bluuebunny/crossref_metadata_2025 huggingface dataset:
641-P: Behavioral Health Needs of a Commercially Insured Adult Population with Type 2 Diabetes
Authors: COOK DAVID J. , DEFAIL ANTHONY , LIVESEY CECILIA , PEDERSON DEREK
Published: May 2022

Background: There is an increasing appreciation of the interconnection between chronic illnesses such as type-2 diabetes and behavioral health conditions such as depression and anxiety, as well as more serious behavioral health conditions. The separation of practice and payment for medical and behavioral conditions is ripe for disruption. This is of particular importance for risk-bearing entities.

Methods: Level2 is a virtual accountable care organization taking total cost-of-care risk for a commercially insured population. Using a de-identified administrative claims research database, we estimated the behavioral health profile of our enrolled population by examining the prescribing of common behavioral health medications.

Results: In our enrolled population of 7,361 members, the average age was 54.4 years, and the M:F ratio was 53:47. Prescriptions for behavioral health medications were demonstrated in 26.2% of the population. Medications for depression and anxiety were most common (20.0% and 8.0% respectively) , while antipsychotics were prescribed in 0.1% of attributed members. Twenty-four months of enrollment (November 2019- November 2021) showed stable prescribing patterns.

Conclusion: The movement towards provider risk bearing, and a more sophisticated understanding of the relationship between physical and behavioral health, necessitate a more comprehensive and integrated approach to care for patients. While this intersection may be evident to providers in their daily activities, the analysis of a population of nearly 7,400 members gives a broader insight into this challenge and calls for clinical service redesign, the application of new methodologies and measurements, and over time, new payment models. Of note, the prescribing data spans the COVID and pre-COVID periods and was stable over time, so the high use of behavioral health medications is not COVID-attributable.

Disclosure

D.J.Cook: None. A.Defail: Employee; Level2. C.Livesey: Advisory Panel; Compass Pathways, Employee; UnitedHealth Group. D.Pederson: Employee; Level2.
643-P: Perceived Usefulness of Mindfulness-Based Stress Reduction in Persons with Type 2 Diabetes
Authors: FERRARA LUCILLE , KAUFMAN SOPHIE R.
Published: May 2022

Diabetes management can be burdensome and stressful. Mindfulness-based Stress Reduction (MBSR) is a method that has shown to help mitigate stress. This qualitative study, as part of a larger study, examined the effects of MBSR on stress in persons with DM2 participating in an 8-week MBSR course and explored how participants: Gained insight regarding their stress Identified aspects of MBSR perceived as useful for stress management Continued to incorporate mindfulness practice in their daily lives as a method of stress management (6 months and 1 year post-intervention) Study Population: 13 adults > 18 years with DM2 having a recent A1C >7% who committed to participate in an 8-week MBSR course. Study Design: Qualitative study exploring the effects of MBSR on stress in persons with DM2. Participants enrolled in an 8-week MBSR course completed open-ended questionnaires at orientation, mid-way, and upon completion of the course to assess learning and attitude towards stress. Video recordings of the classes were transcribed and analyzed. Participants completed the Mindfulness Attention Awareness Scale (MAAS) at the start and end of the course. Participants received follow-up at 6 and 12 months post intervention, including completing the MAAS and were surveyed about the incorporation of mindfulness into their daily lives. Results: Participants shared their realization of the effect of stress on their body and mind, and reported noticing patterns of reactivity, and learning to let go and respond rather than react to stressors. Participants’ reflections and observed behaviors illustrated increased self-awareness, curiosity, patience, less self-judgment, and compassion and kindness toward their experience. Participants reported incorporating mindfulness in their daily routine at 6 month and 12 month post intervention, including meditation, yoga, mindful eating, different response to stressful situations, and better focus. MAAS: Results indicated an increase in MAAS scores over time.

Disclosure

L.Ferrara: None. S.R.Kaufman: None.

Funding

Josiah Macy Foundation (P19014)
645-P: Real-World Outcomes of Thai Patients with Impaired Glucose Tolerance: Patterns of Metformin Usage and Weight Change
Authors: CHATCHOMCHUAN WARALEE , THEWJITCHAROEN YOTSAPON , PRASARTKAEW HUSSAMON , SRICHOMCHEY PANITA , BUTADEJ SIRIWAN , NAKASATIEN SOONTAREE , WANOTHAYAROJ EKGALUCK , KRITTIYAWONG SIRINATE , HIMATHONGKAM THEP
Published: May 2022

Background: Even though lifestyle modifications and pharmacological interventions have been shown to be effective in patients who have impaired glucose tolerance (IGT) , the patients’ responses to lifestyle changes after receiving the diagnosis of IGT in Thai patients are lacking. Therefore, this study aims to determine the weight changes following the diagnosis of IGT and elucidate the patterns of metformin use among Thai patients with IGT.

Methods: A 5-year retrospective study of newly diagnosed Thai patients with IGT in Theptarin Hospital, Bangkok during 2016-2020 was analyzed. Their weight at the last clinical visit was compared with that at the initial visit. The prevalence and characteristics of metformin prescription were also collected.

Results: Two hundred and sixty-six IGT patients (63.9% female, mean age of 51.8 ± 12.5 years, mean body weight 69.8 ± 15.0 kg, and mean body mass index (BMI) of 26.5 ± 4.7 kg/m2) were diagnosed during 2016-2020. The prevalence of metformin usage among these patients was 21.1%. During the median follow-up of months, the mean weight change was -1.0 ± 3.7 kg. A significant weight reduction was found in metformin group compared with control group, (mean weight change of -2.2 ± 4.7 kg vs. -0.7 ± 3.4 kg; p-value =0.006) . Furthermore, up to 26.8% of patients who was prescribed metformin achieved > 5% weight reduction. Metformin was more frequently prescribed in patients who had age ≥ 60 years, BMI ≥ 35 kg/m2, concomitant statin usage, combined impaired fasting glucose (IFG) and IGT, and patients who had A1C ≥ 6.0%.

Conclusions: Weight reduction is minimal among Thai patients who had IGT. More intensive efforts with structured lifestyle programs should be implemented to prevent diabetes. Metformin should be considered if patients are unable or unwilling to lose weight with lifestyle changes.

Disclosure

W. Chatchomchuan: None. Y. Thewjitcharoen: None. H. Prasartkaew: None. E. Wanothayaroj: None. T. Himathongkam: None.
65-LB: Time in Range as a Clinical Outcome—Results of a Longitudinal Analysis of the Literature and Clinical Trials
Authors: PATEL PRANAV M. , ABANIEL RICHARD , DOGRA NATASHA , FRAZZITTA MARIE , VIRDI NAUNIHAL
Published: May 2022

Background: HbA1c has traditionally been the gold standard of glycemic control. Continuous glucose monitoring (CGM) has enabled capture of newer glycemic measures such as time in range (TIR) which has been associated with diabetes outcomes, captures glucose variability, and has been endorsed by professional societies. This preliminary analysis describes trends in publications and clinical trials that capture TIR as a clinical outcome.

Methods: Systematic review of Embase, MEDLINE, and clinical trial registries was conducted. For each article, year of publication, country of research, role of technology, and funding source were captured. Clinical trials also captured study start dates and anticipated completion dates.

Results: TIR was reported in 1561 publications and 401 clinical trials. The number of publications with TIR mentioned grew 12-fold between 2017-2021 (Figure 1) . Among clinical trials capturing TIR, 138 trials were completed between 2010-2020; another 240 have been finished or are estimated to conclude between 2021-2025.

Conclusion: TIR as an important clinical outcome continues to proliferate suggesting increasing acceptance of TIR as an emerging standard of care in diabetes management. Further analysis will differentiate studies where CGM was part of the intervention from those where CGM was used to measure outcomes with other interventions.

Disclosure

P. M. Patel: Employee; Abbott Diabetes. R. Abaniel: None. N. Dogra: Employee; Abbott Diabetes. M. Frazzitta: Employee; Abbott Diabetes, Abbott Diabetes. N. Virdi: Employee; Abbott Diabetes.

Funding

Abbott Diabetes Care
659-P: Long-Term Health Benefit and Economic Return of Time in Range (TIR) Improvement in Individuals with Type 2 Diabetes
Authors: ALKHUZAM KHALID , SHI LIZHENG , FONSECA VIVIAN , ZHANG YONGKANG , GUO JINGCHUAN , SHAO HUI
Published: May 2022

Time in range (TIR) referres to the percentage of time that blood glucose levels stay within a pre-determined range for patients with diabetes. This study used simulation methods to quantify the long-term health benefit and economic return associated with the improvement of TIR in individuals with T2D. Individuals with self-reported T2D were identified from the 2017-2018 National Health and Nutrition Examination Survey as the target population for the simulation. A Markov model with three states (i.e., diabetes, diabetes with a history of cardiovascular disease (CVD) , death) was developed to calculate the 20-year cost, quality-adjusted life-years (QALY) gained, and cardiovascular disease (CVD) risk reduction under four scenarios: TIR >85%, 71-85%, 51-70%, and ≤50%. The risk of CVD and mortality were extracted from literature. CVD and mortality risk reduction associated with TIR improvement, as well as cost and QALY associated with each health state were all extracted from the literature. Costs were standardized to the 2021 US Dollar, and a 3.0% annual discount rate was used. A willingness-to-pay threshold of $50,000/QALY was used to determine cost-effectiveness. Compared with having a TIR <50%, improving the TIR to 51-70% was associated with an increase of 1.14 QALY and 1.20 life years, and a 5.86% relative risk reduction in CVD; improving the TIR to 71-85% was associated with an increase of 1.69 QALY and 1.46 life-years, and a 8.05% relative risk reduction in CVD; improving the TIR to >85% was associated with an increase of 3.QALY and 1.97 life-years, and a 14.89% relative risk reduction in CVD. The annual spending on treatment to improve the TIR from <50% to 51-70%, 71-85%, and >85% should be lower than $2,592, $3,082, and $4,120 respectively to make the treatment cost-effective. Improving TIR can potentially lead to a substantial health benefit. Our study qualified the maximum medical expenses allocated to improve the TIR while keeping the treatment cost-effective.

Disclosure

K.Alkhuzam: None. L.Shi: None. V.Fonseca: Consultant; Abbott, Asahi Kasei Corporation, Bayer AG, Novo Nordisk, Sanofi, Research Support; Fractyl Health, Inc., Jaguar Gene Therapy, Stock/Shareholder; Abbott, Amgen Inc., BRAVO4Health, Mellitus Health. Y.Zhang: None. J.Guo: None. H.Shao: Board Member; BRAVO4HEALTH, LLC.
66-LB: System Performance of an Integrated Blood Glucose Monitoring Device Developed to Reduce Common Barriers to Checking Glucose
Authors: TOMASCO MICHAEL , DAVIS JUDITH M. , REYNOLDS PAUL D. , ESCUTIA RAUL , PERRY JOHN N. , O’DONNELL TIM , HESLEY ROBB P.
Published: May 2022

The POGO Automatic® Blood Glucose Monitoring System miniaturizes individual items required to perform a blood glucose test (lancet, lancing device, test strip, etc.) and integrates those components into a multi-test cartridge that pairs to a handheld device, addressing many perceived checking barriers. This device allows the user to place and hold a finger on the device while the blood sample is acquired and moved to the reagent pad automatically for quantitation. Performance testing was conducted on the device to assess accuracy, precision, and tolerance to hematocrit and interfering substances.

Fingerstick capillary blood was collected from 285 untrained subjects with either type 1 or type 2 diabetes at two sites (age 21-95, mean 58.1; 50.2% female, 84.9% Caucasian) and run on a YSI 2300 analyzer while the subject used the system as designed to obtain a glucose result. When compared against the YSI reference result, 264/277 (95.3%) results were within ± 15 mg/dL or 15% of the reference reading, and 275/277 (99.3%) results were within ± 15 mg/dL or 20% of the reference reading. Precision testing was conducted by running 300 tests using venous blood at each of five glucose levels across the dynamic range, achieving CVs ranging from 2.3%-3.4%. Hematocrit tolerance was evaluated using venous whole blood manipulated into a matrix of seven hematocrit levels (20%-60%) ; each hematocrit was tested across the dynamic range. No mean bias versus YSI at any test condition exceeded 7.5%, and at least 95% of all tests at each condition were within 15% of the YSI reference value. Twenty-three substances, including acetaminophen, ascorbic acid, and maltose, were tested at both therapeutic and toxic concentrations to determine potential interference with measurement accuracy. For all substances tested, the entire 95% confidence interval for interferent bias was within ± 15%, and the average bias was within ± 10% of results from the control sample.

Disclosure

M. Tomasco: Employee; Intuity Medical, Inc. J. M. Davis: None. P. D. Reynolds: Employee; Intuity Medical, Inc. R. Escutia: Employee; Intuity Medical, Inc. J. N. Perry: Employee; Intuity Medical, Inc. T. O’donnell: Employee; Intuity Medical, Inc. R. P. Hesley: Employee; Intuity Medical, Inc.
662-P: Glycemic Variability Patterns Strongly Correlate with Partial Remission Status in Children with Newly Diagnosed Type 1 Diabetes
Authors: POLLE OLIVIER G. , DELFOSSE ANTOINE A. , MARTIN MANON , GIES INGE , IEBRETHON MARIE-CHRISTINE , MOURAUX THIERRY H. , LOUIS JACQUES , SERET NICOLE , GATTO LAURENT , LYSY PHILIPPE A.
Published: May 2022

Residual β-cell secretion is commonly used as primary endpoint of β-cell mass prevention trials. Recently, peak C-peptide was challenged as a clinically relevant marker of β-cell function considering its poor integration of insulin sensitivity and β-cell glucose responsiveness. In our DIATAG study, we evaluated the correlations between metrics of glycemic variability (GV) and markers of diabetes control (i.e. A1C, insulin daily dose, insulin dose-adjusted A1C [IDAA1C]) to identify whether GV indexes may overcome residual β-cell secretion estimates (BSE) in the evaluation of glucose homeostasis during the first year of type 1 diabetes (e.g. remission period) . Data from 78 new-onset type 1 diabetes pediatric patients were collected from diabetes onset (Δ) and cross-sectionally compared using adjusted mixed-effects models at Δ+3, +12 months for BSE (n=119) and Δ+3, +6, +9, +12 months for glucose control and CGM metrics (n=169) . BSE demonstrated weak-to-moderate correlations with clinical parameters and CGM metrics (r2= 0.05-0.25; p<0.05) . CGM metrics strongly correlated with clinical parameters (r2 >0.52; p<0.05) and were sufficient to distinguish remitters from non-remitters (i.e. IDAA1C respectively <9 or ≥9) . Moreover, CGM metrics from remitters exhibited specific nycthemeral patterns characterized by increased glycemic stability (in 63-160 mg/dL range) across days in the early morning period and decreased grade II hypoglycemia during the day (p<0.01) . Using hierarchical clustering on 46 CGM metrics and clinical parameters (n=169) , we identified four unique glucotypes (p<0.001) during the first year of diabetes that allowed better segregation of intermediate values of IDAA1C from Δ+3 months (38% in Group 1, 26% in Group 2, 29% in Group 3, 7% in Group 4) . We conclude that a combination of CGM metrics and clinical parameters unraveled key clinical milestones of glucose homeostasis and remission status during the first year of type 1 diabetes.

Disclosure

O.G. Polle: None. A.A. Delfosse: None. M. Martin: None. I. Gies: None. M. Iebrethon: None. J. Louis: None. N. Seret: None. L. Gatto: None.

Funding

Fond National de la Recherche Scientifique (FRIA grant, FSR starting grant) Belgian Society for Pediatric Endocrinology and Diabetology (BESPEED) Société Francophone du Diabète (SFD)
665-P: Awareness of Time in Range Varies by Type of Health Care Provider
Authors: KENNEY JULIA , BRISKIN ANDREW , TAIT JACQUELINE , SHOGER ERIK , WOOD RICHARD , PETERS ANNE L.
Published: May 2022

Background and Aims: Previous studies have shown an association between Time in Range (TIR) and risk of microvascular complications, but TIR is not used widely in diabetes care. This study aimed to assess differences in awareness and use of TIR among healthcare providers (HCPs) .

Methods: In an online survey in September 2021, 303 HCPs, each working with a minimum of 30 patients with diabetes each month, were asked a series of questions related to challenges, evaluation, and goal-setting when discussing diabetes management with patients. Respondents were classified as either Endocrinologists (Endo) , Diabetes Educators (DE) , or primary care providers (PCP) . Statistical significance was tested at the 95% confidence level (p<0.05) .

Results: DEs were more likely to be aware of (96%, n=106) and use (94%, n=106) TIR in clinical practice than Endos (92%, 88%, n=98) and PCPs (56%, 46%, n=99) . Among respondents who were aware of TIR (n=247) , Endos were more likely to use TIR when making treatment decisions (87%, n=90) than PCPs (69%, n=55) . Among those who reported using TIR in clinical practice (n=234) , PCPs were least familiar (67%, n=46) with CGM metrics compared to Endos (91%, n=88) and DEs (79%, n=100) .

Conclusions: This data highlights differences in TIR use between Endos, DEs, and PCPs, and the lower levels of TIR awareness among PCPs. This study emphasizes opportunities for increased awareness of TIR through education and training of PCPs on CGM and TIR.

Disclosure

J.Kenney: None. A.Briskin: None. J.Tait: Employee; dQ&A. E.Shoger: Other Relationship; Diabetes industry. R.Wood: Other Relationship; Multiple companies and patient organizations (>10) . A.L.Peters: Advisory Panel; Abbott Diabetes, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Shouti, Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Other Relationship; Omada Health, Inc., Research Support; Abbott Diabetes, Dexcom, Inc., Insulet Corporation, Leona M. and Harry B. Helmsley Charitable Trust, Stock/Shareholder; Teladoc Health.
666-P: CGM Access Is the Main Barrier to TIR Use among Providers
Authors: KENNEY JULIA , TAIT JACQUELINE , BRISKIN ANDREW , SHOGER ERIK , WOOD RICHARD , PETERS ANNE L.
Published: May 2022

Background and Aims: Previous studies have shown a correlation between Time in Range (TIR) and risk for microvascular complications, but the metric is not used widely in diabetes care. This study aimed to assess the barriers to TIR use among healthcare providers.

Methods: In an online survey in September 2021, 303 HCPs, each working with a minimum of 30 patients with diabetes each month, were asked a series of questions related to challenges, evaluation, and goal-setting when discussing diabetes management with their patients. Respondents were classified as either Endocrinologists (Endo) , Diabetes Educators (DE) , or primary care providers (PCP) . Statistical significance was tested at the 95% confidence level (p<0.05) .

Results: 80% of HCPs who use TIR (n=234) identify access to CGM as a main drawback of TIR and 72% (n=289) identified cost as a downside of CGM use. When TIR non-users (n=64) were asked what would convince them to use TIR with patients, 41% cited increased access to CGM and 30% cited training and resources about how to use TIR data. 83% of non-users (n=64) believe TIR would be useful in their diabetes care. When asked what would improve their diabetes care, 39% of HCPs said having more patients on CGM and 28% said the ability to use TIR data with more patients (n=246) .

Conclusions: This data highlights the barriers to TIR adoption and use among HCPs. Increased access to CGM and education on TIR use in clinical practice can help advance TIR in diabetes care.

Disclosure

J.Kenney: None. J.Tait: Employee; dQ&A. A.Briskin: None. E.Shoger: Other Relationship; Diabetes industry. R.Wood: Other Relationship; Multiple companies and patient organizations (>10) . A.L.Peters: Advisory Panel; Abbott Diabetes, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Shouti, Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Other Relationship; Omada Health, Inc., Research Support; Abbott Diabetes, Dexcom, Inc., Insulet Corporation, Leona M. and Harry B. Helmsley Charitable Trust, Stock/Shareholder; Teladoc Health.
67-LB: Nursing Perspectives on Hospital Use of Dexcom Continuous Glucose Monitor in Patients with Suspected or Known COVID-19 during Insulin Infusion
Authors: PATTISON JILLIAN , DUNGAN KATHLEEN M. , BUSCHUR ELIZABETH , EXLINE MATTHEW C. , JONES LAUREEN G. , MAY CASEY , MCNETT MOLLY , SMETANA KEATON , FAULDS EILEEN R.
Published: May 2022

The coronavirus disease 2019 pandemic resulted in the need for remote glucose monitoring in intensive care unit (ICU) patients requiring insulin infusions. While rarely reported, perceptions from nursing staff are critical for successful implementation and expanded use. A hybrid continuous glucose monitoring (CGM) and intermittent point of care (POC) glucose monitoring was developed at the study institution. After 1.5 years of protocol use, an anonymous survey was distributed electronically to ICU nurses to obtain their perspectives on CGM utilization. The survey employed a 1-5 Likert scale regarding CGM sensor insertion, accuracy, acceptability, and usability as well as perceptions on reduced room entry and reduced workload. Of the 51 surveys completed, 50 (98%) nurses reported they cared for an ICU patient enrolled in the CGM protocol and 31 (62%) started or replaced a CGM sensor. A representative sample of questions and responses is shown in table 1. ICU nurses overwhelmingly reported CGM was accurate, reduced their workload, provided safer patient care, and was preferred over POC glucose testing alone. These results confirm nursing acceptance and preference for CGM use within a hybrid glucose monitoring protocol in the ICU setting.

Disclosure

J. Pattison: None. K. M. Dungan: Advisory Panel; Dexcom, Inc., Consultant; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Elsevier, Nova Biomedical, Novo Nordisk, Tolerion, Inc., Other Relationship; UpToDate, Research Support; Abbott, Dexcom, Inc., Novo Nordisk, Sanofi, ViaCyte, Inc., Speaker’s Bureau; Academy for Continued Healthcare Learning, Cardiometabolic Health Congress, Medscape. E. Buschur: Advisory Panel; Beta Bionics, Inc., Research Support; Dexcom, Inc. M. C. Exline: Other Relationship; Abbott. L. G. Jones: None. C. May: None. M. Mcnett: None. K. Smetana: None. E. R. Faulds: Advisory Panel; Dexcom, Inc., Research Support; Dexcom, Inc., Speaker’s Bureau; Medscape.
671-P: Patterns of Sensor-Detected Hypoglycemia in Long-Duration CGM Data from a Diabetes Registry
Authors: BAUMANN PETRA M. , HOCHFELLNER DANIEL A. , CIGLER MONIKA , SIEGL REBECCA , POETTLER TINA , MADER JULIA K.
Published: May 2022

Compared to time below range less is known about the frequency and temporal distribution of hypoglycemic episodes in CGM data. Pooled analysis of long-duration CGM data from a diabetes registry allows for large-scale exploration of sensor-detected hypoglycemic episodes (SDHE) .

66 patients with T1D used CGM over 365.7 (340.6-392.5) days (24.530 days total) . In addition to time below range (TBR) , we explored frequency of SDHE >15 minutes at <70, <54 and 40 mg/dl by time of day and sensor runtime (30 days) as well as glycemic control by pooled individual days (12AM-12AM) .

TBR was 5.4% (<70) , 1.9% (<54) and 0.7% (=40) . 24.7% of SDHE<70 occurred at nighttime (0-6am = 25% of hours/day) . SDHE<54 and SDHE=40 had a nightly surplus with 34.4% and 41.5%, respectively. Number of daily SDHE<70 slightly decreased over the first month and was more uniform across subjects. Numbers of SHDE<54 and SHDE=40 are more varied, and the latter increased over time. Pooled CGM days showed a decrease and greater variance in glucose levels during the night, a surplus of nightly readings at 40mg/dl and a drop in glucose around noon.

Focus on SHDE and individual days showed similar patterns to TBR regarding the surplus and variability of nightly low readings. The greater variability and the increase of SHDE=40 over 30 days while SDHE<70 remained stable suggest that sensor lifetime may be a confounder. Overall, SDHE is a valuable addition to TBR.

Disclosure

P.M.Baumann: None. D.A.Hochfellner: None. M.Cigler: None. R.Siegl: None. T.Poettler: None. J.K.Mader: Advisory Panel; Abbott Diabetes, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medtronic, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Roche Diabetes Care, Sanofi-Aventis Deutschland GmbH, Speaker's Bureau; Abbott Diabetes, Eli Lilly and Company, Medtronic, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Roche Diabetes Care, Sanofi-Aventis Deutschland GmbH, Servier Laboratories, Stock/Shareholder; decide Clinical Software GmbH.

Funding

"This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement 777460. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA and T1D Exchange, JDRF, International Diabetes Federation (IDF) , The Leona M. and Harry B. Helmsley Charitable Trust."
68-OR: Using Machine Learning to Improve Screening for Undiagnosed Diabetes among Emergency Department Patients
Authors: BOHART ISAAC , CALDWELL J. REED , SWARTZ JORDAN , ROSEN PERRY E. , GENES NICHOLAS , KOZIATEK CHRISTIAN A. , NEILL DANIEL B. , LEE DAVID C.
Published: May 2022

Introduction: Screening for previously undiagnosed diabetes in the emergency department (ED) can enhance early detection, which may particularly benefit patients with barriers to accessing primary care. To optimize use of limited ED resources, there is a need to identify ED patients who are at high risk.

Objectives: To improve identification of ED patients with undiagnosed diabetes using machine learning (ML) .

Methods: Diabetes screening by HbA1c was implemented in four EDs at an academic medical center. Patients aged 40 or older, with BMI > 25, no history of diabetes and no HbA1c result within 6 months were eligible for screening. Patients were stratified by screening result and compared across demographic and clinical characteristics, and local geographic measures of health and socioeconomic variables. ML classifier models predicting a positive screening result were trained, and were validated on a prospectively withheld subset of the cohort.

Results: In the first weeks after implementation, 2423 eligible patients were identified, and 1518 (62.6%) were screened, with 114 (7.5% of those screened) found to have previously undiagnosed diabetes. Patients with diabetes more often identified as male, Hispanic or Latino, Black, or Asian, had higher BMIs and blood pressures at triage, resided in neighborhoods with higher diabetes prevalence and poverty rates, and had less prior healthcare utilization, especially in the outpatient setting. The best performing classifier models were logistic regression with elastic net regularization (AUC 0.81) and gradient-boosted trees (AUC 0.77) . These models identified a high-risk subgroup consisting of 30% of eligible patients who accounted for over 80% of newly detected cases of diabetes.

Conclusions: ML models can reliably identify ED patients at high risk of having undiagnosed diabetes based on demographic, clinical, and local geographic risk factors, and could form the basis of a selective screening program.

Disclosure

I.Bohart: None. J.Caldwell: None. J.Swartz: None. P.E.Rosen: None. N.Genes: None. C.A.Koziatek: None. D.B.Neill: None. D.C.Lee: None.
685-P: Will Choice of Treatment Influence TIR in T2D with Diabetic Complications?
Authors: KESAVADEV JOTHYDEV , SABOO BANSHI D. , SHANKAR ARUN , KRISHNAN GOPIKA , SANAL GEETHU , BASANTH ANJANA , JOTHYDEV SUNITHA
Published: May 2022

Though TIR is a predictive marker of diabetic complications, there is paucity of data evaluating the association of TIR with therapeutic regimens. We investigated the association of CGM-derived metrics, with presence of complications and therapeutic regimen in T2D. We analyzed AGP of T2D who underwent 14-day p-CGM between 2015 and 2021. Clinical parameters were extracted from EMR. Data of 1218 T2D (baseline age=53.14±15.03 yrs; 69.2% male, avg. duration of diabetes: 14.44±9.48 yrs) on different therapeutic regimen (OHAs±insulin; namely basal only, biphasic, basal plus, basal bolus regimen) were analyzed. A regression model was run with % TIR as dependent variable and age, duration, insulin regimen, complications, and BMI as independent variables. Spearman’s correlation coefficient was calculated between lab A1C and eA1c. On analysis, age was found to have a statistically significant relation with TIR. A moderate correlation (0.60) between A1C and eA1C was observed. 68.4% achieved a target TIR of >70% in T2D without complications. 69.5% with CAD/CKD achieved target TIR of >50%. Among the different therapeutic regimens analyzed, use of analogue basal-bolus regimen was associated with statistically significant (p<0.05) TIR target of >50% and TBR<1% in T2D with CAD/CKD (Figure 1) . In T2D with vascular complications, analogue basal bolus regimen could be a superior choice in reaching optimal TIR with insignificant time below range.

Disclosure

J.Kesavadev: None. B.D.Saboo: None. A.Shankar: None. G.Krishnan: None. G.Sanal: None. A.Basanth: None. S.Jothydev: None.
69-OR: Implementing Autonomous AI in a Federally Qualified Health Center (FQHC) for the Detection of Diabetic Retinopathy Improves Access to Care: A Pre–Post Comparison in the Southeastern U.S.
Authors: GOLDSTEIN JULI , WEITZMAN DENA , ABRÀMOFF MICHAEL D.
Published: May 2022

Diabetic retinopathy (DR) and diabetic macular edema (DME) are debilitating complications of diabetes; however, patients in the most vulnerable populations often face barriers in accessing recommended ocular exams, leading to major health inequity. These barriers are especially true for FQHCs, as they serve the most under resourced and underserved populations. More recently, rigorously validated, FDA cleared, autonomous AI for the detection of DR and DME has been considered as an alternative to deployed remote reading networks. We examined the impact of autonomous AI compared to remote reading on patient access and clinical workflow efficiency, measured as number of steps by the operator. During 90 days in mid-2021, at two FQHC clinics in the southeastern US, autonomous AI was provided in place of a remote reading network. All steps were completed at the point-of-care: qualified patients with diabetes were identified in the electronic health record (EHR) , diagnosed by the autonomous AI output, provided results at time of the exam, and referred to specialists where appropriate. After 90 days, 1patients with diabetes underwent autonomous AI diagnostic testing, and 30/1patients with diabetes (28.6%) were identified by the AI as having signs of vision threatening DR or DME. Testing was accomplished with fewer steps as compared to exams completed with a remote reading network at the same clinics. We conclude that implementing autonomous AI point-of-care testing for the identification of DR and DME in an FQHC setting improved workflow efficiency and patient access compared to remote reading, demonstrating a potential to address health inequities in underserved and vulnerable populations.

Disclosure

J.Goldstein: Employee; Digital Diagnostics. D.Weitzman: Employee; Digital Diagnostics. M.D.Abràmoff: Advisory Panel; NovaGo Therapeutics AG, Board Member; Digital Diagnostics, Consultant; Digital Diagnostics, Speaker's Bureau; AbbVie Inc., Stock/Shareholder; Digital Diagnostics.
693-P: Significant Changes in Dietary Behaviour, Glycemic Control, and Weight after Participation in Personalized Glycemic Response–Based Diabefly Program
Authors: VERMA RITIKA , KHADER MOHAMMED A. , RANADIVE RUCHIRA M. , BUDYAL SWETA , SARAF AMIT A. , RASKAR VIVEK , SARWATE ASHISH , JOSHI MITALI V. , JOSHI SHILPA , SINGAL ARBINDER K.
Published: May 2022

Background: Retrospective evaluation of glycemic responses correlated with lifestyle habits can help in mapping personalized glycemic responses (PGR) for individuals. PGR can aid in more specific nutritional interventions in individuals with diabetes ultimately aiding in better glycemic control and weight management.

Methods: Participants (n=108, mean age 47.24± 12.28 years, 55.5% females) were enrolled in PGR based Diabefly program and were provided with support for lifestyle modification through a combination of expert led care and mobile application. The outcomes were analyzed at the beginning and end of the program. Paired t-test was used for analysis with P<0.considered as statistically significant.

Results: After the program, the daily mean calorie intake significantly reduced by 9.34 ± 30.3 % from a baseline of 1466.93 ± 408.16 cal (P<0.001) . Similarly, the daily mean carbohydrate and fat intake significantly reduced by 10.44 ± 31.99 % and 7.95 ± 39.90 % respectively (P<0.0for both) . The daily mean fiber intake improved by 4.74 ± 44.9 % from the baseline (P=0.26) . Further, the mean energy attributed from protein showed a significant increase by 10.36 ± 25.31 % (P<0.001) . Among participants (n=66) who provided complete data of body weight, BMI, and HbA1c a significant reduction was observed by 3.41 ± 3.33 kg, 1.16± 1.kg/m2, and 2.02 ± 1.73% from a baseline of 76.42 ± 16.61 kg, 27.34 ± 4.40 kg/m2, and 8.78 ± 1.90 % respectively (P<0.0for all) . Waist circumference in participants with complete data (n=53) showed a mean reduction by 4.85 ± 4.45 % from the baseline of 100.3 ± 14.1 cm (P<0.001) .

Conclusion: Significant change in dietary behavior was observed after the completion of the program. Effective weight reduction, waist circumference reduction, and improved glycemic control was also observed suggesting the potential of understanding PGR in an effective manner through the Diabefly program for improved outcomes.

Disclosure

R.Verma: Employee; Fitterfly Healthtech Pvt Ltd, Wellthy Therapeutics Pvt Ltd. A.K.Singal: Other Relationship; Fitterfly Healthtech Pvt Ltd. M.A.Khader: Employee; Fitterfly HealthTech Pvt Ltd. R.M.Ranadive: Employee; Fitterfly Healthtech Pvt Ltd. S.Budyal: None. A.A.Saraf: None. V.Raskar: None. A.Sarwate: None. M.V.Joshi: None. S.Joshi: Consultant; Fitterfly Health Tech Pvt Ltd, Wellthy Therapeutics Pvt Ltd.
7-OR: Distinct Developmental Origins of Brown Adipose Tissue at Different Anatomical Locations
Authors: RUAN HAI-BIN , ZHANG ZENGDI , HUANG ZAN
Published: May 2022

Brown adipose tissue (BAT) is a thermogenic organ that promotes metabolic fitness. In humans, there are two spatiotemporally distinct phases of BAT ontogeny: the prenatally developed dorsal-anterior-located interscapular and retroperitoneal BAT; and the postnatally emerged anterior cervical and supraclavicular BAT. It has been established in rodents that the dorsal-anterior-located BAT depots predominately arise from a Pax3+/Myf5+ lineage in the epaxial dermomyotome that also forms the trunk muscle. However, the developmental origins of the anterior cervical and supraclavicular BAT that adult humans have remain unknown. In this study, using lineage tracing mouse models, we found that these neck BAT depots are not derived from the Pax3+ or Myf5+ precursor cells. Knock out of PPARγ, the master regulator of adipogenesis, in Myf5+ cells caused severe atrophy of interscapular BAT, but did not affect the anterior cervical and supraclavicular depots. Instead, we identified that roughly half of the anterior cervical and supraclavicular brown adipocytes are progeny cells of a developmental lineage that also gives rise to neck muscle cells. PPARγ deficiency in this lineage did not perturb iBAT development, but caused paucity in the anterior cervical and supraclavicular regions, thus sensitizing mice to cold-induced decrease in body temperature.

In summary, our results suggest that there are region-specific myogenic precursors that contribute to BAT development at different anatomical locations. Future studies to understand the pathophysiological regulation of these developmentally distinct BAT depots could inspire new approaches to measure BAT mass and to activate BAT activity in humans for the treatment of obesity, diabetes and related metabolic disorders.

Disclosure

H.Ruan: None. Z.Zhang: None. Z.Huang: None.

Funding

American Diabetes Association (1-18-IBS-167)
70-LB: Lower A1C with Real-Time CGM than with Intermittently-Scanned CGM after One Year—The CORRIDA LIFE Study
Authors: RADOVNICKÁ LUCIE , HÁSKOVÁ ANETA , DO QUOC DAT , HOROVA EVA , NAVRÁTILOVÁ VENDULA , MIKES ONDREJ , CIHLÁR DAVID , PARKIN CHRISTOPHER , GRUNBERGER GEORGE , PRAZNY MARTIN , SOUPAL JAN
Published: May 2022

We investigated the efficacy of real-time continuous glucose monitoring (rtCGM) and intermittently scanned continuous glucose monitoring (isCGM) on change in A1C. CORRIDA LIFE was a 12 month, real-world, non-randomized trial that assessed the impact of rtCGM (Dexcom G5 or G6) vs. isCGM (FreeStyle Libre 14-Day, Abbott) on A1C and other CGM metrics in adults with T1D. Patients on MDI therapy or CSII with no automatic functions were included. One hundred ninety-one adults with T1D (mean age 40±13 years, A1C 8.1±3.4% [65±14 mmol/mol]) participated in this study; 81 patients initiated rtCGM and 110 initiated isCGM. After 12-months, A1C was significantly lower with rtCGM vs. isCGM (7.1±3.1% [54.1±10.1 mmol/mol] vs. 7.7±3.3% [61.2±12.2 mmol/mol]) , p=0.0001. (Figure 1) The percentage of time in hypoglycemia (<70 mg/dL [<3.9 mmol/L]) was lower among rtCGM vs. isCGM participants (4.3±2.8% vs. 6.4±5.3%) , p=0.003) . Patients with rtCGM spent less time in clinically significant hypoglycemia (<54 mg/dL [<3.0 mmol/L]) (0.9±1.0% vs. 2.3±2.5%, p<0.0001) and more time in target range (70-180 mg/dL [3.9-10 mmol/L]) than isCGM users (67.5±14.8% vs. 57.8±17.0%) , p=0.0002. Use of rtCGM was superior to isCGM in reducing A1C and hypoglycemia and improving other glycemic outcomes.

Disclosure

L. Radovnická: Consultant; Medtronic, Speaker’s Bureau; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk, Sanofi. M. Prazny: Advisory Panel; Bayer AG, Consultant; Boehringer Ingelheim International GmbH, Speaker’s Bureau; Abbott Diabetes, Amgen Inc., Eli Lilly and Company, Medtronic, Merck Sharp & Dohme Corp., Novartis Pharmaceuticals Corporation, Novo Nordisk, Sanofi. J. Soupal: Advisory Panel; Abbott Diabetes, Roche Diabetes Care, Speaker’s Bureau; Boehringer Ingelheim International GmbH, Dexcom, Inc., Lilly Diabetes, Medtronic, Novo Nordisk. A. Hásková: None. Q. Do: None. E. Horova: None. V. Navrátilová: None. O. Mikes: None. D. Cihlár: None. C. Parkin: Consultant; Abbott Diabetes, CeQur SA, Dexcom, Inc., LifeScan, MannKind Corporation, Novo Nordisk, Provention Bio, Inc., Roche Diabetes Care. G. Grunberger: Advisory Panel; LifeScan, Nevro Corp., Research Support; Medtronic, Speaker’s Bureau; Abbott Diabetes, Eli Lilly and Company, Novo Nordisk.

Funding

Ministry of Health, Czech Republic, General University Hospital in Prague
70-OR: Association of Diabetes Screening with Demographic, Neighborhood Level Census, and Area Gentrification Characteristics
Authors: THOMAS TAINAYAH , DYER WENDY T. , RODRIGUEZ LUIS A. , SCHMITTDIEL JULIE
Published: May 2022

Research assessing predictors of preventive screening often focuses on individual patient factors, despite known relationships between neighborhood environment and health. Using a retrospective cohort study of 519,826 patients meeting US Preventive Service Task Force guideline recommendation for screening for prediabetes and type 2 diabetes (age 35-70 years and BMI ≥25) from Kaiser Permanente Northern California in 2018, we used logistic regression to assess the relationship between diabetes screening and census neighborhood tract-level measures, and area gentrification measures developed by the Urban Displacement Project, controlling for age, sex, race, ethnicity, and BMI. Thirty-eight percent of patients were screened for diabetes. Patients aged 60-70 years had higher odds of diabetes screening compared to patients aged 35-39 years (OR: 2.73, 95% CI: 2.67-2.78) . Men had lower odds of screening compared to women (OR: 0.91, 0.90-0.92) . Asian patients had higher odds of screening compared to White patients (OR 1.44, 1.42-1.46) . Patients with BMI ≥40 had higher odds of screening compared to patients with BMI 25-29.9 (OR: 1.34, 1.30-1.37) . Patients living in census tracts with the lowest median values of homes (OR: 0.93, 0.90-0.96) and with the lowest median household income (OR: 0.95, 0.91-0.99) had lower odds of diabetes screening compared to those in census tracts with the highest values. Patients living in census tracts classified as Ongoing Displacement/Low Income Susceptible to Displacement had lower odds of screening (OR: 0.96, 0.93-0.98) compared to those living in stable moderate mixed income tracts. We found insufficient screening rates and that gentrification and area-level socioeconomic factors were associated with lower diabetes screening, even after adjusting for individual demographic and clinical factors. Health care systems should consider addressing social needs and community resources as a path to improving preventive care.

Disclosure

T.Thomas: None. W.T.Dyer: None. L.A.Rodriguez: None. J.Schmittdiel: None.

Funding

Kaiser Permanente Northern California Community Benefit Programs; The Permanente Medical Group (TPMG) Delivery Science Fellowship Program; National Institute of Diabetes and Digestive and Kidney Diseases grant T32DK11668401. Dr. Schmittdiel received additional support from the NIDDK-funded Health Delivery Systems Center for Diabetes Translational Research (1P30 DK92924) .
71-OR: County Social Vulnerability and Disparities in Incidence of Diagnosed Diabetes
Authors: DUGANI SAGAR , LAHR BRIAN , BAILEY KENT R. , VELLA ADRIAN , MIELKE MICHELLE M.
Published: May 2022

Individual sociodemographic factors determine risk of diabetes. However, the association of a multidimensional social vulnerability index (SVI) and incident diabetes is unknown. We used CDC data on incidence of diagnosed diabetes, 2011-2018, in adults ≥20 years and defined county social vulnerability using two CDC indices: SVI minority health (SVI-MH; includes 6 dimensions) and SVI (includes 4 dimensions) . Trends in the annual age-adjusted incident diabetes rate per 1000 adults (AADR) were derived from weighted least squares regression. Year and SVI-MH/SVI were fitted nonlinearly with spline functions to test 2018 vs. 20fold-changes in AADR for levels of SVI-MH/SVI. Expressed by SVI-MH percentiles, low (10th) , median (50th) , and high (90th) vulnerability corresponded to overall AADR of 6.8, 8.5, and 10.5, respectively. In all years, counties with higher vulnerability (ie, higher SVI-MH) had significantly higher AADR. In 2018, compared to 2011, counties with high vulnerability showed a small AADR fold-decrease (0.97 [0.95-0.98]; P<.001) . The AADR fold-decrease was larger in counties with median vulnerability (0.92 [0.90-0.94]; P<.001) . In counties with low vulnerability, there was no AADR fold-change (P=.35) . Results for AADR analyzed by SVI were generally similar.

In summary, US counties with high SVI-MH/SVI had high AADR, and these indices could inform multidimensional interventions for diabetes prevention.

Disclosure

K.R. Bailey: None. A. Vella: Advisory Panel; Crinetics Pharmaceuticals, Inc., Rezolute, Inc., vTv Therapeutics, Zealand Pharma A/S. Other Relationship; Novo Nordisk. M.M. Mielke: Consultant; Biogen, LabCorp.

Funding

National Institute on Minority Health and Health Disparities (NIH K23 MD016230)
713-P: Is There a Correct Time to Measure Fasting Blood Sugar in Persons with Type 2 Diabetes Melitus?
Authors: SABOO BANSHI D. , VYAS TARJANI C. , CHENNAMSETTI KAUMUDI , PAREKH MALAY N. , PATEL VIDISHA , PRAJAPATI AAKASH M.
Published: May 2022

Aim: To decide most appropriate time to measure fasting blood sugar (FBS) using continuous glucose monitoring (CGM) .

Methodology: All persons who came to our clinic between 1st March to 30th August’21 were screened. Out of 60 persons with A1c <7.5, with FBS >130mg/dl who were measuring after 7.30am (using glucose meter) and having dinner before 9:30 pm, 28 persons who consented for CGM (Libre Pro) were included. Persons who were on SU/insulin or had nocturnal hypoglycaemia, T1DM, CRF, CLD, steroids or malignancy were excluded. The enrolled persons were told to measure their blood sugar between 5.30am to 6.30 am ; 6.30 am to 7.30am ; 7.30am to 8.30am on alternate days for 14 days by glucose meter along with CGM.

Results: Observed glucose values on different times were106±10mg/dl between 5.30 to 6.30am ;114±12mg/dl between 6.30 to 7.30am and 130±16mg/dl between 7.30 to 8.30am. These sugar values of all persons were correlated with CGM Libre pro data. AGP data of 2 out of the 28 persons have been shown in the graphs attached.

Discussion: It is a routine clinical practice to ask PWD to measure FBS but there is ambiguity in timings as no specification of timing is advised. It is important that patients measure fasting sugar around 6.30 am ± 1 hour as it correlates best with sunrise and has less effect of Dawn phenomenon.

Conclusion: To optimise treatment, persons with diabetes should be advised to measure their FBS before 7.30 am.

Disclosure

B.D.Saboo: None. T.C.Vyas: None. K.Chennamsetti: None. M.N.Parekh: None. V.Patel: None. A.M.Prajapati: None.