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

ABSTRACT: 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.

SUBMITTER: McCoy RG

PROVIDER: S-EPMC6015781 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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

McCoy Rozalina G RG Herrin Jeph J Lipska Kasia J KJ Shah Nilay D ND

Journal of diabetes and its complications 20180424 7

<h4>Aims</h4>Examine 30-day readmissions for recurrent hypoglycemia and hyperglycemia in a national cohort of adults with diabetes.<h4>Methods</h4>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.<h4>Results</h4>After 6419 index hypoglycemia hospitali ...[more]

PMID: 29751961

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Project description:ImportanceIntensive glucose-lowering treatment among patients with non-insulin-requiring type 2 diabetes may increase the risk of hypoglycemia.ObjectivesTo estimate the prevalence of intensive treatment and the association between intensive treatment, clinical complexity, and incidence of severe hypoglycemia among adults with type 2 diabetes who are not using insulin.Design, setting, and participantsRetrospective analysis of administrative, pharmacy, and laboratory data from the OptumLabs Data Warehouse from January 1, 2001, through December 31, 2013. The study included nonpregnant adults 18 years or older with type 2 diabetes who achieved and maintained a hemoglobin A1c (HbA1c) level less than 7.0% without use of insulin and had no episodes of severe hypoglycemia or hyperglycemia in the prior 12 months.Main outcomes and measuresRisk-adjusted probability of intensive treatment and incident severe hypoglycemia, stratified by patient clinical complexity. Intensive treatment was defined as use of more glucose-lowering medications than recommended by practice guidelines at specific index HbA1c levels. Severe hypoglycemia was ascertained by ambulatory, emergency department, and hospital claims for hypoglycemia during the 2 years after the index HbA1c test. Patients were categorized as having high vs low clinical complexity if they were 75 years or older, had dementia or end-stage renal disease, or had 3 or more serious chronic conditions.ResultsOf 31 542 eligible patients (median age, 58 years; interquartile range, 51-65 years; 15 483 women [49.1%]; 18 188 white [57.7%]), 3910 (12.4%) had clinical complexity. The risk-adjusted probability of intensive treatment was 25.7% (95% CI, 25.1%-26.2%) in patients with low clinical complexity and 20.8% (95% CI, 19.4%-22.2%) in patients with high clinical complexity. In patients with low clinical complexity, the risk-adjusted probability of severe hypoglycemia during the subsequent 2 years was 1.02% (95% CI, 0.87%-1.17%) with standard treatment and 1.30% (95% CI, 0.98%-1.62%) with intensive treatment (absolute difference, 0.28%; 95% CI, -0.10% to 0.66%). In patients with high clinical complexity, intensive treatment significantly increased the risk-adjusted probability of severe hypoglycemia from 1.74% (95% CI, 1.28%-2.20%) with standard treatment to 3.04% (95% CI, 1.91%-4.18%) with intensive treatment (absolute difference, 1.30%; 95% CI, 0.10%-2.50%).Conclusions and relevanceMore than 20% of patients with type 2 diabetes received intensive treatment that may be unnecessary. Among patients with high clinical complexity, intensive treatment nearly doubles the risk of severe hypoglycemia.

Project description:BackgroundHospital admissions for severe hypoglycemia are associated with significant healthcare costs, decreased quality of life, and increased morbidity and mortality, especially for older adults with diabetes. Understanding the reasons for hypoglycemia hospitalization is essential for the development of effective interventions; yet, the causes and precipitants of hypoglycemia are not well understood.MethodsWe conducted a qualitative study of non-nursing home patients aged 65 years or older without cognitive dysfunction admitted to a single tertiary-referral hospital with diabetes-related hypoglycemia. During the hospitalization, we conducted one-on-one, in-depth, semi-structured interviews to explore: (1) experiences with diabetes management among patients hospitalized for severe hypoglycemia; and (2) factors contributing and leading to the hypoglycemic event. Major themes and sub-themes were extracted using the constant comparative method by 3 study authors.ResultsAmong the 17 participants interviewed, the mean age was 78.9 years of age, 76.5% were female, 64.7% African American, 64.7% on insulin, and patients had an average of 13 chronic conditions. Patients reported: (1) surprise at hypoglycemia despite living with diabetes for many years; (2) adequate support, knowledge, and preparedness for hypoglycemia; (3) challenges balancing a diet that minimizes hyperglycemia and prevents hypoglycemia; (4) the belief that hyperglycemia necessitates medical intervention, but hypoglycemia does not; and (5) tension between clinician-prescribed treatment plans and self-management based on patients' experience. Notably, participants did not report the previously cited reasons for hypoglycemia, such as food insecurity, lack of support or knowledge, or treatment errors.ConclusionsOur findings suggest that some hypoglycemic events may not be preventable, but in order to reduce the risk of hypoglycemia in older individuals at risk: (1) healthcare systems need to shift from their general emphasis on the avoidance of hyperglycemia towards the prevention of hypoglycemia; and (2) clinicians and patients need to work together to design treatment regimens that fit within patient capacity and are flexible enough to accommodate life's demands.

Project description:BackgroundOlder adults with diabetes are at high risk of severe hypoglycemia (SH). Many machine-learning (ML) models predict short-term hypoglycemia are not specific for older adults and show poor precision-recall. We aimed to develop a multidimensional, electronic health record (EHR)-based ML model to predict one-year risk of SH requiring hospitalization in older adults with diabetes.Methods and findingsWe adopted a case-control design for a retrospective territory-wide cohort of 1,456,618 records from 364,863 unique older adults (age ≥65 years) with diabetes and at least 1 Hong Kong Hospital Authority attendance from 2013 to 2018. We used 258 predictors including demographics, admissions, diagnoses, medications, and routine laboratory tests in a one-year period to predict SH events requiring hospitalization in the following 12 months. The cohort was randomly split into training, testing, and internal validation sets in a 7:2:1 ratio. Six ML algorithms were evaluated including logistic-regression, random forest, gradient boost machine, deep neural network (DNN), XGBoost, and Rulefit. We tested our model in a temporal validation cohort in the Hong Kong Diabetes Register with predictors defined in 2018 and outcome events defined in 2019. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC) statistics, and positive predictive value (PPV). We identified 11,128 SH events requiring hospitalization during the observation periods. The XGBoost model yielded the best performance (AUROC = 0.978 [95% CI 0.972 to 0.984]; AUPRC = 0.670 [95% CI 0.652 to 0.688]; PPV = 0.721 [95% CI 0.703 to 0.739]). This was superior to an 11-variable conventional logistic-regression model comprised of age, sex, history of SH, hypertension, blood glucose, kidney function measurements, and use of oral glucose-lowering drugs (GLDs) (AUROC = 0.906; AUPRC = 0.085; PPV = 0.468). Top impactful predictors included non-use of lipid-regulating drugs, in-patient admission, urgent emergency triage, insulin use, and history of SH. External validation in the HKDR cohort yielded AUROC of 0.856 [95% CI 0.838 to 0.873]. Main limitations of this study included limited transportability of the model and lack of geographically independent validation.ConclusionsOur novel-ML model demonstrated good discrimination and high precision in predicting one-year risk of SH requiring hospitalization. This may be integrated into EHR decision support systems for preemptive intervention in older adults at highest risk.

Project description:AimsMild cognitive dysfunction has been identified in children and adults with type 1 diabetes, but most studies have failed to find a relationship between severe hypoglycemia and cognition, despite reports of such associations in older adults with type 2 diabetes. Focusing on older adults with type 1 diabetes, we examined the associations between cognitive performance and recent episodes of severe hypoglycemia, retinal vessel diameters and the presence of micro- and macrovascular complications.MethodsCognitive functioning was assessed in 244 participants enrolled in the Wisconsin Epidemiologic Study of Diabetic Retinopathy. The mean (SD; range) age at assessment in 2012-14 was 55.2 (8.3; 37-82) years and the mean (SD) duration of diabetes was 41.1 (5.6) years. Three cognitive domains were assessed in this cross-sectional study: mental efficiency and executive function, nonverbal memory, and verbal memory.ResultsMultivariate modeling demonstrated that although age and/or education are most strongly associated with performance on measures of mental efficiency, three diabetes-related variables were also associated with poorer test scores: an episode of severe hypoglycemia in the past year (β=-0.360 [95% CI, -0.672, -0.047]), retinal arteriolar and venular diameters (β=0.140 [95% CI, 0.062, 0.219]; β=-0.127 [95% CI -0.207, -0.047]), and carotid artery plaque (β=-0.372 [95% CI -0.741, -0.003]). In addition, recent severe hypoglycemia was associated with poorer nonverbal memory (β=-0.522 [95% CI, -0.849, -0.194]).ConclusionsFor middle-aged and older adults with long-duration type 1 diabetes, poorer cognition was associated with a recent episode of severe hypoglycemia as well as with the presence of micro- and/or macrovascular conditions. Given the increasing numbers of aging adults with type 1 diabetes, future longitudinal studies are needed to identify causality and to determine whether diabetes management techniques that reduce the onset or severity of vascular complications and hypoglycemia can also reduce the risk of cognitive dysfunction in this population.

Project description:Importance:Severe hypoglycemia is a serious and potentially preventable complication of diabetes, with some of the most severe episodes requiring emergency department (ED) care or hospitalization. A variety of health conditions increase the risk of hypoglycemia. People with diabetes often have multiple comorbidities, and the association of such multimorbidity with hypoglycemia risk in the context of other risk factors is uncertain. Objective:To examine the associations of age, cumulative multimorbidity, glycated hemoglobin (HbA1c) level, and use of glucose level-lowering medication with hypoglycemia-related ED visits and hospitalizations. Design, Setting, and Participants:Cohort study of claims and laboratory data from OptumLabs Data Warehouse, an administrative claims database of commercially insured and Medicare Advantage beneficiaries in the United States. Participants were adults (aged ?18 years) with diabetes who had an available HbA1c level result in 2015. Data from January 1, 2014, to December 31, 2016, were analyzed. Final analyses were conducted from December 2017 to September 2018. Main Outcomes and Measures:This study calculated rates of hypoglycemia-related ED visits and hospitalizations during the year after the index HbA1c level was obtained, stratified by patient demographic characteristics, diabetes type, comorbidities (from 16 guideline-specified high-risk conditions), index HbA1c level, and glucose level-lowering medication use. The association of each variable with hypoglycemia-related ED and hospital care was examined using multivariable Poisson regression analysis overall and by diabetes type. Results:The study cohort was composed of 201?705 adults with diabetes (mean [SD] age, 65.8 [12.1] years; 102?668 [50.9%] women; 118?804 [58.9%] white; mean [SD] index HbA1c level, 7.2% [1.5%]). Overall, there were 9.06 (95% CI, 8.64-9.47) hypoglycemia-related ED visits and hospitalizations per 1000 persons per year. The risk of hypoglycemia-related ED visits and hospitalizations was increased by age 75 years or older (incidence rate ratio [IRR], 1.56 [95% CI, 1.23-2.02] vs 18-44 years), black race/ethnicity (IRR, 1.30 [95% CI, 1.16-1.46] vs white race/ethnicity), lower annual household income (IRR, 0.63 [95% CI, 0.53-0.74] for ?$100?000 vs <$40?000), number of comorbidities (increasing from IRR of 1.66 [95% CI, 1.42-1.95] in the presence of 2 comorbidities to IRR of 4.12 [95% CI, 3.07-5.51] with ?8 comorbidities compared with ?1), prior hypoglycemia-related ED visit or hospitalization (IRR, 6.60 [95% CI, 5.77-7.56]), and glucose level-lowering treatment regimen (IRR, 6.73 [95% CI, 4.93-9.22] for sulfonylurea; 12.53 [95% CI, 8.90-17.64] for basal insulin; and 27.65 [95% CI, 20.32-37.63] for basal plus bolus insulin compared with other medications). Independent of these factors, having type 1 diabetes was associated with a 34% increase in the risk of hypoglycemia-related ED visits or hospitalizations (IRR, 1.34 [95% CI, 1.15-1.55]). The index HbA1c level was associated with hypoglycemia-related ED visits and hospitalizations when both low (IRR, 1.45 [95% CI, 1.12-1.87] for HbA1c level ?5.6% vs 6.5%-6.9%) and high (IRR, 1.24 [95% CI, 1.02-1.50] for HbA1c level ?10%). Conclusions and Relevance:In this cohort study of adults with diabetes, the risk of an ED visit or hospitalization for hypoglycemia appeared to be highest among patients with type 1 diabetes, multiple comorbidities, prior severe hypoglycemia, and sulfonylurea and/or insulin use. At-risk patients may benefit from individualized treatment regimens to decrease their risk of hypoglycemia.

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

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

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