.3%), had Medicare insurance coverage (82.2%), were using intensive insulin (91.3%), and had stage 3 CKD (86.0%). After CGM initiation, rates of hospitalizations for hyperglycemia or hypoglycemia decreased by 18.2% and 17.0%, respectively (P < 0.0001 for both). The proportion hospitalized with at least one hypoglycemic or hyperglycemic event also significantly decreased after CGM initiation. Significant predictors of both hypoglycemic and hyperglycemic encounters included a previous encounter of that type, age 30–59 years and depression (for hypoglycemia), and age 30–49 years and neuropathy (for hyperglycemia). Use of CGM or glucagon-like peptide-1 receptor agonists was significantly protective against hypoglycemic encounters.

Conclusions

Initiation of CGM was associated with significant reductions in diabetes-related hospitalizations among insulin-using individuals with T2D and moderate-to-severe CKD. CGM could help patients with T2D and CKD control their glucose and avoid potentially dangerous glycemic events.

Assessment of Glycemic Control by Continuous Glucose Monitoring, Hemoglobin A1c, Fructosamine, and Glycated Albumin in Patients With End-Stage Kidney Disease and Burnt-Out Diabetes

OBJECTIVE

Patients with diabetes and end-stage kidney disease (ESKD) may experience "burnt-out diabetes," defined as having an HbA1c value <6.5% without antidiabetic therapy for >6 months. We aim to assess glycemic control by continuous glucose monitoring (Dexcom G6 CGM) metrics and glycemic markers in ESKD patients on hemodialysis with burnt-out diabetes.

RESEARCH DESIGN AND METHODS

In this pilot prospective study, glycemic control was assessed by continuous glucose monitoring (CGM), HbA1c measures, and glycated albumin and fructosamine measurements in patients with burnt-out diabetes (n = 20) and without a history of diabetes (n = 20).

RESULTS

Patients with burnt-out diabetes had higher CGM-measured daily glucose levels, lower percent time in the range 70-180 mg/dL, higher percent time above range (>250 mg/dL), and longer duration of hyperglycemia >180 mg/dL (hours/day) compared with patients without diabetes (all P < 0.01). HbA1c and fructosamine levels were similar; however, patients with burnt-out diabetes had higher levels of glycated albumin than did patients without diabetes.

CONCLUSIONS

The use of CGM demonstrated that patients with burnt-out diabetes have significant undiagnosed hyperglycemia. CGM and glycated albumin provide better assessment of glycemic control than do values of HbA1c and fructosamine in patients with ESKD.

Medication-Related Hospital Admissions and Emergency Department Visits in Older People with Diabetes: A Systematic Review

Limited data are available regarding adverse drug reactions (ADRs) and medication-related hospitalisations or emergency department (ED) visits in older adults with diabetes, especially since the emergence of newer antidiabetic agents. This systematic review aimed to explore the nature of hospital admissions and ED visits that are medication-related in older adults with diabetes. The review was conducted according to the PRISMA guidelines. Studies in English that reported on older adults (mean age ≥ 60 years) with diabetes admitted to the hospital or presenting to ED due to medication-related problems and published between January 2000 and October 2023 were identified using Medline, Embase, and International Pharmaceutical Abstracts databases. Thirty-five studies were included. Medication-related hospital admissions and ED visits were all reported as episodes of hypoglycaemia and were most frequently associated with insulins and sulfonylureas. The studies indicated a decline in hypoglycaemia-related hospitalisations or ED presentations in older adults with diabetes since 2015. However, the associated medications remain the same. This finding suggests that older patients on insulin or secretagogue agents should be closely monitored to prevent potential adverse events, and newer agents should be used whenever clinically appropriate.

Use of Analog and Human Insulin in a European Hemodialysis Cohort With Type 2 Diabetes: Associations With Mortality, Hospitalization, MACE, and Hypoglycemia

RATIONALE & OBJECTIVE

Poor glycemic control may contribute to the high mortality rate in patients with type 2 diabetes receiving hemodialysis. Insulin type may influence glycemic control, and its choice may be an opportunity to improve outcomes. This study assessed whether treatment with analog insulin compared with human insulin is associated with different outcomes in people with type 2 diabetes and kidney failure receiving hemodialysis.

STUDY DESIGN

Retrospective cohort study.

SETTING & PARTICIPANTS

People in the Analyzing Data, Recognizing Excellence and Optimizing Outcomes (AROii) study with kidney failure commencing hemodialysis and type 2 diabetes being treated with insulin within 288 dialysis facilities between 2007 and 2009 across 7 European countries. Study participants were followed for 3 years. People with type 1 diabetes were excluded using an established administrative data algorithm.

EXPOSURE

Treatment with an insulin analog or human insulin.

OUTCOME

All-cause mortality, major adverse cardiovascular events (MACE), all-cause hospitalization, and confirmed hypoglycemia (blood glucose<3.0mmol/L sampled during hemodialysis).

ANALYTICAL APPROACH

Inverse probability weighted Cox proportional hazards models to estimate hazard ratios for analog insulin compared with human insulin.

RESULTS

There were 713 insulin analog and 733 human insulin users. Significant variation in insulin type by country was observed. Comparing analog with human insulin at 3 years, the percentage of patients experiencing end points and adjusted hazard ratios (AHR) were 22.0% versus 31.4% (AHR, 0.808 [95% CI, 0.66-0.99], P=0.04) for all-cause mortality, 26.8% versus 35.9% (AHR, 0.817 [95% CI, 0.68-0.98], P=0.03) for MACE, and 58.2% versus 75.0% (AHR, 0.757 [95% CI, 0.67-0.86], P<0.001) for hospitalization. Hypoglycemia was comparable between insulin types at 14.1% versus 15.0% (AHR, 1.169 [95% CI, 0.80-1.72], P=0.4). Consistent strength and direction of the associations were observed across sensitivity analyses.

LIMITATIONS

Residual confounding, lack of more detailed glycemia data.

CONCLUSIONS

In this large multinational cohort of people with type 2 diabetes and kidney failure receiving maintenance hemodialysis, treatment with analog insulins was associated with better clinical outcomes when compared with human insulin.

PLAIN-LANGUAGE SUMMARY

People with diabetes who are receiving dialysis for kidney failure are at high risk of cardiovascular disease and death. This study uses information from 1,446 people with kidney failure from 7 European countries who are receiving dialysis, have type 2 diabetes, and are prescribed either insulin identical to that made in the body (human insulin) or insulins with engineered extra features (insulin analog). After 3 years, fewer participants receiving analog insulins had died, had been admitted to the hospital, or had a cardiovascular event (heart attack, stroke, heart failure, or peripheral vascular disease). These findings suggest that analog insulins should be further explored as a treatment leading to better outcomes for people with diabetes on dialysis.

6. Glycemic Goals and Hypoglycemia: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Evaluation of High-Deductible Health Plans and Acute Glycemic Complications Among Adults With Diabetes

Importance

Optimal diabetes care requires regular monitoring and care to maintain glycemic control. How high-deductible health plans (HDHPs), which reduce overall spending but may impede care by increasing out-of-pocket expenses, are associated with risks of severe hypoglycemia and hyperglycemia is unknown.

Objective

To examine the association between an employer-forced switch to HDHP and severe hypoglycemia and hyperglycemia.

Design, Setting, and Participants

This retrospective cohort study used deidentified administrative claims data for privately insured adults with diabetes from a single insurance carrier with multiple plans across the US between January 1, 2010, and December 31, 2018. Analyses were conducted between May 15, 2020, and November 3, 2022.

Exposures

Patients with 1 baseline year of enrollment in a non-HDHP whose employers subsequently forced a switch to an HDHP were compared with patients who did not switch.

Main Outcomes and Measures

Mixed-effects logistic regression models were used to examine the association between switching to an HDHP and the odds of severe hypoglycemia and hyperglycemia (ascertained using diagnosis codes in emergency department [ED] visits and hospitalizations), adjusting for patient age, sex, race and ethnicity, region, income, comorbidities, glucose-lowering medications, baseline ED and hospital visits for hypoglycemia and hyperglycemia, and baseline deductible amount, and applying inverse propensity score weighting to account for potential treatment selection bias.

Results

The study population was composed of 42 326 patients who switched to an HDHP (mean [SD] age: 52 [10] years, 19 752 [46.7%] women, 7375 [17.4%] Black, 5740 [13.6%] Hispanic, 26 572 [62.8%] non-Hispanic White) and 202 729 patients who did not switch (mean [SD] age, 53 [10] years, 89 828 [44.3%] women, 29 551 [14.6%] Black, 26 689 [13.2%] Hispanic, 130 843 [64.5%] non-Hispanic White). When comparing all study years, switching to an HDHP was not associated with increased odds of experiencing at least 1 hypoglycemia-related ED visit or hospitalization (OR, 1.01 [95% CI, 0.95-1.06]; P = .85), but each year of HDHP enrollment did increase these odds by 2% (OR, 1.02 [95% CI, 1.00-1.04]; P = .04). In contrast, switching to an HDHP did significantly increase the odds of experiencing at least 1 hyperglycemia-related ED visit or hospitalization (OR, 1.25 [95% CI, 1.11-1.42]; P < .001), with each year of HDHP enrollment increasing the odds by 5% (OR, 1.05 [95% CI, 1.01-1.09]; P = .02).

Conclusions and Relevance

In this cohort study, employer-forced switching to an HDHP was associated with increased odds of potentially preventable acute diabetes complications, potentially because of delayed or deferred care. These findings suggest that employers should be more judicious in their health plan offerings, and health plans and policy makers should consider allowing preventive and high-value services to be exempt from deductible requirements.

Continuous Glucose Monitoring to Optimize Management of Diabetes in Patients with Advanced CKD

Treatment of patients with diabetes and CKD includes optimizing glycemic control using lifestyle modifications and drugs that safely control glycemia and improve clinical kidney and cardiovascular disease outcomes. However, patients with advanced CKD, defined as eGFR <30 ml/min per 1.73 m2 or kidney disease treated with dialysis, have limitations to the use of some preferred glucose-lowering medications, are often treated with insulin, and experience high rates of severe hypoglycemia. Moreover, hemoglobin A1c accuracy decreases as GFR deteriorates. Hence, there is a need for better glycemic monitoring tools. Continuous glucose monitoring allows for 24-hour glycemic monitoring to understand patterns and the effects of lifestyle and medications. Real-time continuous glucose monitoring can be used to guide the administration of insulin and noninsulin therapies. Continuous glucose monitoring can overcome the limitations of self-monitored capillary glucose testing and hemoglobin A1c and has been shown to prevent hypoglycemic excursions in some populations. More data are needed to understand whether similar benefits can be obtained for patients with diabetes and advanced CKD. This review provides an updated approach to management of glycemia in advanced CKD, focusing on the role of continuous glucose monitoring in this high-risk population.

American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update

OBJECTIVE

The objective of this clinical practice guideline is to provide updated and new evidence-based recommendations for the comprehensive care of persons with diabetes mellitus to clinicians, diabetes-care teams, other health care professionals and stakeholders, and individuals with diabetes and their caregivers.

METHODS

The American Association of Clinical Endocrinology selected a task force of medical experts and staff who updated and assessed clinical questions and recommendations from the prior 2015 version of this guideline and conducted literature searches for relevant scientific papers published from January 1, 2015, through May 15, 2022. Selected studies from results of literature searches composed the evidence base to update 2015 recommendations as well as to develop new recommendations based on review of clinical evidence, current practice, expertise, and consensus, according to established American Association of Clinical Endocrinology protocol for guideline development.

RESULTS

This guideline includes 170 updated and new evidence-based clinical practice recommendations for the comprehensive care of persons with diabetes. Recommendations are divided into four sections: (1) screening, diagnosis, glycemic targets, and glycemic monitoring; (2) comorbidities and complications, including obesity and management with lifestyle, nutrition, and bariatric surgery, hypertension, dyslipidemia, retinopathy, neuropathy, diabetic kidney disease, and cardiovascular disease; (3) management of prediabetes, type 2 diabetes with antihyperglycemic pharmacotherapy and glycemic targets, type 1 diabetes with insulin therapy, hypoglycemia, hospitalized persons, and women with diabetes in pregnancy; (4) education and new topics regarding diabetes and infertility, nutritional supplements, secondary diabetes, social determinants of health, and virtual care, as well as updated recommendations on cancer risk, nonpharmacologic components of pediatric care plans, depression, education and team approach, occupational risk, role of sleep medicine, and vaccinations in persons with diabetes.

CONCLUSIONS

This updated clinical practice guideline provides evidence-based recommendations to assist with person-centered, team-based clinical decision-making to improve the care of persons with diabetes mellitus.