Diabetes-related Hospitalizations Research Articles

Recurrence of Diabetic Foot Complications: A Domino Effect Leading to Lethal Consequences - Insights from a National Longitudinal Study

Abstract Background Foot complications are common in people with diabetes mellitus (DM), leading to increased healthcare utilization, heightened mortality risk, and notable recurrence rates even after treatment. This retrospective cohort study aimed to investigate the impact of repeated occurrence of DM-related foot complications on the risk of all-cause mortality and to identify the potential risk factors associated with repeated events. Methods People with DM admitted with foot complications (ulcer, skin and soft tissue infection or osteomyelitis) from 2012 to 2014 were identified from Taiwan’s National Health Insurance Research Database, with a three-year follow-up for repeated events. We categorized the study subjects based on their cumulative number of hospital admission with foot complications. Logistic regression was conducted to explore the potential risk factors associated with repeated diabetic foot events. Kaplan-Meier curves and Cox proportional hazard models were used to examine the associations between repeated diabetic foot events and all-cause mortality. Results In this study, 28,754 eligible individuals were enrolled and classified into three groups: no repeated diabetic foot events (76.1%), one repeated event (16.0%), and two or more repeated events (7.9%). Logistic regression revealed that advanced age, males, and those with congestive heart failure, dyslipidemia, hypertension, nephropathy, retinopathy, neuropathy, peripheral vascular disease, diabetes-related preventable hospitalizations, and outpatient visits due to diabetic foot were significantly associated with repeated events of diabetic foot complications. Compared to those with no repeated events, the adjusted hazard ratio (95% CI) for all-cause mortality were 1.26 (1.19-1.34) for one repeated event and 1.36 (1.26-1.47) for two or more repeated events. Conclusions The significant association between repeated diabetic foot and elevated mortality risk highlights the critical necessity for proactive and targeted patient care within clinical practice. More research to delve into the predictive factors related to the repeated occurrence of diabetic foot is needed to provide additional insights for prevention strategies.

Reduction in Diabetes-Related Hospitalizations and Medical Costs After Dexcom G6 Continuous Glucose Monitor Initiation in People with Type 2 Diabetes Using Intensive Insulin Therapy.

Some people with type 2 diabetes (T2D) require intensive insulin therapy to manage their diabetes. This can increase the risk of diabetes-related hospitalizations. We hypothesize that initiation of real-time continuous glucose monitoring (RT-CGM), which continuously measures a user's glucose values and provides threshold- and trend-based alerts, will reduce diabetes-related emergency department (ED) and inpatient hospitalizations and concomitant costs. A retrospective analysis of US healthcare claims data using Optum's de-identified Clinformatics® Data Mart database was performed. The cohort consisted of commercially insured, CGM-naïve individuals with T2D who initiated Dexcom G6 RT-CGM system between August 1, 2018, and March 31, 2021. Twelve months of continuous health plan enrollment before and after RT-CGM initiation was required to capture baseline and follow-up rates of diabetes-related hospitalizations and associated healthcare resource utilization (HCRU) costs. Analyses were performed for claims with a diabetes-related diagnosis code in either (1) any position or (2) first or second position on the claim. A total of 790 individuals met the inclusion criteria. The average age was 52.8 (10.5) [mean (SD)], 53.3% were male, and 76.3% were white. For claims with a diabetes-related diagnosis code in any position, the number of individuals with ≥ 1 ED visit decreased by 30.0% (p = 0.01) and with ≥ 1 inpatient visit decreased by 41.5% (p < 0.0001). The number of diabetes-related visits and average number of visits per person similarly decreased by at least 31.4%. Larger relative decreases were observed for claims with a diabetes-related diagnosis code in the first or second position on the claim. Total diabetes-related costs expressed as per-person-per-month (PPPM) decreased by $341 PPPM for any position and $330 PPPM for first or second position. Initiation of Dexcom G6 among people with T2D using intensive insulin therapy was associated with a significant reduction in diabetes-related ED and inpatient visits and related HCRU costs. Expanded use of RT-CGM could augment these benefits and result in further cost reductions.

Treatment approaches and costs associated with diabetes clinical metrics as measured by Healthcare Effectiveness Data and Information Set (HEDIS)

BackgroundThe clinical outcomes of diabetes can be influenced by primary care providers’ (PCP) treatment approaches. This study explores the association between PCP approaches to management and performance measured by established diabetes metrics and related costs.MethodsIn phase one, Electronic Medical Records were used to extract diabetes related metrics using Healthcare Effectiveness Data and Information Set (HEDIS), for patients with diabetes who had office visits to 44 PCP practices from April 2019 to March 2020. Using those metrics and scoring system, PCP practices were ranked and then categorized into high- and low-performing groups (top and bottom 25%, n = 11 each), with a total of 19,059 clinic visits by patients with a diagnosis of diabetes. Then extensive analysis was performed to evaluate a correlation between treatment approaches and diabetes outcomes across the top and bottom performing practices. In phase 2, patients with diabetes who were attributed to the aforementioned PCP practices were identified in a local health plan claims data base (a total of 3,221 patients), and the allowed amounts from their claims were used to evaluate differences in total and diabetes-related healthcare costs by providers’ performance.ResultsComparing 10,834 visits in high-performing practices to 8,235 visits in low-performing practices, referrals to certified diabetes care and education specialists and provider-to-provider electronic consults (e-consults) were higher in high-performing practices (Z = 6.06, p < .0001), while traditional referrals were higher in low-performing practices (Z = -6.94, p < .0001). The patient-to-provider ratio was higher in the low-performing group (M = 235.23) than in the high-performing group (M = 153.26) (Z = -2.82, p = .0048). Claims data analysis included 1,825 and 1,396 patients from high- and low-performing providers, respectively. The patient-to-provider ratio was again higher in the low-performing group (p = .009, V = 0.62). Patients receiving care from lower-performing practices were more likely to have had a diabetes-related hospital observation (5.7% vs. 3.9%, p = .02; V = 0.04) and higher diabetes-related care costs (p = .002; d = − 0.07); these differences by performance status persisted when controlling for differences in patient and physician characteristics. Patients seeing low-performing providers had higher Charlson Comorbidity Index scores (Mdn = 3) than those seeing high-performing providers (Mdn = 2).ConclusionsReferrals to the CDCES and e-Consult were associated with better measured diabetes outcomes, as were certain aspects of cost and types of hospital utilization. Higher patients to providers ratio and patients with more comorbidities were observed in low performing group.

The variation in preventable hospitalization in patients with type 2 diabetes in Kentucky before and after the Medicaid expansion.

Hospitalizations are more resource intensive and expensive than outpatient care. Therefore, type 2 diabetes-related preventable hospitalization are a major topic of research efficiency in the healthcare system. Analyze county level variation in type 2 diabetes-related preventable hospitalization rates in Kentucky before the Medicaid expansion (2010-2013) and after the Medicaid expansion (2014-2017). Geographic mapping and cluster analysis. Data for a state of the United States of America. We used the KID data to generate geographic mapping for type 2 diabetes-related preventable hospitalizations to visualize rates. We included all Kentucky discharges of age 18 years and older with the ICD9/10 principal diagnosis code for type 2 diabetes. Then, we conducted cluster analysis techniques to compare county-level variation in type 2 diabetes-related preventable hospitalization rates across Kentucky counties pre- and post-Medicaid expansion. County type 2 diabetes-related preventable hospitalization pre- and post-Medicaid expansion. From 2010-2017, type 2 diabetes-related preventable hospitalization discharge rates reduced significantly in the period of the post-Medicaid expansion (P=.001). The spatial statistics analysis revealed a significant spatial clustering of counties with similar rates of type 2 diabetes-related preventable hospitalization in the south, east, and southeastern Kentucky pre- and post-Medicaid expansion (positive z-score and positive Moran's Index value (P>.05). Also, there was a significant clustering of counties with low type 2 diabetes-related preventable hospitalization rates in the north, west, and central regions of the state pre-Medicaid expansion and post-Medicaid expansion (positive z-score and positive Moran's Index value (P>.05). Kentucky counties in the southeast have experienced a significant clustering of highly avoidable hospitalization rates during both periods. Focusing on the vulnerable counties and the economic inequality in Kentucky could lead to efforts to lowering future type 2 diabetes-related preventable hospitalization rates. We used de-identified data which does not provide insights into the frequency of hospitalizations per patient. An individual patient may be hospitalized several times and counted as several individuals.

Predictions of Early Hospitalization of Diabetes Patients Based on Deep Learning: A Review

Unmanaged diabetes can result in a number of complications that need to be hospitalised. Diabetes is a chronic disorder. With preventive treatment, outcomes may be improved through early prediction of diabetes-related hospitalisation using data-driven algorithms. Here, we examine recent advances in deep learning methods for anticipating readmissions and unexpected hospital stays in adult patients with diabetes. Firstly, we present an overview of the main factors that indicate the need for hospitalisation due to diabetic complications. The research on hospitalisation risk prediction using structured health data, such as demographics, prescriptions, test results, etc., using conventional machine learning techniques is then summarised. Using data from insurance claims and electronic health records, we then examine current research that has used deep learning models. It is emphasised that longitudinal data can be included using recurrent neural networks. Model architectures, training methods, and important data modalities are covered. The assessment also addresses deployment difficulty and the model's performance assessment on real-world datasets. Ultimately, potential paths forward include hybrid models that integrate data diversity, explainable predictions, and clinical knowledge. In order to provide evidence-based predictions of the risk of hospitalisation and readmission for diabetes patients, we examine the potential and constraints of recently developed deep learning algorithms in this review.

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

There is a heightened risk of glycemic variability in patients with diabetes and chronic kidney disease (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. 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 1/1/2016 and 3/31/2022 were identified. NDC and HCPCS codes were used to identify CGM device use and ICD-10 codes were used to identify CKD diagnosis and categorize healthcare encounters. Rates of diabetes-related hospitalizations were obtained, and multivariable logistic regression analyses revealed predictors of hypoglycemic and hyperglycemic encounters. A total of 8,959insulin-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 and neuropathy (for hyperglycemia). Use of CGM or glucagon-like peptide-1 receptor agonists was significantly protective against hypoglycemic encounters. 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.

Determinants of disparities of diabetes-related hospitalization rates in Florida: a retrospective ecological study using a multiscale geographically weighted regression approach

BackgroundEarly diagnosis, control of blood glucose levels and cardiovascular risk factors, and regular screening are essential to prevent or delay complications of diabetes. However, most adults with diabetes do not meet recommended targets, and some populations have disproportionately high rates of potentially preventable diabetes-related hospitalizations. Understanding the factors that contribute to geographic disparities can guide resource allocation and help ensure that future interventions are designed to meet the specific needs of these communities. Therefore, the objectives of this study were (1) to identify determinants of diabetes-related hospitalization rates at the ZIP code tabulation area (ZCTA) level in Florida, and (2) assess if the strengths of these relationships vary by geographic location and at different spatial scales.MethodsDiabetes-related hospitalization (DRH) rates were computed at the ZCTA level using data from 2016 to 2019. A global ordinary least squares regression model was fit to identify socioeconomic, demographic, healthcare-related, and built environment characteristics associated with log-transformed DRH rates. A multiscale geographically weighted regression (MGWR) model was then fit to investigate and describe spatial heterogeneity of regression coefficients.ResultsPopulations of ZCTAs with high rates of diabetes-related hospitalizations tended to have higher proportions of older adults (p < 0.0001) and non-Hispanic Black residents (p = 0.003). In addition, DRH rates were associated with higher levels of unemployment (p = 0.001), uninsurance (p < 0.0001), and lack of access to a vehicle (p = 0.002). Population density and median household income had significant (p < 0.0001) negative associations with DRH rates. Non-stationary variables exhibited spatial heterogeneity at local (percent non-Hispanic Black, educational attainment), regional (age composition, unemployment, health insurance coverage), and statewide scales (population density, income, vehicle access).ConclusionsThe findings of this study underscore the importance of socioeconomic resources and rurality in shaping population health. Understanding the spatial context of the observed relationships provides valuable insights to guide needs-based, locally-focused health planning to reduce disparities in the burden of potentially avoidable hospitalizations.

Diyabetik Ayağın Derin Öğrenme Yöntemleriyle Ayırıcı Tanısı

Diabetic foot complications, caused by prolonged hyperglycemia, are a significant health concern among diabetes patients. Majority of patients develop diabetic foot complications, contributing significantly to diabetes-related hospital admissions. These complications include foot ulcers, infections, ischemia, Charcot foot, and neuropathy. They also increase the risk of amputation, affecting quality of life and putting strain on healthcare systems. At this stage, early diagnosis plays a vital role. The process of diagnosing involves not only identifying the presence or absence of a disease, but also categorizing the disease. In this study, we examine the use of deep learning methods in the diagnosis of diabetic foot conditions. It explores various aspects such as predictive modeling and image analysis. The study discusses the progression of model designs, data sources, and interpretability methodologies, with a focus on improving accuracy and early detection. Overall, the study provides a comprehensive analysis of the current state of deep learning in diabetic foot problems with highlighting advancements.

Ambient heat and diabetes hospitalizations: Does the timing of heat exposure matter?

BackgroundAlthough ambient heat exposure is linked with diabetes mortality, the impacts of heat exposure on diabetes-related hospitalizations remain controversial. Previous research did not examine the timing of heat-diabetes associations and relation with comorbidities/risk factors. ObjectiveWe examined the association between heat exposure and diabetes-related hospitalizations in the transitional and summer months and identified populations vulnerable to heat. MethodsWe conducted a time-stratified case-crossover study. Data on diabetes hospital admissions (primary diagnosis of type 1 and type 2 diabetes, 2013–2020) were collected by the New York State (NYS) Department of Health under the state legislative mandate. We treated temperature and air pollutants as continuous variables and defined the heat exposure as per interquartile range (IQR, a measure between the 25th and 75th percentiles) increase of daily mean temperature. Conditional logistic regressions were performed to quantify the heat-diabetes associations after controlling for air pollutants and time variant variables. Multiplicative-scale interactions between heat and demographics/comorbidities/risk factors on diabetes hospitalizations were investigated. ResultsEach IQR increase in temperature was associated with significantly increased risks for diabetes admissions that occurred immediately and lasted for an entire week during multi-day lags in the transitional month of May (ranges of excess risk: 3.1 %–4.8 %) but not in the summer (June–August) (ranges of excess risk: −0.3 %–1.3 %). The significant increases in the excess risk of diabetes were also found among diabetes patients with complications of neuronopathy (excess risk: 27.7 %) and hypoglycemia (excess risk: 19.1 %). Furthermore, the modification effects on the heat-diabetes association were significantly stronger in females, Medicaid enrollees, non-compliant patients, and individuals with comorbidities of atherosclerotic heart disease and old myocardial infarction. ConclusionsAmbient heat exposure significantly increased the burden of hospital admissions for diabetes in transitional rather than summer months indicating the importance of exposure timing. Vulnerability to heat varied by demographics and heart comorbidity.

Impact of multidisciplinary care of diabetic foot infections for inpatients at Campbelltown Hospital

BackgroundDiabetic foot infection (DFI), including diabetic foot ulcer, is a serious complication of diabetes, particularly in the South Western Sydney (SWS) region where it is a leading cause of diabetes-related hospitalisations. Multidisciplinary team (MDT) involvement is effective at improving the health outcomes of DFI patients. This study investigated the impact of MDT (High Risk Foot Service, HRFS) on the length of stay and surgical outcomes of inpatients with DFI in a Sydney tertiary hospital.MethodA retrospective audit of electronic medical records of inpatient admissions for DFI at Campbelltown Hospital between January 2019 - December 2021, was performed. The main outcome of the study was MDT involvement, defined as having two or more specialities involved in the patient’s treatment. The other measured variables included length of stay (defined as the total duration from admission to discharge), and surgical outcomes including debridement, minor amputation, and major amputation.ResultsOver the three years, 78 participants presented to the hospital for 89 unique DFI admissions. There were 24 admissions in 2019, 28 admissions in 2020, and 37 admissions in 2021, with MDT attendance showing a steady increase at 62.5%, 75.0% and 83.8% respectively. Patients with serious comorbidities such as chronic kidney disease were more likely to have MDT involvement (84.8% vs. 15.2%, P = 0.048). Imaging was more likely to be performed with MDT involvement (78.8% vs. 21.3%, p < 0.05). Comparing patients who received and did not receive MDT care, the mean HbA1c (%) (8.4 ± 2.0 vs. 8.2 ± 2.7, P = 0.701), median length of stay (LOS: 7.8, IQR 15.0 days vs. 4.8 IQR 7.9 days, P = 0.243) and rate of surgical outcomes (74.6% vs. 72.7%, P = 0.262) were similar. Patients who required major amputation had significantly longer LOS (24 days, IQR 21.5 vs. 5.2 days, IQR 13.0, P = 0.004) but similar HbA1c (P = 0.552) compared to those who had conservative intervention.ConclusionAdopting an MDT approach was associated with more thorough investigation of DFI, with similar rates of surgical outcomes. Further research on the impacts of MDT on length of stay and surgical outcomes of DFI patients in other SWS hospitals is needed.

Development and implementation of a workshop for young adults with diabetes entering college and the workforce.

The process of transitioning from pediatric to adult diabetes care for adolescents and young adults is challenging. This transition period may include many life changes, and can be fraught with worsening glycemic control leading to increased risk for diabetes-related hospitalizations and complications. Research has demonstrated that increased support during this period can help maintain engagement in diabetes care. Transition guidelines highlight the importance of preparation and readiness for transition. In this article, we discuss the development, implementation and content of a workshop for patients and parents/caregivers preparing for the transition to college, the workforce and adult diabetes care.

Emergency Department Use in Black Individuals With Diabetes.

The prevalence of diabetes is higher in Black than in White individuals, and Blacks seek emergency department (ED) care for diabetes more often than Whites. This randomized controlled trial compared the efficacy of a novel intervention called the Diabetes Interprofessional Team to Enhance Adherence to Medical Care (DM I-TEAM) to usual medical care (UMC) to prevent return diabetes-related ED visits and hospitalizations over 12 months in 200 Black individuals with diabetes after an ED visit. The trial also identified baseline variables associated with return ED visits and hospitalizations. The DM I-TEAM provided diabetes education and behavioral activation services delivered by race-concordant research assistants, telehealth visits with a diabetes care and education specialist and primary care physicians, and clinical pharmacist recommendations. Participants had a mean age of 64.9 years, and 73.0% were women. There was no treatment group difference in return diabetes-related ED visits or hospitalizations over 12 months (DM I-TEAM n = 39 [45.3%] vs. UMC n = 37 [38.5%], χ2 = 0.864, P = 0.353). Baseline variables that were associated with return diabetes-related ED visits or hospitalizations were longer duration of diabetes, higher number of chronic health conditions, higher number of previous ED visits or hospitalizations, greater anticholinergic medication burden, lower satisfaction with primary care physicians, and lower trust in physicians (all P ≤0.05). Among Black individuals with diabetes, the DM I-TEAM interprofessional intervention was no better than UMC at preventing return diabetes-related ED visits or hospitalizations. High medical morbidity, greater anticholinergic medication burden, low satisfaction with primary care physicians, and physician mistrust were associated with diabetes-related ED visits or hospitalizations independent of treatment. Before clinical interventions such as the DM I-TEAM can be effective, reducing system-level barriers to health, improving physician-patient relationships and medication prescribing, and building community health care capacity will be necessary.

Clinical impacts of frailty on 123,172 people with diabetes mellitus considering the age of onset and drugs of choice: a nationwide population-based 10-year trajectory analysis.

Frailty substantially increased the risk of adverse clinical outcomes, which was also critical in diabetes management. This study aimed to investigate the interrelationships between the age of onset, frailty, anti-diabetic medications and clinical outcomes in people with diabetes mellitus (DM). A total of 123,172 people aged 40years and older who were newly diagnosed with DM were identified and categorised into four frailty subgroups (robust, mild, moderate and severe) based on the multimorbidity frailty index (mFI). Cox proportional hazards models were used to examine associations between frailty and clinical outcomes at different ages of DM onsets (40-64, 65-74, 75-84 and 85+ years). Outcomes of interest included generic outcomes (mortality and unplanned hospitalisation) and DM-related outcomes (cardiovascular disease-related mortality, major adverse cardiovascular events (MACEs), diabetes-related hospitalisation and hypoglycaemia). The proportion of frailty increased with age at diagnosis amongst people with incident DM and the mFI scores increased significantly during the 10-year follow-up. Amongst people with diabetes, those with mild, moderate and severe frailty were associated with greater risks of all-cause mortality (mild: adjusted hazard ratio (aHR) 1.69 [95% confidence interval (CI) 1.60-1.80], P< 0.01; moderate: aHR 2.46 [2.29-2.65], P< 0.01; severe frailty: aHR 3.40 [3.16-3.65], P< 0.01) compared with the robust group. Similar results were found in unplanned hospitalisations, cardiovascular disease-related mortality, MACEs and hypoglycaemia. Our study quantified the prevalence of frailty, captured its dynamic changes and examined its impacts on various clinical outcomes amongst people with diabetes at different ages at onset. Frailty assessment and management should be implemented into routine diabetes care.

991-P: Reduction in Diabetes-Related Hospitalizations and Medical Costs after Real-Time Continuous Glucose Monitor (rtCGM) Initiation in Patients with Type 2 Diabetes (PWT2D) on Intensive Insulin Therapy (IIT)

This study evaluated changes in diabetes-related hospitalizations and healthcare resource utilization (HCRU) costs after rtCGM initiation in PWT2D on IIT. Retrospective analysis of US healthcare claims data using Optum’s Clinformatics® database was conducted. The cohort included CGM naïve PWT2D on IIT who initiated rtCGM (Dexcom G6) between 8/1/2018 through 3/31/2021 (index date=earliest observed pharmacy claim). Diabetes-related (e.g., diabetic ketoacidosis, hyperglycemia and hypoglycemia) hospitalizations (ER and inpatient visits) and associated HCRU costs were assessed 12-months pre- and post-index. Hospitalizations were expressed as changes in the number of visits. Changes in diabetes-related HCRU costs were reported as per-person-per-month (PPPM) costs. Hospitalizations and HCRU costs were defined as claims with a diabetes-related diagnosis code in the 1st or 2nd position on the claim. A total of 790 PWT2D (average age=52.8 (sd=10.5) years, 46.7% female) rtCGM users on IIT with commercial health insurance met inclusion criteria. A 50% reduction (p&amp;lt;0.0001) in the number of diabetes-related inpatient visits after rtCGM initiation was observed (baseline n=132, follow-up n=66). Similarly, after rtCGM initiation, a 47% reduction (p&amp;lt;0.05) in the number of diabetes-related ER visits occurred (baseline n=85, follow up n=45). Average PPPM diabetes-related hospitalization medical costs decreased by $329.53 (p&amp;lt;0.05). HCRU cost reductions were driven by reduced diabetes-related inpatient medical costs (-$308.46 PPPM). Payer claims showed that hyperglycemia and ketoacidosis were the most common reasons for hospitalizations 12-months pre- and post-device initiation. Findings suggest that rtCGM initiation may contribute to reduced HCRU for PWT2D on IIT by way of improving glycemic control. Disclosure K.Hannah: Employee; Dexcom, Inc. P.Nemlekar: Employee; Dexcom, Inc. G.J.Norman: Employee; Dexcom, Inc. Funding Dexcom, Inc.

1332-P: Comparison of Clinical Characteristics of People Living with Latent Autoimmune Diabetes of the Adult (LADA) and Type 1 Diabetes (T1D) in the Canadian BETTER Registry

Introduction: LADA is known for a slow progression of autoimmune destruction of beta-cells with cases that span a spectrum between classic T1D and T2D phenotypes. To date, lacking a good understanding of LADA has prohibited the release of specific clinical practice guidelines and subsequently an optimal management. Methodology: Cross-sectional analysis of online clinical questionnaires in the Canadian BETTER registry; participants can specify having received a diagnosis of LADA or T1D. Data was analyzed for the first 1464 participants; 131 (9%) reported LADA and 1333 (91%) T1D. Results: At registration; LADA vs T1D were 49 ± 13 y.o. vs 42 ± 15 y.o; 61% vs. 62% females; diabetes duration 10 ± 9 vs. 24 ± 15 years. LADA vs. T1D were older at diagnosis (39 ± 12 vs. 18 ± 12 years old; p&amp;lt;0.001), only half started insulin in first year of diagnosis (52 vs. 97%; p&amp;lt;0.001), more often reported a family history of T1D (46 vs. 32%; p=0.001). For comparable glycemic control (HbA1c &amp;lt; 8.6 mmol/l, &amp;lt;7%, 38 vs. 32%), fewer cases with LADA reported at least an episode in last month of level II hypoglycemia &amp;lt;54 mg/dL (3.0mmol/L) 63% vs. 77%; p= 0.004, severe hypoglycemia rates were 8% vs. 12%, p=0.15. Diabetes related hospitalizations were 10% in LADA vs. 6%, p=0.11, insulin pumps and glucagon were less used in LADA. In a matched analysis for diabetes duration and gender (1:1), glycemic control was still statistically comparable in LADA vs. T1D (HbA1c &amp;lt;7%: 38 vs 35%, p=0.12) as well as rates of nephropathy (6% vs. 11%, p=0.22), neuropathy (12% vs. 7%, p=0.23) and retinopathy (6% vs. 9%, p=0.07) yet with more cardiovascular disease (5% vs. 2%; p=0.02) and less coeliac disease (3 vs. 5%; p=0.001). Data analysis of 3000 participants is ongoing in early 2023. Conclusion: Reported differences may impact LADA management. This study sets the stage for building a prospective Canadian cohort of LADA to undergo deep phenotyping, genotyping and interventional trials. Disclosure M.Issa: None. A.Brazeau: Other Relationship; Dexcom, Inc., Diabète québec, Ordre des diététistes nutritionnistes du Québec, Research Support; Canadian Institutes of Health Research, Fonds de recherche du Québec en Santé. S.Haag: Other Relationship; Omnipod. A.Roy-fleming: None. V.Messier: None. N.Taleb: Consultant; Viatris Inc.

1047-P: Evaluating Discharge Prescription Errors and the Clinical Impacts in Patients with Insulin-Treated Diabetes Mellitus in a Community Hospital

Introduction: Transitioning patients with insulin treated diabetes (ITDM) at time of hospital discharge is identified as a source of error in how information for home management is provided that can contribute to significant adverse health outcomes. To address this, we conducted a quality improvement project investigating the safety of current discharge procedures in our hospital and the impact on glycemic control at 3 months and diabetes related readmissions at 3 and 6 months. Methods: We retrospectively analyzed discharge prescription errors in patients with ITDM in a community hospital between January 2020 and December 2021. Errors were defined as being discharged on the wrong form of insulin (pen vs vial), and/or not being provided appropriate insulin administration devices (i.e., pen needles or syringes). Data was collected by reviewing discharge summaries, discharge medication reconciliations and pharmacy records. Results: Among 75 patients with ITDM (62 (82%) T2DM, 12 (16%) T1DM, 1 (1%) ketosis-prone DM), errors were noted in 73 (97%) patients. 46 (63%) were discharged on wrong form of insulin and 67 (91%) were discharged without appropriate insulin administration devices. Among those 73 patients, 19 (26%) patients had an increase in HbA1c at 3 months (8.7 vs 10.03, p=0.001); 5 (25%) and 8 (24%) had 30-day and 90-day diabetes-related hospital readmissions, respectively. In 2 patients with appropriate discharge, there were no 30-day or 90-day hospital readmissions. Conclusion: Prescription errors in patients with ITDM at discharge are common and potentially remediable and lead to hospital readmissions and poor glycemic control. These results demonstrate the need for increased awareness among providers through adoption of standardized discharge insulin order sets in EMR system including the form of insulin, insulin administration devices and supplies as well as for early post-discharge follow up with endocrinology. Disclosure A.N.Keskinkilic: None. M.T.Korytkowski: None. S.Mon: None.

Text message-based intervention, Keeping in Touch (KiT), to support youth as they transition to adult type 1 diabetes care: a protocol for a multisite randomised controlled superiority trial

IntroductionTransition from paediatric to adult care can be challenging for youth living with type 1 diabetes (T1D), as many youth feel unprepared to transfer to adult care and are at...

Recurrent depression relates to worse outcomes than single episode depression among Hispanic adolescents with diabetes.

Adolescents with type 1 diabetes (T1D) are at increased risk for depression. A history of recurrent depression (HRD) may relate to worse health outcomes than single-episode depression. However, no study has explored this issue among T1D adolescents. We examined differences in psychosocial and diabetes-related outcomes between T1D adolescents with (G1; n = 33) and without (G2; n = 18) HRD. Participants were 51 youths (aged 12-17 years) enrolled in a depression treatment study. Youths and one caregiver each completed several measures. Using MANOVA, followed by individual ANOVAs, and chi-square tests, we compared groups in continuous and categorical variables, respectively. MANOVA results were significant, F(7, 43) = 3.97, p = .002. Adolescents from G1 obtained higher scores than youths in G2 in self-esteem/guilt problems, cognitive alterations, and sadness due to T1D. Their caregivers reported more burden and rated their offspring as having more internalizing problems, facing more barriers to complying with T1D treatment, and using a medical ID less frequently than their counterparts did. A higher percentage of G1 participants presented clinical anxiety and inadequate glycemic control, and reported a history of major depression. According to caregivers, a higher proportion of G1 members had experienced multiple diabetes-related hospitalizations, were non-compliant with insulin treatment, and lived in homes with a conflictive environment. Our study documents important differences in outcomes between T1D youths with vs. without any HRD. Clinicians may need an intensive and integrative approach to treat mental and physical aspects of health among these patients.

Clinical and biochemical predictors of intensive care unit admission among patients with diabetic ketoacidosis.

Diabetic ketoacidosis (DKA) contributes to 94% of diabetes-related hospital admissions, and its incidence is rising. Due to the complexity of its management and the need for rigorous monitoring, many DKA patients are managed in the intensive care unit (ICU). However, studies comparing DKA patients managed in ICU to non-ICU settings show an increase in healthcare costs without significantly affecting patient outcomes. It is, therefore, essential to identify suitable candidates for ICU care in DKA patients. To evaluate factors that predict the requirement for ICU care in DKA patients. This retrospective study included consecutive patients with index DKA episodes who presented to the emergency department of four general hospitals of Hamad Medical Corporation, Doha, Qatar, between January 2015 and March 2021. All adult patients (> 14 years) fulfilling the American Diabetes Association criteria for DKA diagnosis were included. We included 922 patients with DKA in the final analysis, of which 229 (25%) were managed in the ICU. Compared to non-ICU patients, patients admitted to ICU were older [mean (SD) age of 40.4 ± 13.7 years vs 34.5 ± 14.6 years; P < 0.001], had a higher body mass index [median (IQR) of 24.6 (21.5-28.4) kg/m2 vs 23.7 (20.3-27.9) kg/m2; P < 0.030], had T2DM (61.6%) and were predominantly males (69% vs 31%; P < 0.020). ICU patients had a higher white blood cell count [median (IQR) of 15.1 (10.2-21.2) × 103/uL vs 11.2 (7.9-15.7) × 103/uL, P < 0.001], urea [median (IQR) of 6.5 (4.6-10.3) mmol/L vs 5.6 (4.0-8.0) mmol/L; P < 0.001], creatinine [median (IQR) of 99 (75-144) mmol/L vs 82 (63-144) mmol/L; P < 0.001], C-reactive protein [median (IQR) of 27 (9-83) mg/L vs 14 (5-33) mg/L; P < 0.001] and anion gap [median (IQR) of 24.0 (19.2-29.0) mEq/L vs 22 (17-27) mEq/L; P < 0.001]; while a lower venous pH [mean (SD) of 7.10 ± 0.15 vs 7.20 ± 0.13; P < 0.001] and bicarbonate level [mean (SD) of 9.2 ± 4.1 mmol/L vs 11.6 ± 4.3 mmol/L; P < 0.001] at admission than those not requiring ICU management of DKA (P < 0.001). Patients in the ICU group had a longer LOS [median (IQR) of 4.2 (2.7-7.1) d vs 2.0 (1.0-3.9) d; P < 0.001] and DKA duration [median (IQR) of 24 (13-37) h vs 15 (19-24) h, P < 0.001] than those not requiring ICU admission. In the multivariate logistic regression analysis model, age, Asian ethnicity, concurrent coronavirus disease 2019 (COVID-19) infection, DKA severity, DKA trigger, and NSTEMI were the main predicting factors for ICU admission. In the largest tertiary center in Qatar, 25% of all DKA patients required ICU admission. Older age, T2DM, newly onset DM, an infectious trigger of DKA, moderate-severe DKA, concurrent NSTEMI, and COVID-19 infection are some factors that predict ICU requirement in a DKA patient.

Who are the most vulnerable populations for primary care? Avoidable hospitalizations across individuals with different types of disabilities in South Korea

BackgroundIndividuals with disabilities have limited access to primary care, the quality of care must be examined. ObjectiveTo examine avoidable hospitalizations among individuals with disabilities and determine the most vulnerable populations across types of disabilities. MethodsUsing the Korean National Health Insurance Claims Database, we compared hypertension- and diabetes-related avoidable hospitalizations (HRAH and DRAH, respectively) across disability status and disability type based on age-sex standardized rates from 2011 to 2020 and logistic regression. ResultsThe gap between those with and without disabilities in age-sex standardized HRAH and DRAH increased over 10 years. Odds ratios for HRAH were higher for those with disabilities, with individuals with mental disabilities having the highest odds ratio, followed by those with intellectual/developmental disabilities, then those with physical disabilities; for DRAH, the three highest odds ratios belonged to individuals with mental, intellectual/developmental, and visual disabilities. Among those with disabilities, HRAH was higher for those with mental, intellectual/developmental, and severe physical disabilities, whereas DRAH was higher for those with mental, severe visual, and intellectual/developmental disabilities compared to those with mild physical disabilities. ConclusionThis study reveals high avoidable hospitalization rates among individuals with disabilities and calls for policies supporting quality primary care and comprehensively addressing disparities.