Hospital Readmissions among Commercially Insured and Medicare Advantage Beneficiaries with Diabetes and the Impact of Severe Hypoglycemic and Hyperglycemic Events

A Systematic Review of Recent Studies on Hospital Readmissions of Patients With Diabetes

Hospital readmissions are a major area of concern across the healthcare ecosystem. Diabetes mellitus (DM) and associated complications significantly contributed to hospital readmissions in 2018, placing it among the leading causes alongside septicemia and heart failure. Diabetes is an urgent public health concern that has reached epidemic proportions globally. Compared to the early 2000s, the prevalence of diabetes among individuals aged 20-79 years in the US has significantly increased. This research provides an in-depth examination of diabetes-related hospital readmissions and reviews recent studies (2015-2023) to understand the characteristics, risk factors, and potential outcomes for re-admitted diabetes patients. The study identified 21 articles that met the inclusion criteria to provide valuable insights and analyze risk factors associated with these readmissions. The findings indicated that risk factors such as age, demographics, income, insurance type, severity of illness, and comorbidities among diabetic patients were critical and warranted further investigation. Diabetes awareness, quality of hospital care, involvement of healthcare providers, timely screening, and lifestyle changes were noted as important factors to improve the effectiveness of healthcare delivery, reduce diabetes-related complications, and eventually lower preventable hospital readmissions.

Outcomes of the Dulce Digital-COVID Aware (DD-CA) discharge texting platform for US/Mexico border Hispanic individuals with diabetes

BACKGROUND

Hispanic individuals have higher type 2 diabetes (T2D) prevalence, poorer outcomes, and are disproportionately affected by COVID-19. Culturally-tailored, diabetes educational text messaging has previously improved HbA1c in this population.

METHODS

During the pandemic, hospitalized Hispanic adults with T2D (N = 172) were randomized to receive Dulce Digital-COVID Aware ("DD-CA") texting platform upon discharge plus diabetes transition service (DTS) or DTS alone. DD-CA includes diabetes educational messaging with additional COVID-safe messaging (e.g., promoting masking; social distancing; vaccination).

FINDINGS

Among adults with poorly-controlled diabetes (Mean HbA1c = 9.6 ± 2.2 %), DD-CA did not reduce 30- or 90-day readmissions compared to standard care (28 % vs 15 %, p = .06; 37 % vs 35 %, p = .9, respectively). However, the improvement in HbA1c was larger among those in the DD-CA compared to DTS at 3 months (n = 56; -2.69 % vs. -1.45 %, p = .0496) with reduced effect at 6 months (n = 64; -2.03 % vs -0.91 %, p = .07). Low follow-up completion rates and the addition of covariates (to control for baseline group differences that existed despite randomization) impacted statistical power.

INTERPRETATION

During the pandemic, DD-CA offered an alternative digital approach to diabetes and COVID education and support for a high-risk Hispanic population and achieved trends toward improvement in glycemic control despite relatively low engagement and not reducing hospital readmissions.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Risk of Severe Hypoglycemia With Newer Second-line Glucose-lowering Medications in Older Adults With Type 2 Diabetes Stratified by Known Indicators of Hypoglycemia Risk

BACKGROUND

Severe hypoglycemia is associated with adverse clinical outcomes. We evaluated the risk of severe hypoglycemia in older adults initiating newer glucose-lowering medications overall and across strata of known indicators of high hypoglycemia risk.

METHODS

We conducted a comparative-effectiveness cohort study of older adults aged >65 years with type 2 diabetes initiating sodium-glucose cotransporter 2 inhibitors (SGLT2i) versus dipeptidyl peptidase-4 inhibitors (DPP-4i) or SGLT2i versus glucagon-like peptide-1 receptor agonists (GLP-1RA) using Medicare claims (3/2013-12/2018) and Medicare-linked-electronic health records. We identified severe hypoglycemia requiring emergency or inpatient visits using validated algorithms. After 1:1 propensity score matching, we estimated hazard ratios (HR) and rate differences (RD) per 1,000 person-years. Analyses were stratified by baseline insulin, sulfonylurea, cardiovascular disease (CVD), chronic kidney disease (CKD), and frailty.

RESULTS

Over a median follow-up of 7 (interquartile range: 4-16) months, SGLT2i was associated with a reduced risk of hypoglycemia versus DPP-4i (HR 0.75 [0.68, 0.83]; RD -3.21 [-4.29, -2.12]), and versus GLP-1RA (HR 0.90 [0.82, 0.98]; RD -1.33 [-2.44, -0.23]). RD for SGLT2i versus DPP-4i was larger in patients using baseline insulin than in those not, although HRs were similar. In patients using baseline sulfonylurea, the risk of hypoglycemia was lower in SGLT2i versus DPP-4i (HR 0.57 [0.49, 0.65], RD -6.80 [-8.43, -5.16]), while the association was near-null in those without baseline sulfonylurea. Results stratified by baseline CVD, CKD and frailty were similar to the overall cohort findings. Findings for the GLP-1RA comparison were similar.

CONCLUSIONS

SGLT2i was associated with a lower hypoglycemia risk versus incretin-based medications, with larger associations in patients using baseline insulin or sulfonylurea.

Glucagon prescribing and prevention of hospitalization for hypoglycemia in a large health system

AIMS

To examine glucagon prescribing trends among patients at high risk of severe hypoglycemia and assess if a glucagon prescription is associated with lower rates of severe hypoglycemia requiring hospital care.

METHODS

Retrospective analysis of electronic health records from a large integrated healthcare system between May 2019 and August 2021. We included adults (≥18 years) with type 1 diabetes or with type 2 diabetes treated with short-acting insulin and/or recent history of hypoglycemia-related emergency department visit or hospitalization. We calculated rates of glucagon prescribing overall and by patient characteristics. We then matched 1:1 those who were and were not prescribed glucagon and assessed subsequent hypoglycemia-related hospitalization.

RESULTS

Of 9,200 high risk adults, 2063 (22.4%) were prescribed glucagon. Among patients more likely to be prescribed glucagon were those younger, female, White, living in urban areas, with prior severe hypoglycemia, and with a recent endocrinology specialist visit. In the matched cohort (N = 1707 per arm), 62 prescribed glucagon and 33 not prescribed glucagon were hospitalized for hypoglycemia (adjusted incidence rate ratio 1.71, 95% CI 1.10-2.66; P = 0.018).

CONCLUSION

Glucagon prescribing was infrequent with significant racial and rural disparities. Patients with glucagon prescriptions did not have lower rates of hospitalization for hypoglycemia.

Glucagon Prescribing and Costs Among U.S. Adults With Diabetes, 2011-2021

OBJECTIVE

To characterize contemporary trends in glucagon fill rates and expenditures in a nationwide cohort of adults with diabetes overall and by key demographic and clinical characteristics.

RESEARCH DESIGN AND METHODS

In this retrospective cohort study, we examined 1) glucagon fill rates per 1,000 person-years and 2) patient out-of-pocket and health plan costs per filled glucagon dose among adults with diabetes included in OptumLabs Data Warehouse between 1 January 2011 and 31 March 2021.

RESULTS

The study population comprised 2,814,464 adults with diabetes with a mean age of 62.8 (SD 13.2) years. The overall glucagon fill rate decreased from 2.91 to 2.28 per 1,000 person-years (-22%) over the study period. In groups at high risk for severe hypoglycemia, glucagon fill rates increased from 22.46 to 36.76 per 1,000 person-years (64%) among patients with type 1 diabetes, 11.64 to 16.63 per 1,000 person-years (43%) among those treated with short-acting insulin, and 16.08 to 20.12 per 1,000 person-years (25%) among those with a history of severe hypoglycemia. White patients, women, individuals with high income, and commercially insured patients had higher glucagon fill rates compared with minority patients, males, individuals with low income, and Medicare Advantage patients, respectively. Total cost per dosing unit increased from $157.97 to $275.32 (74%) among commercial insurance beneficiaries and from $150.37 to $293.57 (95%) among Medicare Advantage beneficiaries.

CONCLUSIONS

Glucagon fill rates are concerningly low and declined between 2011 and 2021 but increased in appropriate subgroups with type 1 diabetes, using short-acting insulin, or with a history of severe hypoglycemia. Fill rates were disproportionately low among minority patients and individuals with low income.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

[Hospital diabetes management (Update 2023)]

This position statement presents the recommendations of the Austrian Diabetes Association for diabetes management of adult patients during inpatient stay. It is based on the current evidence with respect to blood glucose targets, insulin therapy and treatment with oral/injectable antidiabetic drugs during inpatient hospitalization. Additionally, special circumstances such as intravenous insulin therapy, concomitant therapy with glucocorticoids and use of diabetes technology during hospitalization are discussed.

Predicting readmission due to severe hyperglycemia after a hyperglycemic crisis episode

AIM

This study aimed to investigate the readmission pattern and risk factors for patients who experienced a hyperglycemic crisis.

METHODS

Patients admitted to MacKay Memorial Hospital for diabetic ketoacidosis (DKA) or hyperglycemic hyperosmolar state (HHS) between January 2016 and April 2019 were studied. The timing of the first readmission for hyperglycemia and other causes was recorded. Kaplan-Meier analysis was used to compare patients with hyperglycemia and all-cause readmissions. Cox regression was used to identify independent predictors for hyperglycemia and all-cause readmission post-discharge.

RESULTS

The study cohort included 410 patients, and 15.3 % and 46.3 % of them had hyperglycemia and all-cause readmissions, respectively. The DKA and HHS group showed a similar incidence for hyperglycemia, with the latter group showing a higher incidence of all-cause readmissions. The significant predictors of hyperglycemia readmissions included young age, smoking, hypoglycemia, higher effective osmolality, and hyperthyroidism in the DKA group and higher glycated hemoglobin level in the HHS group.

CONCLUSIONS

Patients who experienced DKA and HHS had similar hyperglycemia readmission rates; however, predictors in the DKA group were not applicable to the HHS group. Designing different strategies for different types of hyperglycemic crisis is necessary for preventing readmission.

Burden of hospitalizations in newly diagnosed heart failure patients in Poland: real world population based study in years 2013-2019

Aims

We aim to report trends in unplanned hospitalizations among newly diagnosed heart failure patients with regard to hospitalizations types and their impact on outcomes.

Methods and results

A nation‐wide study of all citizens in Poland with newly diagnosed heart failure based on ICD‐10 coding who were beneficiaries of either public primary, secondary, or hospital care between 2013 and 2018 in Poland. Between 1 January 2013 and 31 December 2019, there were 1 124 118 newly diagnosed heart failure patients in Poland in both out‐ and inpatient settings. The median observation time was 946 days. As many as 49% experienced at least one acute heart failure hospitalization. Once hospitalized, 44.6% patients experienced at least one all‐cause rehospitalization and 26% another heart failure rehospitalization. The latter had the highest Charlson co‐morbidity index (1.36). The 30 day heart failure readmission rate was 2.96%. Kaplan–Meier analysis revealed very early readmissions (up to 1–7 days) were associated with better survival compared with rehospitalization between 8 and 30 days. All‐cause mortality was related to the number of hospitalization with adjusted estimated hazard ratios: 1.550 (95% CI: 1.52–158) for the second HF hospitalization, 2.158 (95% CI: 2.098–2.219) for third, and 2.788 (95% CI: 2.67–2.91) for the fourth HF hospitalization and subsequent ones, as compared with the first hospitalization.

Conclusions

Among newly diagnosed heart failure patients in Poland between 2013 and 2019, nearly half required at least one unplanned heart failure hospitalization. The risk of death was growing with every other hospital reoccurrence due to heart failure.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Clinical risk factors and social needs of 30-day readmission among patients with diabetes: A retrospective study of the Deep South

Introduction

Evidence is needed for 30-day readmission risk factors (clinical factors and social needs) among patients with diabetes in the Deep South. To address this need, our objectives were to identify risk factors associated with 30-day readmissions among this population and determine the added predictive value of considering social needs.

Methods

This retrospective cohort study utilized electronic health records from an urban health system in the Southeastern U.S. The unit of analysis was index hospitalization with a 30-day washout period. The index hospitalizations were preceded by a 6-month pre-index period to capture risk factors (including social needs), and hospitalizations were followed 30 days post-discharge to evaluate all-cause readmissions (1=readmission; 0=no readmission). We performed unadjusted (chi-square and student's t-test, where applicable) and adjusted analyses (multiple logistic regression) to predict 30-day readmissions.

Results

A total of 26,332 adults were retained in the study population. Eligible patients contributed a total of 42,126 index hospitalizations, and the readmission rate was 15.21%. Risk factors associated with 30-day readmissions included demographics (e.g., age, race/ethnicity, insurance), characteristics of hospitalizations (e.g., admission type, discharge status, length of stay), labs and vitals (e.g., highest and lowest blood glucose measurements, systolic and diastolic blood pressure), co-existing chronic conditions, and preadmission antihyperglycemic medication use. In univariate analyses of social needs, activities of daily living (p<0.001), alcohol use (p<0.001), substance use (p=0.002), smoking/tobacco use (p<0.001), employment status (p<0.001), housing stability (p<0.001), and social support (p=0.043) were significantly associated with readmission status. In the sensitivity analysis, former alcohol use was significantly associated with higher odds of readmission compared to no alcohol use [aOR (95% CI): 1.121 (1.008-1.247)].

Conclusions

Clinical assessment of readmission risk in the Deep South should consider patients' demographics, characteristics of hospitalizations, labs, vitals, co-existing chronic conditions, preadmission antihyperglycemic medication use, and social need (i.e., former alcohol use). Factors associated with readmission risk can help pharmacists and other healthcare providers identify high-risk patient groups for all-cause 30-day readmissions during transitions of care. Further research is needed about the influence of social needs on readmissions among populations with diabetes to understand the potential clinical utility of incorporating social needs into clinical services.

Association Between Area-Level Socioeconomic Deprivation and Diabetes Care Quality in US Primary Care Practices

IMPORTANCE

Diabetes management operates under a complex interrelationship between behavioral, social, and economic factors that affect a patient's ability to self-manage and access care.

OBJECTIVE

To examine the association between 2 complementary area-based metrics, area deprivation index (ADI) score and rurality, and optimal diabetes care.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study analyzed the electronic health records of patients who were receiving care at any of the 75 Mayo Clinic or Mayo Clinic Health System primary care practices in Minnesota, Iowa, and Wisconsin in 2019. Participants were adults with diabetes aged 18 to 75 years. All data were abstracted and analyzed between June 1 and November 30, 2020.

MAIN OUTCOMES AND MEASURES

The primary outcome was the attainment of all 5 components of the D5 metric of optimal diabetes care: glycemic control (hemoglobin A1c <8.0%), blood pressure (BP) control (systolic BP <140 mm Hg and diastolic BP <90 mm Hg), lipid control (use of statin therapy according to recommended guidelines), aspirin use (for patients with ischemic vascular disease), and no tobacco use. The proportion of patients receiving optimal diabetes care was calculated as a function of block group-level ADI score (a composite measure of 17 US Census indicators) and zip code-level rurality (calculated using Rural-Urban Commuting Area codes). Odds of achieving the D5 metric and its components were assessed using logistic regression that was adjusted for demographic characteristics, coronary artery disease history, and primary care team specialty.

RESULTS

Among the 31 934 patients included in the study (mean [SD] age, 59 [11.7] years; 17 645 men [55.3%]), 13 138 (41.1%) achieved the D5 metric of optimal diabetes care. Overall, 4090 patients (12.8%) resided in the least deprived quintile (quintile 1) of block groups and 1614 (5.1%) lived in the most deprived quintile (quintile 5), while 9193 patients (28.8%) lived in rural areas and 2299 (7.2%) in highly rural areas. The odds of meeting the D5 metric were lower for individuals residing in quintile 5 vs quintile 1 block groups (odds ratio [OR], 0.72; 95% CI, 0.67-0.78). Patients residing in rural (OR, 0.84; 95% CI, 0.73-0.97) and highly rural (OR, 0.81; 95% CI, 0.72-0.91) zip codes were also less likely to attain the D5 metric compared with those in urban areas.

CONCLUSIONS AND RELEVANCE

This cross-sectional study found that patients living in more deprived and rural areas were significantly less likely to attain high-quality diabetes care compared with those living in less deprived and urban areas. The results call for geographically targeted population health management efforts by health systems, public health agencies, and payers.

Liraglutide hospital discharge trial: A randomized controlled trial comparing the safety and efficacy of liraglutide versus insulin glargine for the management of patients with type 2 diabetes after hospital discharge

AIM

To compare a glucagon-like peptide-1 receptor agonist with basal insulin at hospital discharge in patients with uncontrolled type 2 diabetes in a randomized clinical trial.

METHODS

A total of 273 patients with glycated haemoglobin (HbA1c) 7%-10% (53-86 mol/mol) were randomized to liraglutide (n = 136) or insulin glargine (n = 137) at hospital discharge. The primary endpoint was difference in HbA1c at 12 and 26 weeks. Secondary endpoints included hypoglycaemia, changes in body weight, and achievement of HbA1c <7% (53 mmol/mol) without hypoglycaemia or weight gain.

RESULTS

The between-group difference in HbA1c at 12 weeks and 26 weeks was -0.28% (95% CI -0.64, 0.09), and at 26 weeks it was -0.55%, (95% CI -1.01, -0.09) in favour of liraglutide. Liraglutide treatment resulted in a lower frequency of hypoglycaemia <3.9 mmol/L (13% vs 23%; P = 0.04), but there was no difference in the rate of clinically significant hypoglycaemia <3.0 mmol/L. Compared to insulin glargine, liraglutide treatment was associated with greater weight loss at 26 weeks (-4.7 ± 7.7 kg vs -0.6 ± 11.5 kg; P < 0.001), and the proportion of patients with HbA1c <7% (53 mmol/mol) without hypoglycaemia was 48% versus 33% (P = 0.05) at 12 weeks and 45% versus 33% (P = 0.14) at 26 weeks in liraglutide versus insulin glargine. The proportion of patients with HbA1c <7% (53 mmol/mol) without hypoglycaemia and no weight gain was higher with liraglutide at 12 (41% vs 24%, P = 0.005) and 26 weeks (39% vs 22%; P = 0.014). The incidence of gastrointestinal adverse events was higher with liraglutide than with insulin glargine (P < 0.001).

CONCLUSION

Compared to insulin glargine, treatment with liraglutide at hospital discharge resulted in better glycaemic control and greater weight loss, but increased gastrointestinal adverse events.

Risk factors for hyperglycemia and hypoglycemia in adults with pharmacologically treated type 2 diabetes mellitus: a quantitative systematic review protocol

OBJECTIVE

The objective of this review is to identify and synthesize the risk factors for hyperglycemia or hypoglycemia in adults with pharmacologically treated type 2 diabetes mellitus in any scenarios and environments for health care.

INTRODUCTION

Studies around the world have investigated which factors are associated with episodes of alteration of blood glucose level. It is through the characterization of these factors that nurses can plan and intervene accurately in the control of serum glucose levels in people with diabetes.

INCLUSION CRITERIA

This review will include studies conducted among adults with pharmacologically treated type 2 diabetes mellitus in any scenarios and environments for health care. Studies should focus on risk factors for the variation of fasting glycemic levels lower than 3.9 mmol/L and higher than 7.21 mmol/L, as well as postprandial glycemic levels lower than 3.9 mmol/L and higher than 10 mmol/L.

METHODS

Databases to be searched include MEDLINE, Embase, CINAHL, PsycINFO, Web of Science, Scopus, LILACS, and ScienceDirect. Following the search, titles and abstracts will be screened by two independent reviewers for assessment against the inclusion criteria for the review. The full text of selected citations will be assessed in detail against the inclusion criteria, and studies selected for retrieval will be assessed by two independent reviewers for methodological validity using JBI critical appraisal tools. Studies will not be excluded based on their quality assessment. Data will be extracted using the standardized data extraction tools. Quantitative data will, where possible, be pooled in statistical meta-analysis.

SYSTEMATIC REVIEW REGISTRATION NUMBER

PROSPERO (CRD42019134755).

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Flash CGM Is Associated With Reduced Diabetes Events and Hospitalizations in Insulin-Treated Type 2 Diabetes

Purpose

Suboptimal glycemic control among individuals with diabetes is a leading cause of hospitalizations and emergency department utilization. Use of flash continuous glucose monitoring (flash CGM) improves glycemic control in type 1 and type 2 diabetes, which may result in lower risk for acute and chronic complications that require emergency services and/or hospitalizations.

Methods

In this retrospective, real-world study, we analyzed IBM MarketScan Commercial Claims and Medicare Supplemental databases to assess the impact of flash CGM on diabetes-related events and hospitalizations in a cohort of 2463 individuals with type 2 diabetes who were on short- or rapid-acting insulin therapy. Outcomes were changes in acute diabetes-related events (ADE) and all-cause inpatient hospitalizations (ACH), occurring during the first 6 months after acquiring the flash CGM system compared with event rates during the 6 months prior to system acquisition. ICD-10 codes were used to identify ADE for hypoglycemia, hypoglycemic coma, hyperglycemia, diabetic ketoacidosis, and hyperosmolarity.

Results

ADE rates decreased from 0.180 to 0.072 events/patient-year (hazard ratio [HR]: 0.39 [0.30, 0.51]; P < 0.001) and ACH rates decreased from 0.420 to 0.283 events/patient-year (HR: 0.68 [0.59 0.78]; P < 0.001). ADE reduction occurred regardless of age or gender.

Conclusions

Acquisition of the flash CGM system was associated with reductions in ADE and ACH. These findings provide support for the use of flash CGM in type 2 diabetes patients treated with short- or rapid-acting insulin therapy to improve clinical outcomes and potentially reduce costs.

The validity of cost-effectiveness analyses of tight glycemic control. A systematic survey of economic evaluations of pharmacological interventions in patients with type 2 diabetes

PURPOSE

Currently available randomized trial evidence has shown no reductions in type 2 diabetes (T2D) complications important to patients with tight glycemic control. Yet, economic analyses consistently find tight glycemic control to be cost-effective. To understand this apparent paradox, we systematically identified and appraised economic analyses of tight glycemic control for T2D.

METHODS

We searched multiple databases from January 2016 to January 2018 for cost-effectiveness or cost-utility analyses of any glucose-lowering treatments for adults with T2D using simulations with long-40 years to lifetime-time horizons. Reviewers selected and appraised each study independently and in duplicate with good reproducibility.

RESULTS

We found 30 analyses, most comparing the glycemic impact of glucose-lowering drugs and applying their impact on HbA1c to model (most commonly IMS CORE or Cardiff T2DM) their impact on the incidence of diabetes-related complication. Models drew from observational evidence of the correlation of HbA1c levels and diabetes-related complication rates; none used estimates of the effect of lowering HbA1c on these outcomes from systematic reviews of randomized trials. Sensitivity analyses, when conducted, demonstrate substantial loss of cost-effectiveness as simulations approach the results seen in these trials.

CONCLUSIONS

Reliance on the association between glycemic control and diabetes-related complications evident in observational studies but not apparent in randomized trial bias the estimates of the cost-effectiveness of interventions to improve glycemic control.

Glucose as the Fifth Vital Sign: A Randomized Controlled Trial of Continuous Glucose Monitoring in a Non-ICU Hospital Setting

OBJECTIVE

The current standard for hospital glucose management is point-of-care (POC) testing. We conducted a randomized controlled trial of real-time continuous glucose monitoring (RT-CGM) compared with POC in a non-intensive care unit (ICU) hospital setting.

RESEARCH DESIGN AND METHODS

A total of 110 adults with type 2 diabetes on a non-ICU floor received RT-CGM with Dexcom G6 versus usual care (UC). RT-CGM data were wirelessly transmitted from the bedside. Hospital telemetry monitored RT-CGM data and notified bedside nursing of glucose alerts and trends. Standardized protocols were used for interventions.

RESULTS

The RT-CGM group demonstrated significantly lower mean glucose (M∆ = -18.5 mg/dL) and percentage of time in hyperglycemia >250 mg/dL (-11.41%) and higher time in range 70-250 mg/dL (+11.26%) compared with UC (P values <0.05). Percentage of time in hypoglycemia was very low.

CONCLUSIONS

RT-CGM can be used successfully in community-based hospital non-ICU settings to improve glucose management. Continuously streaming glucose readings may truly be the fifth vital sign.

Examining Racial Disparities in Diabetes Readmissions in the United States Military Health System

INTRODUCTION

Diabetes is one of the most common chronic conditions in the United States and has a cost burden over $120 billion per year. Readmissions following hospitalization for diabetes are common, particularly in minority patients, who experience greater rates of complications and lower quality healthcare compared to white patients. This study examines disparities in diabetes-related readmissions in the Military Health System, a universally insured, population of 9.5 million beneficiaries, who may receive care from military (direct care) or civilian (purchased care) facilities.

METHODS

The study identified a population of 7,605 adult diabetic patients admitted to the hospital in 2014. Diagnostic codes were used to identify hospital readmissions, and logistic regression was used to analyze associations among race, beneficiary status, patient or sponsor's rank, and readmissions at 30, 60, and 90 days.

RESULTS

A total of 239 direct care patients and 545 purchased care patients were included in our analyses. After adjusting for age and sex, we found no significant difference in readmission rates for black versus white patients; however, we found a statistically significant increase in the likelihood for readmission of Native American/Alaskan Native patients compared to white patients, which persisted in direct care at 60 days (adjusted odds ratio [AOR] 11.51, 95% CI 1.11-119.41) and 90 days (AOR 18.42, 95% CI 1.78-190.73), and in purchased care at 90 days (AOR 4.54, 95% CI 1.31-15.74).

CONCLUSION

Our findings suggest that universal access to healthcare alleviates disparities for black patients, while Native America/Alaskan Native populations may still be at risk of disparities associated with readmissions among diabetic patients in both the closed direct care system and the civilian fee for service purchased care system.

Predictors of 30-day unplanned hospital readmission among adult patients with diabetes mellitus: a systematic review with meta-analysis

Adult patients with diabetes mellitus (DM) represent one-fifth of all 30-day unplanned hospital readmissions but some may be preventable through continuity of care with better DM self-management. We aim to synthesize evidence concerning the association between 30-day unplanned hospital readmission and patient-related factors, insurance status, treatment and comorbidities in adult patients with DM. We searched full-text English language articles in three electronic databases (MEDLINE, Embase and CINAHL) without confining to a particular publication period or geographical area. Prospective and retrospective cohort and case-control studies which identified significant risk factors of 30-day unplanned hospital readmission were included, while interventional studies were excluded. The study participants were aged ≥18 years with either type 1 or 2 DM. The random effects model was used to quantify the overall effect of each factor. Twenty-three studies published between 1998 and 2018 met the selection criteria and 18 provided information for the meta-analysis. The data were collected within a period ranging from 1 to 15 years. Although patient-related factors such as age, gender and race were identified, comorbidities such as heart failure (OR=1.81, 95% CI 1.67 to 1.96) and renal disease (OR=1.69, 95% CI 1.34 to 2.12), as well as insulin therapy (OR=1.45, 95% CI 1.24 to 1.71) and insurance status (OR=1.41, 95% CI 1.22 to 1.63) were stronger predictors of 30-day unplanned hospital readmission. The findings may be used to target DM self-management education at vulnerable groups based on comorbidities, insurance type, and insulin therapy.

Intelligent therapeutic decision support for 30 days readmission of diabetic patients with different comorbidities

The significance of medication therapy in managing comorbid diabetes is vital for maintaining the overall wellness of patients and reducing the cost of healthcare. Thus, using appropriate medication or medication combinations will be necessary for improved person-centred care and reduce complications associated with diagnosis and treatment. This study explains an intelligent decision support framework for managing 30 days unplanned readmission (30_URD) of comorbid diabetes using the Random Forest (RF) algorithm and Bayesian Network (BN) model. After the analysis of the medical records of 101,756 de-identified diabetic patients treated with 21 medications for 28 comorbidity combinations, the optimal medications for minimizing the likelihood of early readmissions were determined. This approach can help for identifying and managing most vulnerable patients thereby giving room to enhance post-discharge monitoring through clinical specialist supports to build critical-self management skills that will minimize the cost of diabetes care.

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.

Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals.

RESULTS

Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

IMPACT OF STRUCTURED INSULIN ORDER SETS ON INPATIENT HYPOGLYCEMIA AND GLYCEMIC CONTROL

Objective: In hospitalized patients, glycemic excursions outside recommended glycemic targets have been associated with increased morbidity and mortality. Despite recommendations to avoid use of correctional insulin alone for managing hyperglycemia, this approach remains common. We performed a quality improvement project aimed at both reducing hypoglycemic events and promoting increased use of basal insulin by updating our insulin order sets to reflect clinical practice guideline recommendations. Methods: Brooke Army Medical Center correctional insulin order sets were modified to reflect higher treatment thresholds and targets, and a basal insulin order was added with a recommended weight-based starting dose. Pre- and postintervention analyses were performed. Patients were included if they were prescribed subcutaneous insulin during their hospital stay. The following outcomes were measured: (1) glucose levels, and (2) prescriptions for basal insulin. Results: A significant reduction in hypoglycemia events was noted following the intervention (glucose <70 mg/dL: 9.2% pre-intervention vs. 8.8% postintervention; glucose <55 mg/dL: 4.2% pre-intervention vs. 2.2% postintervention). When excluding patients that were ordered correctional insulin alone but did not receive a dose, an increase in basal insulin use was seen (50% pre-intervention vs. 61% postintervention). Rates and severity of hyperglycemia (glucose >180 mg/dL) remained unchanged. Conclusion: The alteration in insulin order set parameters resulted in a significant reduction in hypoglycemia without significant increases in hyperglycemia. Although basal insulin use increased, optimal dosing recommendations were not often utilized. Further interventions are necessary to reduce hyperglycemia. Abbreviations: CPOE = computerized provider order entry; EMR = electronic medical record; HbA1c = hemoglobin A1c; LOS = length of stay; QI = quality improvement; SSI = sliding scale insulin.

Periodontal Treatment Experience Associated with Oral Health-Related Quality of Life in Patients with Poor Glycemic Control in Type 2 Diabetes: A Case-Control Study

Severe periodontitis is a risk factor for poor glycemic control. The appropriate medical treatment and plaque control of periodontitis positively affects blood-sugar control in diabetes patients. We aimed to identify the factors associated with glycemic control and examine the periodontal treatment (PT) experience and oral health-related quality of life (OHQoL) for patients with poor glycemic control in type 2 diabetes mellitus (T2DM). This multicenter case–control study recruited 242 patients with poor glycemic control and 198 patients with good glycemic control. We collected patients’ information through face-to-face interviews using a structured questionnaire. The Oral Health Impact Profile-14 (OHIP-14) was used to measure OHQoL. Based on PT status, the patients were classified into three groups: a non-periodontal disease group, a PT group, and a non-PT (NPT) group. Regression models were used to analyze the data. No interdental cleaning (adjusted odds ratio (aOR) = 1.78) and positive attitudes toward periodontal health (aOR = 1.11) were significantly more likely to be associated with poor glycemic control in patients with T2DM. The PT group had a significantly lower OHIP-14 score than the NPT group (6.05 vs. 9.02, p < 0.001), indicating a better OHQoL among patients with poorly controlled T2DM. However, the OHQoL did not differ significantly in patients with well-controlled T2DM between the PT and NPT groups. This suggested that diabetic patients with poor glycemic control must improve periodontal care practices and receive proper PT, if necessary, to improve their OHQoL.

Racial and Ethnic Differences in 30-Day Hospital Readmissions Among US Adults With Diabetes

IMPORTANCE

Differences in readmission rates among racial and ethnic minorities have been reported, but data among people with diabetes are lacking despite the high burden of diabetes and its complications in these populations.

OBJECTIVES

To examine racial/ethnic differences in all-cause readmission among US adults with diabetes and categorize patient- and system-level factors associated with these differences.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study includes 272 758 adult patients with diabetes, discharged alive from the hospital between January 1, 2009, and December 31, 2014, and stratified by race/ethnicity. An administrative claims data set of commercially insured and Medicare Advantage beneficiaries across the United States was used. Data analysis took place between October 2016 and February 2019.

MAIN OUTCOMES AND MEASURES

Unplanned all-cause readmission within 30 days of discharge and individual-, clinical-, economic-, index hospitalization-, and hospital-level risk factors for readmission.

RESULTS

A total of 467 324 index hospitalizations among 272 758 adults with diabetes (mean [SD] age, 67.7 [12.7]; 143 498 [52.6%] women) were examined. The rates of 30-day all-cause readmission were 10.2% (33 683 of 329 264) among white individuals, 12.2% (11 014 of 89 989) among black individuals, 10.9% (4151 of 38 137) among Hispanic individuals, and 9.9% (980 of 9934) among Asian individuals (P < .001). After adjustment for all factors, only black patients had a higher risk of readmission compared with white patients (odds ratio, 1.05; 95% CI, 1.02-1.08). This increased readmission risk among black patients was sequentially attenuated, but not entirely explained, by other demographic factors, comorbidities, income, reason for index hospitalization, or place of hospitalization. Compared with white patients, both black and Hispanic patients had the highest observed-to-expected (OE) readmission rate ratio when their income was low (annual household income <$40 000 among black patients: OE ratio, 1.11; 95% CI, 1.09-1.14; among Hispanic patients: OE ratio, 1.11; 95% CI, 1.07-1.16) and when they were hospitalized in nonprofit hospitals (black patients: OE ratio, 1.10; 95% CI, 1.08-1.12; among Hispanic patients: OE ratio, 1.08; 95% CI, 1.05-1.12), academic hospitals (black patients: OE ratio, 1.16; 95% CI, 1.13-1.20; Hispanic patients: OE ratio, 1.12; 95% CI, 1.06-1.19), or large hospitals (ie, with ≥400 beds; black patients: OE ratio, 1.11; 95% CI, 1.09-1.14; Hispanic patients: OE ratio, 1.09; 95% CI, 1.04-1.14).

CONCLUSIONS AND RELEVANCE

In this study, black patients with diabetes had a significantly higher risk of readmission than members of other racial/ethnic groups. This increased risk was most pronounced among lower-income patients hospitalized in nonprofit, academic, or large hospitals. These findings reinforce the importance of identifying and addressing the many reasons for persistent racial/ethnic differences in health care quality and outcomes.

Severe Hypoglycemia Attributable to Intensive Glucose-Lowering Therapy Among US Adults With Diabetes: Population-Based Modeling Study, 2011-2014

OBJECTIVE

To estimate the contemporary prevalence of intensive glucose-lowering therapy among US adults with diabetes and model the number of hypoglycemia-related emergency department (ED) visits and hospitalizations that are attributable to such intensive treatment.

PATIENTS AND METHODS

US adults with diabetes and glycated hemoglobin (HbA_1c) levels less than 7.0% who were included in the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2014. Participants were categorized as clinically complex if 75 years or older or with 2 or more activities of daily living limitations, end-stage renal disease, or 3 or more chronic conditions. Intensive treatment was defined as any glucose-lowering medications with HbA_1c levels of 5.6% or less or 2 or more with HbA_1c levels of 5.7% to 6.4%. First, we quantified the proportion of clinically complex and intensively treated individuals in the NHANES population. Then, we modeled the attributable hypoglycemia-related ED visits/hospitalizations over a 2-year period based on published data for event risk.

RESULTS

Almost half (48.8% [10,719,057 of 21,980,034]) of US adults with diabetes (representing 10.7 million US adults) had HbA_1c levels less than 7.0%. Among them, 32.3% (3,466,713 of 10,719,057) were clinically complex, and 21.6% (2,309,556 of 10,719,057) were intensively treated, with no difference by clinical complexity. Over a 2-year period, we estimated 31,511 hospitalizations and 30,954 ED visits for hypoglycemia in this population; of these, 4774 (95% CI, 954-9714) hospitalizations and 4804 (95% CI, 862-9851) ED visits were attributable to intensive treatment.

CONCLUSION

Intensive glucose-lowering therapy, particularly among vulnerable clinically complex adults, is strongly discouraged because it may lead to hypoglycemia. However, intensive treatment was equally prevalent among US adults, irrespective of clinical complexity. Over a 2-year period, an estimated 9578 hospitalizations and ED visits for hypoglycemia could be attributed to intensive diabetes treatment, particularly among clinically complex patients. Patients at risk for hypoglycemia may benefit from treatment deintensification to reduce hypoglycemia risk and treatment burden.

[Hospital diabetes management (Update 2019)]

This position statement presents the recommendations of the Austrian Diabetes Association for diabetes management of adult patients during inpatient stay. It is based on the current evidence with respect to blood glucose targets, insulin therapy and treatment with oral antidiabetic drugs during inpatient hospitalization. Additionally, special circumstances such as intravenous insulin therapy, concomitant therapy with glucocorticoids and use of diabetes technology during hospitalization are discussed.

Impact of a Pharmacy-Initiated Inpatient Diabetes Patient Education Program on 30-Day Readmission Rates

Background:

In October 2012, a pharmacy-driven Inpatient Diabetes Patient Education (IDPE) program was implemented at the University of Toledo Medical Center (UTMC).

Objective:

To determine the difference in 30-day hospital readmission rates for patients who receive IDPE compared to those who do not.

Methods:

This retrospective cohort was completed at UTMC. Patients admitted between October 1, 2012, and September 30, 2013, were included if they were ≥18 years and had one of the following: (1) diagnosis of diabetes mellitus, (2) blood glucose >200 mg/dL (>11.11 mmol/L) on admission, or (3) hemoglobin A1C of >6.5% (>48 mmol/mol). Patients who received IDPE from a pharmacist or student pharmacist (intervention group) were compared to patients who did not receive IDPE (control group).

Results:

The 30-day readmission rate was 13.2% for the intervention group (n = 364) and 21.5% for the control group (n = 149) ( P = .023). Average time to 30-day readmission was 13.1 (±8.3) days for the IDPE group and 11.9 (±7.9) days for the control group. There was no significant difference in diabetes-related readmission between the intervention and control groups (25.5% vs 21.9%).

Conclusions:

An IDPE program delivered primarily by pharmacists and student pharmacists significantly reduced 30-day readmission rates among patients with diabetes.

Excess Burden of Mental Illness and Hospitalization in Young-Onset Type 2 Diabetes: A Population-Based Cohort Study

BACKGROUND

Type 2 diabetes (T2D) increases hospitalization risk. Young-onset T2D (YOD) (defined as onset before age 40 years) is associated with excess morbidity and mortality, but its effect on hospitalizations is unknown.

OBJECTIVE

To determine hospitalization rates among persons with YOD and to examine the effect of age at onset on hospitalization risk.

DESIGN

Prospective cohort study.

SETTING

Hong Kong.

PARTICIPANTS

Adults aged 20 to 75 years in population-based (2002 to 2014; n = 422 908) and registry-based (2000 to 2014; n = 20 886) T2D cohorts.

MEASUREMENTS

All-cause and cause-specific hospitalization rates. Negative binomial regression models estimated effect of age at onset on hospitalization rate and cumulative bed-days from onset to age 75 years for YOD.

RESULTS

Patients with YOD had the highest hospitalization rates by attained age. In the registry cohort, 36.8% of YOD bed-days before age 40 years were due to mental illness. The adjusted rate ratios showed increased hospitalization in YOD versus usual-onset T2D (onset at age ≥40 years) (all-cause, 1.8 [95% CI, 1.7 to 2.0]; renal, 6.7 [CI, 4.2 to 10.6]; diabetes, 3.7 [CI, 3.0 to 4.6]; cardiovascular, 2.1 [CI, 1.8 to 2.5]; infection, 1.7 [CI, 1.4 to 2.1]; P < 0.001 for all). Models estimated that intensified risk factor control in YOD (hemoglobin A1c level <6.2%, systolic blood pressure <120 mm Hg, low-density lipoprotein cholesterol level <2.0 mmol/L [<77.3 mg/dL], triglyceride level <1.3 mmol/L [<115.1 mg/dL], waist circumference of 85 cm [men] or 80 cm [women], and smoking cessation) was associated with a one-third reduction in cumulative bed-days from onset to age 75 years (97 to 65 bed-days).

LIMITATION

Possible residual confounding.

CONCLUSION

Adults with YOD have excess hospitalizations across their lifespan compared with persons with usual-onset T2D, including an unexpectedly large burden of mental illness in young adulthood. Efforts to prevent YOD and intensify cardiometabolic risk factor control while focusing on mental health are urgently needed.

PRIMARY FUNDING SOURCE

Asia Diabetes Foundation.

Recurrent hospitalizations for severe hypoglycemia and hyperglycemia among U.S. adults with diabetes

AIMS

Examine 30-day readmissions for recurrent hypoglycemia and hyperglycemia in a national cohort of adults with diabetes.

METHODS

Retrospective analysis of data from OptumLabs Data Warehouse for all adults with diabetes hospitalized January 1, 2009 to December 31, 2014 with a principal diagnosis of hypoglycemia or hyperglycemia. We examined the rates and risk factors of 30-day readmissions for hypoglycemia and hyperglycemia.

RESULTS

After 6419 index hypoglycemia hospitalizations, 1.2% were readmitted for recurrent hypoglycemia, 0.2% for hyperglycemia, and 8.6% for other causes. Multimorbidity was the strongest predictor of recurrent hypoglycemia. After 6872 index hyperglycemia hospitalizations, 4.0% were readmitted for recurrent hyperglycemia, 0.4% for hypoglycemia, and 5.4% for other causes. Recurrent hyperglycemia was less likely in older patients (OR 0.6, 95% CI 0.5-0.9 for 45-64 vs. <45 years) and with the addition of a new glucose-lowering medication at index discharge (OR 0.40; 95% CI 0.2-0.7). New hypoglycemia readmissions were most likely among patients ≥75 years (OR 13.3, 95% CI 2.4-73.4, vs. <45 years).

CONCLUSIONS

Patients hospitalized for hyperglycemia are often readmitted for recurrent hyperglycemia, while patients hospitalized for hypoglycemia are generally readmitted for unrelated causes. Early recognition of high risk patients may identify opportunities to improve post-discharge management and reduce these events.

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.

The Bidirectional Association Between Depression and Severe Hypoglycemic and Hyperglycemic Events in Type 1 Diabetes

OBJECTIVE

Severe hyperglycemia and hypoglycemia ("severe dysglycemia") are serious complications of type 1 diabetes (T1D). Depression has been associated with severe dysglycemia in type 2 diabetes but has not been thoroughly examined specifically in T1D. We evaluated bidirectional associations between depression and severe dysglycemia among older people with T1D.

RESEARCH DESIGN AND METHODS

We abstracted depression and severe dysglycemia requiring emergency room visit or hospitalization from medical health records in 3,742 patients with T1D during the study period (1996-2015). Cox proportional hazards models estimated the associations between depression and severe dysglycemia in both directions, adjusting for demographics, micro- and macrovascular complications, and HbA_1c.

RESULTS

During the study period, 41% had depression and 376 (11%) and 641 (20%) had hyperglycemia and hypoglycemia, respectively. Depression was strongly associated with a 2.5-fold increased risk of severe hyperglycemic events (hazard ratio [HR] 2.47 [95% CI 2.00, 3.05]) and 89% increased risk of severe hypoglycemic events (HR 1.89 [95% CI 1.61, 2.22]). The association was strongest within the first 6 months (HR_{hyperglycemia} 7.14 [95% CI 5.29, 9.63]; HR_hypoglycemia 5.58 [95% CI 4.46, 6.99]) to 1 year (HR_{hyperglycemia} 5.16 [95% CI 3.88, 6.88]; HR_hypoglycemia 4.05 [95% CI 3.26, 5.04]) after depression diagnosis. In models specifying severe dysglycemia as the exposure, hyperglycemic and hypoglycemic events were associated with 143% (HR 2.43 [95% CI 2.03, 2.91]) and 74% (HR 1.75 [95% CI 1.49, 2.05]) increased risk of depression, respectively.

CONCLUSIONS

Depression and severe dysglycemia are associated bidirectionally among patients with T1D. Depression greatly increases the risk of severe hypoglycemic and hyperglycemic events, particularly in the first 6 months to 1 year after diagnosis, and depression risk increases after severe dysglycemia episodes.