BMJ Open Diabetes Research & Care最新文献

{"title":"Effect of weight-maintaining ketogenic diet on glycemic control and insulin sensitivity in obese T2D subjects.","authors":"Aurora Merovci, Brittany Finley, Andrea Hansis-Diarte, Sivaram Neppala, Muhammad A Abdul-Ghani, Eugenio Cersosimo, Curtis Triplitt, Ralph A DeFronzo","doi":"10.1136/bmjdrc-2024-004199","DOIUrl":"10.1136/bmjdrc-2024-004199","url":null,"abstract":"<p><strong>Introduction: </strong>Low carbohydrate ketogenic diets have received renewed interest for the treatment of obesity and type 2 diabetes. These diets promote weight loss, improve glycemic control, and reduce insulin resistance. However, whether the improvements in glycemic control and insulin sensitivity are secondary to the weight loss or result from a direct effect of hyperketonemia is controversial.</p><p><strong>Research design and methods: </strong>29 overweight obese subjects were randomized to one of three dietary interventions for 10 days: (1) Weight-maintaining standard diet; (2) Weight-maintaining ketogenic diet; (3) Weight-maintaining ketogenic diet plus supplementation with the ketone ester of beta-hydroxybutyrate (β-OH-B), 8 g every 8 hours. At baseline, all subjects had oral glucose tolerance test, 2-step euglycemic insulin clamp (20 mU/m².min and 60 mU/m².min) with titrated glucose and indirect calorimetry.</p><p><strong>Results: </strong>Body weight, fat content, and per cent body fat (DEXA) remained constant over the 10-day dietary intervention period in all three groups. Plasma β-OH-B concentration increased twofold, while carbohydrate oxidation decreased, and lipid oxidation increased demonstrating the expected shifts in substrate metabolism with institution of the ketogenic diet. Glucose tolerance either decreased slightly or remained unchanged in the two ketogenic diet groups. Whole body (muscle), liver, and adipose tissue sensitivity to insulin remained unchanged in all 3 groups, as did the plasma lipid profile and blood pressure.</p><p><strong>Conclusion: </strong>In the absence of weight loss, a low carbohydrate ketogenic diet has no beneficial effect on glucose tolerance, insulin sensitivity, or other metabolic parameters.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11492932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142458046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National health and economic impact of a lifestyle program to prevent type 2 diabetes mellitus in Germany: a simulation study.","authors":"Katherine Ogurtsova, Michael Laxy, Karl Emmert-Fees, Charalabos-Markos Dintsios, Ping Zhang, Andrea Icks","doi":"10.1136/bmjdrc-2024-004382","DOIUrl":"10.1136/bmjdrc-2024-004382","url":null,"abstract":"<p><strong>Introduction: </strong>To examine the long-term health and economic impact of a lifestyle diabetes prevention program in people with high risk of developing type 2 diabetes in Germany.</p><p><strong>Research design and methods: </strong>We assessed the lifetime cost-effectiveness of a 2-year pragmatic lifestyle program for preventing type 2 diabetes targeting German adults aged 35-54 and 55-74 years old with hemoglobin A1c (HbA1c) from 6.0% to 6.4%. We used the Centers for Disease Control and Prevention RTI Diabetes Cost-Effectiveness Model to run a simulation on the program effectiveness. We estimated incremental health benefits in quality-adjusted life years (QALYs) and costs using an established simulation model adapted to the German context, from a healthcare system and societal perspective. The cost-effectiveness of the program was measured by incremental cost-effectiveness ratios (ICERs) in cost per QALY. We projected the number of type 2 diabetes cases prevented by participation rate if the program was implemented nationwide.</p><p><strong>Results: </strong>The lifestyle program would result to more QALYs and higher costs. The lifetime ICERs were 14 690€ (35-54 years old) and 14 372€ (55-74 years old) from a healthcare system perspective and cost saving (ICER=-3805€) and cost-effective (ICER=4579€), respectively, from a societal perspective. A total of 10 527 diabetes cases would be prevented over lifetime if the program was offered to all eligible people nationwide and 25% of those would participate in the program.</p><p><strong>Conclusions: </strong>Implementing the lifestyle intervention for people with HbA1c from 6.0% to 6.4% could be a cost-effective at standard willingness to pay level strategy for type 2 diabetes prevention. The intervention in the younger cohort could be cost saving from a societal perspective. The successful implementation of a lifestyle-based diabetes prevention program could be an important component of a successful National Diabetes Strategy in Germany.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11492960/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142458047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ethnic-specific oral glucose tolerance (OGTT) phenotypes in women with hyperglycemia in pregnancy.","authors":"Yu Bin Tan, Phaik Ling Quah, Kok Hian Tan","doi":"10.1136/bmjdrc-2024-004331","DOIUrl":"10.1136/bmjdrc-2024-004331","url":null,"abstract":"<p><strong>Introduction: </strong>Ethnic differences associated with oral glucose tolerance test (OGTT) phenotypes is less studied in Southeast Asian ethnicities, especially in women with hyperglycemia in pregnancy (HIP).</p><p><strong>Research design and methods: </strong>We retrospectively examined 3027 women at KK Women's and Children's Hospital in 2019. Of these, 508 (16.8%) women were diagnosed with HIP using the IADPSG (International Association of Diabetes and Pregnancy Study Groups) criteria at 24-28 weeks. OGTT phenotypes were classified into four mutually exclusive groups based on abnormal plasma glucose at (1) 0 hour only; (2) 1 hour only; (3) 2 hour only; (4) ≥2 timepoints (reference). Multinomial logistic regression was used to examine the association between ethnicity and OGTT phenotypes, adjusting for maternal age, parity, and first-trimester body mass index.</p><p><strong>Results: </strong>Overall HIP prevalence was 16.8%, highest among Indians (20.5%), then Chinese (18.3%) and Malays (14.2%). Indians (relative risk ratio (RRR) 3.05) and Chinese (RRR 2.33) were at higher risk of displaying a fasting-only phenotype compared with Malays. Chinese were at increased risk of displaying a 2-hour postprandial phenotype with an RRR of 2.88 as compared with Malays.</p><p><strong>Conclusions: </strong>Unique OGTT phenotypes exist across ethnic groups among women who developed HIP in a multi-ethnic Asian population.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11459354/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142375149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent trends in GLP-1 RA and SGLT2i use among people with type 2 diabetes and atherosclerotic cardiovascular disease in the USA.","authors":"Aaron King, Xi Tan, Neil Dhopeshwarkar, Rhonda Bohn, Katherine Dea, Charles E Leonard, Adam de Havenon","doi":"10.1136/bmjdrc-2024-004431","DOIUrl":"10.1136/bmjdrc-2024-004431","url":null,"abstract":"<p><strong>Introduction: </strong>This study aimed to assess recent trends in the US use of glucagon-like peptide-1 receptor agonist (GLP-1 RA) and sodium-glucose cotransporter 2 inhibitor (SGLT2i) in people with type 2 diabetes (T2D) and atherosclerotic cardiovascular disease (ASCVD), including incident use following newly diagnosed ASCVD.</p><p><strong>Research design and methods: </strong>This real-world, retrospective observational study used de-identified data from the TriNetX Dataworks-USA network. A longitudinal analysis of cross-sectional data (interval: January 01, 2018 to December 31, 2022) assessed the yearly prevalent use of GLP-1 RA and SGLT2i. A nested cohort study (January 01, 2017 to January 31, 2023) assessed the proportions of patients with T2D newly prescribed GLP-1 RAs and SGLT2is after incident ASCVD diagnosis.</p><p><strong>Results: </strong>Prevalent use of GLP-1 RA and/or SGLT2i increased from 9.2% of patients in 2018 to 27.1% in 2022, with eligible annual patient numbers ranging from 279,474 to 348,997. GLP-1 RA-alone use rose from 5.2% to 9.9% and SGLT2i-alone use rose from 2.8% to 12.2% over this interval. Incident use of GLP-1 RA and/or SGLT2i within the year following ASCVD diagnosis increased from 5.9% to 17.0% (2018-2022). For GLP-1 RA alone, this increase was from 3.6% to 7.8%, while for SGLT2i alone, it was from 1.8% to 7.0%.</p><p><strong>Conclusions: </strong>Use of GLP-1 RAs/SGLT2is in patients with T2D and ASCVD has increased in recent years in the USA, but remains suboptimal given the prevalence of ASCVD and its high morbidity and mortality.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11459310/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142375150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Presentation and characteristics of children with screen-detected type 1 diabetes: learnings from the ELSA general population pediatric screening study.","authors":"Lauren M Quinn, Renuka P Dias, Christopher Bidder, Sudeshna Bhowmik, Kerstin Bumke, Jaikumar Ganapathi, Shaun Gorman, Edward Hind, Swati Karandikar, Kiran Kumar, Nicholas Lipscomb, Sheila McGovern, Vijith R Puthi, Tabitha Randell, Gemma Watts, Parth Narendran","doi":"10.1136/bmjdrc-2024-004480","DOIUrl":"https://doi.org/10.1136/bmjdrc-2024-004480","url":null,"abstract":"<p><strong>Introduction: </strong>We describe the identification and management of general population screen-detected type 1 diabetes (T1D) and share learnings for best practice.</p><p><strong>Research design and methods: </strong>Children diagnosed with T1D through a general population screening initiative, the EarLy Surveillance for Autoimmune diabetes (ELSA) study, were reviewed and described.Parents provided written, informed consent for inclusion in the case series.</p><p><strong>Results: </strong>14 children with insulin requiring (stage 3) T1D are described. These cases offer unique insights into the features of screen-detected T1D. T1D is identified sooner through screening programs, characterized by absent/short symptom duration, median presenting glycated hemoglobin 6.6% (49 mmol/mol) and insulin requirements<0.5 units/kg/day. ELSA identified four children at stage 3 and another 4 progressed within 4 months of ELSA completion, including two single seropositive children. Six children developed stage 3 T1D prior to ELSA completion, including two children (14%, n=2/14) with diabetic ketoacidosis prior to confirmed antibody status.</p><p><strong>Conclusions: </strong>There are three main learnings from this case series. First, T1D identified through screening is at an earlier stage of its natural history and requires personalized insulin regimens with lower total daily insulin doses. Second, single autoantibody seropositivity can rapidly progress to stage 3. Finally, insulin requirement can manifest at any stage of the T1D screening pathway, and therefore early education around symptom recognition is essential for families participating in screening programs.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11429353/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142341705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying machine learning approaches for predicting obesity risk using US health administrative claims database.","authors":"Casey Choong, Alan Brnabic, Chanadda Chinthammit, Meena Ravuri, Kendra Terrell, Hong Kan","doi":"10.1136/bmjdrc-2024-004193","DOIUrl":"10.1136/bmjdrc-2024-004193","url":null,"abstract":"<p><strong>Introduction: </strong>Body mass index (BMI) is inadequately recorded in US administrative claims databases. We aimed to validate the sensitivity and positive predictive value (PPV) of BMI-related diagnosis codes using an electronic medical records (EMR) claims-linked database. Additionally, we applied machine learning (ML) to identify features in US claims databases to predict obesity status.</p><p><strong>Research design and methods: </strong>This observational, retrospective analysis included 692 119 people ≥18 years of age, with ≥1 BMI reading in MarketScan Explorys Claims-EMR data (January 2013-December 2019). Claims-based obesity status was compared with EMR-based BMI (gold standard) to assess BMI-related diagnosis code sensitivity and PPV. Logistic regression (LR), penalized LR with L1 penalty (Least Absolute Shrinkage and Selection Operator), extreme gradient boosting (XGBoost) and random forest, with features drawn from insurance claims, were trained to predict obesity status (BMI≥30 kg/m²) from EMR as the gold standard. Model performance was compared using several metrics, including the area under the receiver operating characteristic curve. The best-performing model was applied to assess feature importance. Obesity risk scores were computed from the best model generated from the claims database and compared against the BMI recorded in the EMR.</p><p><strong>Results: </strong>The PPV of diagnosis codes from claims alone remained high over the study period (85.4-89.2%); sensitivity was low (16.8-44.8%). XGBoost performed the best at predicting obesity with the highest area under the curve (AUC; 79.4%) and the lowest Brier score. The number of obesity diagnoses and obesity diagnoses from inpatient settings were the most important predictors of obesity. XGBoost showed an AUC of 74.1% when trained without an obesity diagnosis.</p><p><strong>Conclusions: </strong>Obesity prevalence is under-reported in claims databases. ML models, with or without explicit obesity, show promise in improving obesity prediction accuracy compared with obesity codes alone. Improved obesity status prediction may assist practitioners and payors to estimate the burden of obesity and investigate the potential unmet needs of current treatments.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11429277/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142341696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Serum isthmin-1 is a potential biomarker for metabolic dysfunction associated fatty liver disease in patients with metabolic syndrome and type 2 diabetes mellitus.","authors":"Xiaohui Lei, HaiYan Chen, YuXin Xu, Zhuoran Yang, Lili Zhang, Cong Wang, Hu Du","doi":"10.1136/bmjdrc-2024-004514","DOIUrl":"10.1136/bmjdrc-2024-004514","url":null,"abstract":"<p><strong>Introduction: </strong>Metabolic dysfunction associated fatty liver disease (MAFLD) is a prevalent condition in patients with type 2 diabetes mellitus (T2DM). Isthmin-1 (ISM1) is an adipokine that promotes glucose uptake and improves glucose tolerance and hepatic steatosis. Although ISM1 has been shown to be associated with T2DM, its role in patients with MAFLD and metabolic syndrome (MetS) remains insufficiently examined. This study aimed to investigate the relationship between serum ISM1 and MAFLD in patients with T2DM and the potential involvement of MetS in this association.</p><p><strong>Research design and methods: </strong>A total of 250 participants were divided into four groups: 60 patients with T2DM and MAFLD, 60 with newly diagnosed T2DM, 60 with MAFLD, and 70 healthy controls. Serum ISM1 levels were measured using ELISA. The distribution of ISM1 concentration in the combined data was divided into quartiles, and the Cochran-Armitage trend test was performed to estimate the significant trends across increasing quartiles.</p><p><strong>Results: </strong>Compared with the controls, patients with coexisting MAFLD, MetS, and T2DM exhibited significantly elevated serum ISM1 concentrations. Serum ISM1 levels in the overweight/obese group were also higher than those in the lean group. Serum ISM1 levels were positively correlated with body mass index (BMI), uric acid, alanine aminotransferase, aspartate aminotransferase, total cholesterol (TC), low-density lipoprotein cholesterol, fasting insulin, and homeostasis model assessment of insulin resistance and negatively associated with age and high-density lipoprotein cholesterol (HDL-C). BMI, TC, and HDL-C were independently associated with serum ISM1 concentration. The relative risks for MAFLD, T2DM, and T2DM with MAFLD increased significantly with higher ISM1 quartiles. Furthermore, a positive correlation was observed between serum ISM1 levels and the number of MetS components, with the elevated plasma levels of ISM1 escalating the risk of developing MetS to some extent.</p><p><strong>Conclusions: </strong>The combination of ISM1 with TG and UA was identified as the best predictive factor for diagnosing MAFLD and MetS, potentially due to their contribution to aggravating the metabolic state.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11425935/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142341706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increased incidence of neurodegenerative diseases in Finnish individuals with type 1 diabetes.","authors":"Susanna Satuli-Autere, Valma Harjutsalo, Marika I Eriksson, Stefanie Hägg-Holmberg, Hanna Öhman, Tor-Björn Claesson, Per-Henrik Groop, Lena M Thorn","doi":"10.1136/bmjdrc-2024-004024","DOIUrl":"10.1136/bmjdrc-2024-004024","url":null,"abstract":"<p><strong>Introduction: </strong>Diabetes is linked to neurodegenerative diseases (NDs), but data in type 1 diabetes are scarce. Our aim was to assess the standardized incidence ratios (SIRs) of different NDs in type 1 diabetes, and to evaluate the impact of diabetic vascular complications and age at diabetes onset.</p><p><strong>Research design and methods: </strong>In this observational cohort study, we included 4261 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy study, and 11 653 matched population-based controls without diabetes. NDs were identified from registers until the end of 2017. Diabetic complications were assessed at the baseline study visit. SIRs were calculated from diabetes onset, except for impact of complications that was calculated from baseline study visit.</p><p><strong>Results: </strong>The SIRs for NDs were increased in type 1 diabetes: any dementia 2.24 (95% CI 1.79 to 2.77), Alzheimer's disease 2.13 (95% CI 1.55 to 2.87), vascular dementia 3.40 (95% CI 2.08 to 5.6), other dementias 1.70 (95% CI 1.22 to 2.31), and Parkinson's disease 1.61 (95% CI 1.04 to 2.37). SIR showed a twofold increased incidence already in those without albuminuria (1.99 (1.44-2.68)), but further increased in presence of diabetic complications: kidney disease increased SIR for Alzheimer's disease, while cardiovascular disease increased SIR for both Alzheimer's disease and other dementias. Diabetes onset <15 years, compared with ≥15 years, increased SIR of Alzheimer's disease, 3.89 (2.21-6.35) vs 1.73 (1.16-2.48), p<0.05, but not the other dementias.</p><p><strong>Conclusions: </strong>ND incidence is increased 1.7-3.4-fold in type 1 diabetes. The presence of diabetic kidney disease and cardiovascular disease further increased the incidence of dementia.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11381727/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142145158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Not all healthcare inequities in diabetes are equal: a comparison of two medically underserved cohorts.","authors":"Ashby F Walker, Michael J Haller, Ananta Addala, Stephanie L Filipp, Rayhan Lal, Matthew J Gurka, Lauren E Figg, Melanie Hechavarria, Dessi P Zaharieva, Keilecia G Malden, Korey K Hood, Sarah C Westen, Jessie J Wong, William T Donahoo, Marina Basina, Angelina V Bernier, Paul Duncan, David M Maahs","doi":"10.1136/bmjdrc-2024-004229","DOIUrl":"10.1136/bmjdrc-2024-004229","url":null,"abstract":"<p><strong>Introduction: </strong>Diabetes disparities exist based on socioeconomic status, race, and ethnicity. The aim of this study is to compare two cohorts with diabetes from California and Florida to better elucidate how health outcomes are stratified within underserved communities according to state location, race, and ethnicity.</p><p><strong>Research design and methods: </strong>Two cohorts were recruited for comparison from 20 Federally Qualified Health Centers as part of a larger ECHO Diabetes program. Participant-level data included surveys and HbA1c collection. Center-level data included Healthcare Effectiveness Data and Information Set metrics. Demographic characteristics were summarized overall and stratified by state (frequencies, percentages, means (95% CIs)). Generalized linear mixed models were used to compute and compare model-estimated rates and means.</p><p><strong>Results: </strong>Participant-level cohort: 582 adults with diabetes were recruited (33.0% type 1 diabetes (T1D), 67.0% type 2 diabetes (T2D)). Mean age was 51.1 years (95% CI 49.5, 52.6); 80.7% publicly insured or uninsured; 43.7% non-Hispanic white (NHW), 31.6% Hispanic, 7.9% non-Hispanic black (NHB) and 16.8% other. Center-level cohort: 32 796 adults with diabetes were represented (3.4% with T1D, 96.6% with T2D; 72.7% publicly insured or uninsured). Florida had higher rates of uninsured (p<0.0001), lower continuous glucose monitor (CGM) use (18.3% Florida; 35.9% California, p<0.0001), and pump use (10.2% Florida; 26.5% California, p<0.0001), and higher proportions of people with T1D/T2D>9% HbA1c (p<0.001). Risk was stratified within states with NHB participants having higher HbA1c (mean 9.5 (95% CI 8.9, 10.0) compared with NHW with a mean of 8.4 (95% CI 7.8, 9.0), p=0.0058), lower pump use (p=0.0426) and CGM use (p=0.0192). People who prefer to speak English were more likely to use a CGM (p=0.0386).</p><p><strong>Conclusions: </strong>Characteristics of medically underserved communities with diabetes vary by state and by race and ethnicity. Florida's lack of Medicaid expansion could be a factor in worsened risks for vulnerable communities with diabetes.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11381725/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142145159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a three-dimensional scoring model for the assessment of continuous glucose monitoring data in type 1 diabetes.","authors":"Jeanie Dawnbringer, Henrik Hill, Markus Lundgren, Sergiu-Bogdan Catrina, José Caballero-Corbalan, Lars Cederblad, Per-Ola Carlsson, Daniel Espes","doi":"10.1136/bmjdrc-2024-004350","DOIUrl":"10.1136/bmjdrc-2024-004350","url":null,"abstract":"<p><strong>Introduction: </strong>Despite the improvements in diabetes management by continuous glucose monitoring (CGM) it is difficult to capture the complexity of CGM data in one metric. We aimed to develop a clinically relevant multidimensional scoring model with the capacity to identify the most alarming CGM episodes and/or patients from a large cohort.</p><p><strong>Research design and methods: </strong>Retrospective CGM data from 2017 to 2020 available in electronic medical records were collected from n=613 individuals with type 1 diabetes (total 82 114 days). A scoring model was developed based on three metrics; glycemic variability percentage, low blood glucose index and high blood glucose index. Values for each dimension were normalized to a numeric score between 0-100. To identify the most representative score for an extended time period, multiple ways to combine the mean score of each dimension were evaluated. Correlations of the scoring model with CGM metrics were computed. The scoring model was compared with interpretations of a clinical expert board (CEB).</p><p><strong>Results: </strong>The dimension of hypoglycemia must be weighted to be representative, whereas the other two can be represented by their overall mean. The scoring model correlated well with established CGM metrics. Applying a score of ≥80 as the cut-off for identifying time periods with a 'true' target fulfillment (ie, reaching all targets for CGM metrics) resulted in an accuracy of 93.4% and a specificity of 97.1%. The accuracy of the scoring model when compared with the CEB was high for identifying the most alarming CGM curves within each dimension of glucose control (overall 86.5%).</p><p><strong>Conclusions: </strong>Our scoring model captures the complexity of CGM data and can identify both the most alarming dimension of glycemia and the individuals in most urgent need of assistance. This could become a valuable tool for population management at diabetes clinics to enable healthcare providers to stratify care to the patients in greatest need of clinical attention.</p>","PeriodicalId":9151,"journal":{"name":"BMJ Open Diabetes Research & Care","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11381645/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142145157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}