bluuebunny/crossref_metadata_2025 huggingface dataset:
154-LB: Cardiac MRI Findings in Young Adults with Childhood-Onset Type 2 Diabetes
Authors: DIAZ SANDRA VAZQUEZ , KATZ LORRAINE E. , GIDDING SAMUEL , WITSCHEY WALTER , CAPELLA COURTNEY , LITT HAROLD
Published: June 2020

Left ventricular (LV) hypertrophy and left atrial dilation are present at echocardiography in youth with T2D, however limited cardiac MRI data exist. We compared cardiac MRI findings in young adults with childhood- onset T2D (n=10) age 19-24 years, with published controls. History, physical exam and HbA1c were obtained. Hemodynamics were evaluated from cine imaging. For myocardial fibrosis, extracellular volume (ECV) fraction and native T1 relaxation times were assessed using a Modified Look-Locker Imaging sequence. Subjects were 8 females and 2 males, 7 black, 1 white, 1 mixed race and 1 Hispanic. Median (interquartile range IQR) age, diabetes duration, SBP, BMI and HbA1c were 19.9 (1.39) years, 7.8 (4.7) years, 121.5 (25) mmHg, 32.7 (9.5) kg/m2 and 10.3 (3.04)%, respectively. Subjects had a higher median (IQR) end systolic volume (ESV) index than published mean (SD) for healthy 20-29 year olds: 40.81 (5.74) ml/m2 vs. 29 (5.1) ml/m2 (p=0.007). However, they had lower LV mass index: 54.61 (9.01) g/m2 vs. 69 (8.1) g/m2 (p=0.01) and ejection fraction (EF): 50 (2.8)% vs. 66 (4.6)% (p=0.0049). Higher median (IQR) myocardial T1 of 1030.35 (44.6) msec vs. 965.6 (30.2) msec (p=0.005) and ECV fraction of 27.5 (1.5)% vs. 25 (3)% (p=0.012) were present. LV mass index directly correlated with HbA1c (rs= 0.69, p=0.03). Females had a higher median (IQR) ESV index of 40.81 (4.08) ml/m2 than published mean (SD) for females age 16-20 years of 29 (7.5) ml/m2 (p= 0.01), but lower EF of 50 (2.65)% vs. 64.3 (7.3)% (p= 0.01) and cardiac index of 3.08 (0.425) L/min/m2 vs. 3.85 (0.86) L/min/m2 (p= 0.01). ESV index positively correlated with HbA1c (rs=0.762, p=0.03). Males had a median (IQR) ESV index of 39.94 (25.7) ml/m2, LV mass index of 67.46 (13.9) g/m2 and EF of 54.95 (9.9)%. In this pilot study, young adult subjects with youth-onset T2D had a different myocardial phenotype compared to published normal values, characterized by undersized hearts relative to larger body size, poorer systolic performance and evidence for early onset myocardial fibrosis.

Disclosure

S. Vazquez Diaz: None. L.E. Katz: None. S. Gidding: None. W. Witschey: None. C. Capella: None. H. Litt: None.

Funding

University of Pennsylvania; National Institutes of Health (3T32DK7314-39S1)
1545-P: Associations of Carotenoids with Hyperuricemia: Results from a National Population Study
Authors: ZHANG NAN , ZHANG NAN , CHEN LULU
Published: June 2020

Background: Carotenoid are strong antioxidants rich in fruits and vegetables. Plasma carotenoids are good markers of fruit and vegetable intakes. We aimed to investigate the associations of plasma carotenoid levels with uric acid concentrations and hyperuricemia.

Method: A cross-sectional study using data from United States National Health and Nutrition Examination Survey from 2001 to 2006 was conducted. After excluding missing data of uric acid and carotenoids levels, 19124 participants aged 0-85 were included in the study. Associations of carotenoids with uric acid or hyperuricemia were conducted using multivariate linear regression or logistic regression.

Results: In the study, 1992 participants had hyperuricemia. After adjustments of age, gender, race, education, cotinine, physical activity, alcohol drinking, energy intake, body mass index, C-reactive protein, estimated glomerular filtration rate (eGFR), non-high-density lipoprotein cholesterol (nonHDL-C), HDL-C and hypertension, each unit increase of a-carotene, trans-b-carotene, cis-b-carotene, trans-lycopene, combined lutein/zeaxanthin, and b-cryptoxanthin was associated with 33.01 (95% CI= -50.57 to -15.44), 10.59 (95% CI= -14.76 to -6.41), 169.40 (95% CI=-235.98 to -102.83), 13.05 (95% CI=-24.53 to -1.57), 27.99 (95% CI=-43.84 to -12.14), and 36.14 (95% CI=-55.16 to -17.12) mmol/L decrease of uric acid, respectively and odds ratios of above carotenoids and hyperuricemia were 0.05 (95% CI= 0.01 to 0.5), 0.31 (95% CI= 0.14 to 0.68), <0.001 (95% CI=<0.001 to 0.003), 0.37 (95% CI=0.20 to 0.66), 0.22 (95% CI=0.07 to 0.77), and 36.14 (95% CI=0.02 to 0.20) respectively.

Conclusion: Carotenoids were inversely associated with uric acid levels and hyperuricemia risk. Higher plasma carotenoids may be beneficial against hyperuricemia. Increasing carotenoids concentrations, for instance by fruits and vegetables intake, as a novel preventive treatment for hyperuricemia deserves further investigation.

Disclosure

N. Zhang: None. N. Zhang: None. L. Chen: Consultant; Self; AstraZeneca, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S.
155-OR: ADA Presidents’ Select Abstract: Symptom Responses to Hypoglycemia Are Related to Connectivity Change between the Thalamus and Frontal Lobes
Authors: JACOB PETER , NWOKOLO MUNACHISO , ODALY OWEN , ZELAYA FERNANDO O. , AMIEL STEPHANIE A. , CHOUDHARY PRATIK
Published: June 2020

Neuroimaging studies highlight the importance of thalamic activation in response to hypoglycemia in people with and without type 1 diabetes (T1D). This activation is characteristically attenuated in impaired awareness of hypoglycaemia (IAH), a major risk factor for severe hypoglycemia. We investigated changes in connectivity of the thalamus with other brain regions during hypoglycemia.

Methods: Fourteen people without diabetes (no diabetes, ND), 15 with T1D and normal awareness of hypoglycemia (NAH) and 22 with IAH, all right-handed, age, sex and gender matched, underwent a hyperinsulinemic glucose clamp during which we acquired blood oxygen level dependent fMRI at euglycemia (90mg/dL) and at onset of hypoglycemia (48mg/dL). Connectivity was studied using the CONN toolbox in SPM12. A thalamic seed was used in a seed-to-voxel analysis with and without the increase in symptoms at hypoglycemia as an explanatory regressor variable.

Results: Symptom scores in response to hypoglycemia rose earliest and to the greatest levels in NAH (11.0 to 18.3, p= 0.029). The rise in symptom scores in ND was not significant at this timepoint (9.2 to 13.8, p= 0.057), whilst IAH showed no symptom change (10.5 to 9.8, p= 0.7). In ND, hypoglycemia increased thalamic connectivity with the right frontal pole (pFDR = 0.018). This did not occur in diabetes, either in NAH or IAH. The NAH group demonstrated a positive relationship between change in symptoms with change in connectivity of the thalamus and a left frontal pole region (pFDR = 0.035), whereas an overlapping area had a negative correlation in ND (pFDR = 0.001). There was no correlation in IAH.

Conclusion: During hypoglycemia, those with T1D display aberrantly enhanced thalamic connectivity with brain regions responsible for complex behavior. Disruption of this network occurs in IAH and may be the mechanism for failure of perception of the onset of hypoglycemia and reduced hypoglycemia avoidance behaviors, increasing severe hypoglycemia risk.

Disclosure

P. Jacob: None. M. Nwokolo: Other Relationship; Self; Sanofi. O. ODaly: None. F.O. Zelaya: None. S.A. Amiel: Advisory Panel; Self; Medtronic, Novo Nordisk A/S, Roche Pharma. Other Relationship; Self; Diabetes UK. P. Choudhary: Advisory Panel; Self; Abbott, Eli Lilly and Company, Insulet Corporation, Medtronic. Research Support; Self; European Union, JDRF. Speaker’s Bureau; Self; Dexcom, Inc., Novartis AG, Novo Nordisk A/S, Sanofi-Aventis.

Funding

JDRF (3-SRA-2017-484-S-B)
1553-P: Combination of Diabetes Mellitus and Lack of Habitual Physical Activity Is a Risk Factor for Functional Disability in Japanese
Authors: FUJIHARA KAZUYA , YAMADA MAYUKO H. , MATSUBAYASHI YASUHIRO , KITAZAWA MASARU , KANEKO MASANORI , YAMAMOTO MASAHIKO , YAGUCHI YUTA , YAHIRO TAKUYA , KODAMA SATORU , KATO KIMINORI , SONE HIROHITO
Published: June 2020

Declining healthy life expectancy due to functional disability is relevant and urgent not only because of its association with decreased quality of life but also for its enormous socioeconomic impact. Thus, we analyzed a population-based retrospective cohort study including 9,673 community dwelling Japanese adults (4,420, men) aged 39-98 years in 2012-2017. Functional disability was defined as a condition meeting Japan’s new long-term care insurance certification requirements for the need of assistance in the activities of daily living whether by caregivers or assistive devices. Cox proportional hazards regression model identified variables related to functional disability. Median follow-up was 3.7 years. During the study period, 165 disabilities occurred in the overall study population. Multivariate analysis showed that diabetes (hazard ratio [HR] 1.74 (95% CI: 1.12-2.68)), no physical activity habit (HR 1.83 (1.27-2.65)), and low BMI category (18.5 kg/m2 >) (HR 1.63 (1.02-2.63)) presented increased risks for disability. The prevalence ratio of 0, 1, 2, 3 and 4 conditions (diabetes, hypertension, dyslipidemia, and physical activity habits) was 12.8%, 40.0%, 32.6%, 12.9 and 1.7%, respectively. HR for disability increased with the number of risk factors (HR of individuals with 1, 2, 3 and 4 conditions, 1.34 (0.71-2.52), 1.95 (1.04-3.63), 2.11 (1.07-4.15), and 3.96 (1.59-9.99) vs. individuals with none of those conditions as a ref.). HR for disability among diabetes patients with and without a physical activity habit was 1.68 (0.70-4.04) and 3.19 (1.79-5.70), respectively, compared to individuals without diabetes with a physical activity habit. This shows that the combination of diabetes and lack of habitual physical activity is predictive of functional disability in Japanese. Habitual physical activity attenuates the risk of functional disability in patients with diabetes.

Disclosure

K. Fujihara: None. M.H. Yamada: None. Y. Matsubayashi: None. M. Kitazawa: None. M. Kaneko: None. M. Yamamoto: None. Y. Yaguchi: None. T. Yahiro: None. S. Kodama: None. K. Kato: None. H. Sone: Research Support; Self; Kyowa Hakko Kirin Co., Ltd., Novartis AG, Ono Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co.

Funding

Japan Society for the Promotion of Science (18K17897)
156-OR: Fear of Hypoglycemia in People with Type 1 Diabetes and Problematic Hypoglycaemia: A Mismatch between Worry and Behaviour?
Authors: MACLEAN RORY H. , JACOB PETER , HAYWOOD SEAN , CHOUDHARY PRATIK , HELLER SIMON R. , TOSCHI ELENA , KARIYAWASAM DULMINI , ANDERBRO THERESE C. , AMIEL STEPHANIE A.
Published: June 2020

Problematic hypoglycemia complicates insulin therapy in >25% of adults with type 1 diabetes (T1D). Previous work has identified relationships between cognitive barriers to hypoglycemia avoidance and impaired awareness of hypoglycemia (IAH) with recurrent severe episodes (SH). We investigated fear of hypoglycemia in people with IAH and SH enrolling in a trial of interventions to restore hypoglycemia awareness (“HARPdoc” ClinicalTrials.gov NCT02940873) and compared their data with T1D clinic attenders not enriched for problematic hypoglycemia.

Method: Adults with T1D (HARPdoc cohort; n=98, age 54±13 yr, 56% female, T1D duration 40±15 yr) and problematic hypoglycemia (Clarke score 5.5±1.0) completed the Hypoglycemia Fear Survey II (HFS), Hyperglycemia Avoidance Scale (HAS) and anonymous 12 month SH recall forms. The T1D clinic comparator group was n=467, age 46±14 yr, 50% female, T1D duration 30±13 yr.

Results: In preliminary analyses, the HARPdoc cohort (n=88) reported higher scores on total HFS (p=0.018) and its worry subscale (p<0.0001) than the comparator. Behavior subscale scores were lower (p<0.0001). In the HARPdoc cohort, 25% (n = 22) reported low worry about hypoglycemia despite high SH risk (vs. 8% in the comparator). People with high worry scored the HAS worry subscale higher (p<0.001). The HARPdoc cohort were grouped by frequency of SH (<2; 2 - 4; 5-12 and >12 SH per yr). Worry scores increased with higher SH rates (p=0.004). Behavior scores increased (p=0.041) but not above the comparator 75th centile. In the ’maintaining high glucose’ subset of HFS behavior items, scores increased between the high SH rate groups (p=0.042) but not the lower rate groups.

Conclusion: The majority of people with significant hypoglycemia problems show appropriately increased worry but not corresponding increases in behavior scores. A subgroup show inappropriately low worry. Inability to change behaviors, and worry about hyperglycemia, may be barriers to avoiding SH.

Disclosure

R.H. Maclean: None. P. Jacob: None. S. Haywood: None. P. Choudhary: Advisory Panel; Self; Abbott, Eli Lilly and Company, Insulet Corporation, Medtronic. Research Support; Self; European Union, JDRF. Speaker’s Bureau; Self; Dexcom, Inc., Novartis AG, Novo Nordisk A/S, Sanofi-Aventis. S.R. Heller: Advisory Panel; Self; Eli Lilly and Company, Novo Nordisk A/S, Zealand Pharma A/S. Speaker’s Bureau; Self; AstraZeneca, Novo Nordisk A/S. Other Relationship; Self; MannKind Corporation. E. Toschi: None. D. Kariyawasam: None. T.C. Anderbro: None. S.A. Amiel: Advisory Panel; Self; Medtronic, Novo Nordisk A/S, Roche Pharma. Other Relationship; Self; Diabetes UK.

Funding

JDRF (4-SRA-2017-266-M-N)
1561-P: Racial Disparity May Exist in Patients with Diabetes Mellitus Hospitalized with Acute Pancreatitis
Authors: CHOI NICOLE , GARCIA MONIKA E. , ZAKHARY BISHOY L. , FIREK MATTHEW A. , KIM DANIEL I. , JACKSON CHRISTIAN S. , FIREK ANTHONY
Published: June 2020

Introduction: Acute pancreatitis (AP) is the most common reason for hospitalizations for gastrointestinal disorders in the United States. Diabetes mellitus (DM) is known to increase the risk for AP by almost 3-fold. Single center studies have demonstrated demographic disparities in AP patients with DM. The identification of AP and DM patients at risk may provide clues to etiology and develop population preventative measures to lower AP-related hospitalizations. Our primary aim was to evaluate demographic trends in patients with DM and AP using a large national database.

Methods: We extracted data from the Healthcare Cost and Utilization Project Nationwide Inpatient Sample database, from 2012-2014. International Classification of Diseases 9th Version, and used clinical modification codes for adult patients hospitalized with primary diagnosis of AP.

Results: There were 1,310,385 primary admissions for AP during the study period. 27.4% were diagnosed with AP-DM. Patients with AP-DM were older in age compared to AP only (p<0.001). Majority of AP only patients were female (50.4%). Majority of patients with AP-DM were male (55.1% without complications and 50.7% with complications). Non-Hispanic Whites (NHW) had the highest prevalence of AP without DM. All other races had greater prevalence of AP-DM, including the largest discrepancy in African-Americans (AA) and Hispanics. For NHW, 67.6% did not have DM, 59.0% and 53.3% had DM without and with complications, respectively. For AA, 14.5% did not have DM, 18.8% and 24.4% had DM without and with complications, respectively.

Conclusions: This study is the first to demonstrate a racial disparity in AP patients with DM on a national scale. Patients with AP-DM were likely to be older, male, and AA compared to NHW, which is consistent with previous data. Multiple factors between NHW, AA and Hispanics which include but are not limited to genetic, socioeconomic, and cultural factors may be determinants of this disparity.

Disclosure

N. Choi: None. M.E. Garcia: None. B.L. Zakhary: None. M.A. Firek: None. D.I. Kim: None. C.S. Jackson: None. A. Firek: None.
1567-P: Burden of Diabetes Mellitus in Adults in the Americas, 1990-2017: Global Burden of Disease Study
Authors: COUSIN EWERTON , SCHMIDT MARIA I. , DUNCAN BRUCE B.
Published: June 2020

Background: Many countries of the Americas have a high prevalence of diabetes, but the disease burden related to diabetes in the Americas has been little investigated. We aim to describe current diabetes burden in the Americas and changes from 1990 to 2017.

Methods: We used estimates from the 2017 GBD Study for incidence, prevalence, deaths, disability-adjusted life years (DALYs) and risk factors in American regions for those aged 25+.

Results: Age-standardized incidence increased 20.8% from 1990 to 2017. Crude prevalence increased 40%, reaching 11.7% (95%UI: 9.4% - 11.2%), the highest rates being in North America and Central Latin America. A total of 352,769 (95% UI 340,170-366,155) deaths due to diabetes occurred in 2017. Central Latin America and the Caribbean presented the highest disease burden. Age-standardized DALYs increased 18% overall, with marked variation across nations (Figure). Main risk factors were high BMI and dietary characteristics.

Conclusion: Burden of diabetes in the Americas is high, being disproportionately large in Central Latin America and the Caribbean. High BMI and inadequate nutrition appear to be the main culprits. Public policies aiming to decrease diabetes incidence by acting on these and other risk factors, and to provide effective and cost-efficient care for all people with diabetes are much needed.

Figure: Percentage change in the age-standardized rate of DALYs, 1990-2017.

Disclosure

E. Cousin: None. M.I. Schmidt: None. B.B. Duncan: None.

Funding

Bill & Melinda Gates Foundation; Research Support Foundation of Rio Grande do Sul
157-LB: Nocturnal Alarms: A Potential Barrier to Diabetes Technology Use
Authors: COBRY ERIN C. , BERGET CARI , MESSER LAUREL H. , WADWA R. PAUL , VIGERS TIMOTHY B. , PYLE LAURA , SLOVER ROBERT H. , DRISCOLL KIMBERLY A. , FORLENZA GREGORY P.
Published: June 2020

High quality sleep is important for individuals with type 1 diabetes (T1D). Alarms associated with using diabetes technology may cause sleep disturbance. The objective of this study was to describe nighttime alarm frequency in a sample of youth using Hybrid Closed-Loop (HCL) technology and to compare alarm frequency between baseline Sensor Augmented Pump (SAP) and HCL.

Youth starting the 670G participated in an observational study. Data on sensor wear, HCL use, and frequency of nighttime alarms (10pm-6am) were collected while using 670G in SAP (before starting HCL), 2 weeks after starting HCL, and during clinic visits 3, 6, 9 and 12 months after starting HCL.

Forty-one youth (age 15 [12, 17] yrs, T1D duration 7.2 [4.6, 10.2] yrs, HbA1c 8.8±1.5%) were included. The median number of alarms per night with HCL use ranged from 1.4 to 2.0 across the study compared to a median of 2.1 alarms per night with baseline SAP use. There was no difference in alarm frequency with HCL use compared to SAP use (p=0.40, adjusted for percent HCL use).

Experiencing two device alarms per night is likely to cause significant sleep disruption for youth and their parents, suggesting device alarms may reduce quality of life and be a barrier to diabetes technology use. Further research is needed to assess the impact of device alarms on sleep disruption for youth with T1D and their parents, and to identify strategies to reduce nighttime alarm frequency for youth using diabetes technology.

Disclosure

E.C. Cobry: None. C. Berget: None. L.H. Messer: Consultant; Self; Capillary Biomedical, Inc., Clinical Sensors, Inc., Dexcom, Inc., Tandem Diabetes Care. R. Wadwa: Advisory Panel; Self; Eli Lilly and Company, Medtronic. Research Support; Self; Dexcom, Inc., Eli Lilly and Company, MannKind Corporation, Medtronic, Novo Nordisk Inc., Tandem Diabetes Care. T.B. Vigers: None. L. Pyle: None. R.H. Slover: None. K.A. Driscoll: None. G.P. Forlenza: Advisory Panel; Self; Medtronic. Consultant; Self; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care. Research Support; Self; Abbott, Dexcom, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care.

Funding

National Institutes of Health (K12DK094712); JDRF (5-ECR-2019-736-A-N)
1572-P: Neighborhood Investments and Cardiometabolic Health in Two Predominantly African-American Communities: A Natural Experiment Study
Authors: GARY-WEBB TIFFANY , DUBOWITZ TAMARA , BOGART TIMOTHY A. , DASTIDAR MADHUMITA GHOSH , TROXEL WENDY M.
Published: June 2020

Background: Neighborhood disadvantage is a robust and independent risk factor for poor cardiometabolic health, however, causal relationships have been difficult to establish. We used a natural experiment design to examine neighborhood investment on cardiometabolic risk factors among a randomly selected cohort of residents from two, low-income, urban, and predominately African American matched neighborhoods.

Methods: The sample included 532 participants (80% female; mean age=59 years; mean income=$21,073). During the study period (2016-2018), the intervention neighborhood received substantially more publicly-funded investments (housing and commercial investment) than a demographically matched comparison neighborhood. Difference-in-difference analyses tested for differential change between the neighborhoods in BMI, HbA1c, HDL-c, and SBP and DBP. Covariates included age, sex, income, education, presence of children in the home, length of residence in neighborhood, and BMI (for all outcomes except BMI).

Results: Contrary to expectations, relative to the comparison neighborhood, we saw a net increase in DBP (β=3.00, SE=1.24; p =.02) and a marginally significant increase in SBP (β= 4.30, p = .07) in the intervention neighborhood. In contrast, for HbA1c and HDL-c, intervention neighborhood residents showed improvements in these outcomes, relative to the comparison neighborhood; however, the effects were non or marginally significant after covariate adjustment (p=.12 for HbA1c and p=0.06 for HDL-c). There were no significant changes in BMI.

Conclusion: Our findings suggest that the potential cardiometabolic benefits of neighborhood revitalization may manifest over a longer period of follow-up, and that there may be some interim consequences for certain health outcomes, in the process of neighborhood change. These findings highlight the importance of examining root causes of health disparities and using robust study designs.

Disclosure

T. Gary-Webb: None. T. Dubowitz: None. T.A. Bogart: None. M. Ghosh Dastidar: None. W.M. Troxel: None.

Funding

National Heart, Lung, and Blood Institute (HL131531)
1577-P: How Does Military Service Impact Risk for Diabetes in African Americans with a History of Adverse Childhood Experiences?
Authors: WARDIAN JANA L. , STONE EMILY
Published: June 2020

Background: African Americans (AA) in the general population have double the odds for developing diabetes (DM). In addition, older age and a score of 4+ on the Adverse Childhood Experiences (ACE) inventory has been associated with increased risk for DM; education has been found to moderate risk. In addition, military service disproportionately attracts those with high ACE; however, educational opportunity is more readily available. We explored the effect of military service on the risk for developing diabetes in AA with high ACE.

Methods: We analyzed 2009-2012 BRFSS data from U.S. states opting to include an ACE module (n=117,084). AA (n=8715) comprise about 9.3% of this sample after weighted for representativeness.

Results: In the overall sample, age (OR= 1.04, 95% CI = 1.05-1.05), high ACE (4+; OR = 1.38, 95% CI =1.24-1.53), and being AA (OR = 2.1, 95% CI = 1.88-2.34) all significantly (p < .001) increase likelihood of developing DM, and education reduces it (OR = 0.80, 95% CI = 0.77-0.83; p < .001). Controlling for age, males are more likely to have a history of military service (OR = 23.7, 95% CI = 20.9-26.9, p < .001). Those with high ACE are more likely to enlist (OR = 1.66, 95% CI = 1.45-1.90, p < .001) and AAs are more likely to enlist (OR = 1.27, 95% CI =1.09-1.47, p < .01) compared to other races. Furthermore, when examining just AAs, those with military service have an increased likelihood of developing DM (OR = 1.24, 95% CI = 1.12-1.38). However, 2009-10 data show current active duty and those who served within one year may experience some protective effects; when controlling for age, they have the same or decreased DM compared to other veterans or civilians.

Discussion: Military service does not buffer the risk for DM in AAs with high ACE, regardless of education. This may be partially due to an increase in ACE among those with a history of military service and the inclusion of the Veteran Administration population, which tend to have increase co-morbidities.

Disclosure

J.L. Wardian: None. E. Stone: None.
1578-P: Differences in Gut Microbiota between Diabetic and Nondiabetic Subjects
Authors: MURABAYASHI MASAYA , DAIMON MAKOTO , MURAKAMI HIROSHI , MATSUHASHI YUKI , KAMBA AYA , MIZUSHIRI SATORU
Published: June 2020

Objective: Since gut microbiota activity results in the production of specific microbial-derived metabolites (short-chain fatty acids) and structural components (LPS and peptidoglycans), changes in such microbiota composition appears to be involved in pathophysiology of common chronic disorders such as diabetes. Indeed, differences in gut microbiota between diabetic and nondiabetic subjects have been reported frequently in many ethnic groups, but not frequently in Japanese populations.

Research Design and Methods: Among participants of the population-based Iwaki study of Japanese held in 2016, those with information of gut microbiota evaluated using 16S rRNA sequencing were included in the study (gender (M/F): 446/672; age: 54.8±15.6). Diabetic (n=122): either on treatment for diabetes or HbA1c levels ≥6.5% or FBG ≥126 mg/dl; Nondiabetic (n=996): others.

Results: When examined the differences in gut microbiota in taxonomy category genus, proportions of several genuses were different between diabetic and nondiabetic subjects. Especially, proportions of the genus Streptococcus (4.79±9.53% vs. 2.12±3.74%, p=0.011) and Lactobacillus (3.11±8.10% vs. 0.344±1.95%, p <0.01), which are known to produce lactic acid, were higher, and genus Blautia (5.52±4.26% vs. 7.31±4.37%, p <0.01) and Bacteroides (8.14±9.38% vs. 10.8±7.84%, p <0.01), which are known to produce short chain fatty acids, were lower in diabetics subjects than those in nondiabetic subjects.

Conclusions: Differences in gut microbiota proportion were also found between diabetic and nondiabetic subjects in a Japanese population. Since lactic acid is known to have an effect of suppressing pathogenic bacteria, the increase in lactic acid producing bacteria may have effects against infection. Further, since short chain fatty acids act as signal transduction molecules that affect energy metabolism, the decrease in short-chain fatty acid producing bacteria may be involved in the development of diabetes.

Disclosure

M. Murabayashi: None. M. Daimon: None. H. Murakami: None. Y. Matsuhashi: None. A. Kamba: None. S. Mizushiri: None.
1579-P: Prevalence and Incidence of Obesity and Diabetes in the United States, 2011-2017
Authors: NIELSEN JANNIE , GREGG ED , VENKAT NARAYAN K.M. , CUNNINGHAM SOLVEIG A.
Published: June 2020

Recent studies in the U.S. have shown that incidence of diagnosed diabetes decreased and prevalence plateaued after 2010 despite a modest increase in obesity prevalence. If the reduction in diabetes incidence is driven by changing obesity levels, prevalence may be an inadequate metric. Therefore, we investigated changes in prevalence and incidence of obesity and diabetes in adults in the United States during a 17 year period, 2001-2017.

We analyzed adult (≥20years) anthropometric records and diabetes status (prediabetes and diabetes combined) from the U.S. national representative Panel Study of Income Dynamics, 2001-2017. We used Poisson models to estimate the prevalence biannually from 2001-2017 and incidence of obesity (cases/1000 person years, PY) over 4 periods (2001-2005; 2005-2009; 2009-2013; 2013-2017). All rates were age- and sex-adjusted; survey weights were applied.

Prevalence of obesity increased from 20.9% (95% CI, 19.4-22.5) in 2001 to 26.4 (95% CI, 25.0-27.8) in 2009 to 29.5% (95% CI, 28.1-31.0) in 2017 (p<0.001), while prevalence of diabetes over the same period increased from 7.5% (95% CI, 6.6-8.4) to 10.0 (95% CI, 9.0-11.0) to 11.8% (95% CI, 10.8-12.7) (p<0.001).

The incidence of obesity changed over time: Compared to an obesity incidence of 29.3/1000 PY (95% CI, 26.0-35.5) in 2001-2005, the incidence increased to 31.7/1000 PY (95% CI,29.7-33.7) in 2005-2009, decreased to 28.8/1000 PY (26.3-31.4) in 2009-2013, and increased to 34.0/1000 PY (95% CI, 31.1-36.7) in 2013-2017 (p<0.001). There was an overall linear increase in diabetes incidence across periods from 2001-2005 to 2013-2017 (p<0.001): In 2001-2005, incidence was 11.9 per 1000 PY (95% CI, 10.6-13.1); in 2005-2009, 12.4/1000 PY (10.7-14.2); in 2009-2013, 13.3/1000 PY (11.5-15.2); and in 2013-2017 14.0/1000 PY (95% CI, 12.2-15.8).

In contrast to other U.S. studies of diabetes incidence, our results show no decline during the 2010s. This may be explained by our findings of an increasing incidence of obesity in the same population.

Disclosure

J. NIelsen: None. E. Gregg: None. K. Narayan: None. S.A. Cunningham: None.

Funding

Independent Research Fund Denmark (DFF-7025-00053B); National Institute of Diabetes and Digestive and Kidney Diseases (P30DK111024, 1R01DK115937)
158-LB: iSpy: A Pilot Study of a Novel Carbohydrate Counting Smartphone App for Youth with Type 1 Diabetes
Authors: CHOI ELIZABETH , ALFONSI JEFFREY , ARSHAD TAHA , SAMMOTT STACIE-ANN , PAIS VANITA , STINSON JENNIFER , PALMERT MARK
Published: June 2020

Introduction: Carbohydrate counting is an important part of diabetes management, but it is difficult and can negatively impact quality of life. To address this challenge, a novel mobile application (app) called iSpy that uses computer vision and artificial intelligence to identify foods, estimate their carbohydrate content, and provide real-time feedback to users, was developed.

Objective: To evaluate iSpy’s functionality among youth aged 10 to 17 years (mean age = 14 years) with type 1 diabetes mellitus (T1DM).

Design/Methods: A pilot study among 44 youth (22 each randomized to intervention (iSpy) or control) was conducted to assess: (1) whether iSpy leads to improved carbohydrate counting ability (accuracy and speed) measured using standardized meal plates at baseline and at the end of the 12-week study; and (2) implementation outcomes such as app acceptability and technical problems.

Results: Compared to the control group, the intervention group improved its carbohydrate counting accuracy (total grams per meal) over the 12-week study period (p=0.007). Moreover, the percentage of times the carbohydrate estimate of a particular item was off by more than 10g from the true value was reduced by 9.9% (p=0.047). There was no statistically significant difference in total time to count carbohydrates. Qualitative interviews and app acceptability scale scores across 7 domains were primarily positive. 43% of iSpy participants were still using the app and logged at least once per 2 weeks at the end of the study. No major technical challenges were identified.

Conclusion(s): Participants using iSpy demonstrated improved carbohydrate counting accuracy and positive acceptability. iSpy has the potential to improve diabetes management, which should be further tested in a formal randomized controlled trial.

Disclosure

E. Choi: Other Relationship; Self; Inner Analytics Inc. J. Alfonsi: Other Relationship; Self; Inner Analytics Inc. T. Arshad: None. S. Sammott: None. V. Pais: None. J. Stinson: None. M. Palmert: None.

Funding

Physician Services Incorporated Foundation
1580-P: Hemoglobin A1c (HbA1c) Trajectories of Youth with Type 1 Diabetes (T1D) over 10 Years Postdiagnosis from Three Continents
Authors: SHERR JENNIFER , SCHWANDT ANKE , PHELAN HELEN , CLEMENTS MARK A. , HOLL REINHARD W. , BENITEZ-AGUIRRE PAUL Z. , MILLER KELLEE , WOELFLE JOACHIM , DOVER THOMAS , MAAHS DAVID M. , FRÖHLICH-REITERER ELKE , CRAIG MARIA E.
Published: June 2020

Distinct HbA1c trajectories have previously been identified in youth with established T1D. We used data from 3 international registries to evaluate whether distinct HbA1c trajectories occur from T1D onset. Participants were <18 yrs old at diagnosis and had at least 1 HbA1c measured within 12 months post-diagnosis, along with ≥3 duration-year aggregated HbA1c values over 10 yrs of follow-up. 7,292 participants from the Australasian Diabetes Data Network, 39,226 from the German/Austrian Diabetes Prospective Follow-up, and 3,704 from the U.S. T1D Exchange were included. Group-based modelling identified unique HbA1c trajectories from onset of T1D. Five distinct trajectories occurred in all 3 registries (Figure), with similar patterns of proportion by group. Over 50% had stable HbA1c in or near target. Conversely, ∼15% in each registry were characterized by stable HbA1c >8.0%, and ∼11% had values that began in or near target but then increased. Only ∼5% of youth were suboptimal from diagnosis with an increasing HbA1c. This group differed from others with higher rates of minority status and older age at diagnosis across all 3 registries (p≤0.001). We observed similar post-diagnostic HbA1c patterns across 3 international registries. Identifying youth at greatest risk for deterioration in HbA1c over time may allow clinicians to intervene early to avert increasing HbA1c.

Disclosure

J. Sherr: Advisory Panel; Self; Bigfoot Biomedical, Cecelia Health. Consultant; Self; Eli Lilly and Company, Lexicon Pharmaceuticals, Inc., Medtronic, Sanofi, T1D Exchange. A. Schwandt: None. H. Phelan: None. M.A. Clements: Consultant; Self; Glooko, Inc. Other Relationship; Self; Glooko, Inc. R.W. Holl: None. P.Z. Benitez-Aguirre: None. K. Miller: None. J. Woelfle: Advisory Panel; Self; Novo Nordisk A/S. T. Dover: None. D.M. Maahs: Advisory Panel; Self; Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S. Consultant; Self; Abbott, Sanofi. Research Support; Self; Bigfoot Biomedical, Dexcom, Inc., Roche Diabetes Care, Tandem Diabetes Care. E. Fröhlich-Reiterer: None. M.E. Craig: None.

Funding

German Centre for Diabetes Research (FKZ82DZD01402); German Diabetes Association; European Foundation for the Study of Diabetes; INNODIA; The Leona M. and Harry B. Helmsley Charitable Trust
1596-P: Evaluating Reports of Pancreatic Malignancy and Liraglutide: A Pharmacovigilance Study of the FDA Adverse Event Reporting System
Authors: ALVAREZ CARLOS A. , TENG CHENGWEN , MANSI ISHAK
Published: June 2020

Background: Animal studies have raised concerns about glucagon-like peptide-1 (GLP-1) receptor agonist usage and incidence of pancreatic premalignant changes. Although randomized controlled Trials (RCTs) have not described this association, smaller size and shorter duration of RCTs may limit their statistical power to find such an association. Liraglutide utilization has been increasing due to the prescribing label change and indication for cardiovascular disease.

Aim: Evaluate reporting associations between pancreatic cancer and liraglutide using FDA Adverse Event Reporting System (FAERS).

Methods: FAERS reports from 1 January 2004 to 31 December 2018 were included in the study. The Medical Dictionary for Regulatory Activities (MedDRA) was used to identify pancreatic cancer cases. Reporting odds ratios (RORs) and corresponding 95% confidence intervals (CIs) for the reporting associations among liraglutide, metformin, glyburide, glipizide, and empagliflozin and pancreatic cancer were calculated.

Results: A total of 10,015,622 reports were considered. Pancreatic cancer RORs (95% CI) in descending order were: Liraglutide 32.47 (30.53-34.52), metformin 6.85 (6.52-7.19), glyburide 5.24 (4.48-6.14), glipizide 3.83 (3.32-4.42), and empagliflozin 3.42 (2.50-4.67). The number of reports for pancreatic cancer increased from 2735 in 2010 to 4967 in 2018.

Conclusion: Liraglutide had greater reporting associations when compared to other antidiabetes medications. Further studies are needed to determine if this signal is causal.

Disclosure

C.A. Alvarez: None. C. Teng: None. I. Mansi: None.

Funding

National Institutes of Health (K08DK101602)
1599-P: Receipt of Comprehensive Diabetes Care in U.S. Adults with Diabetes: 2005-2016
Authors: SHIN JUNG-IM , WANG DAN , FERNANDES GAIL , DAYA NATALIE R. , GRAMS MORGAN , GOLDEN SHERITA , RAJPATHAK SWAPNIL , SELVIN ELIZABETH
Published: June 2020

Background: Quality health care delivery is critical to prevent diabetes-related complications. However, there is limited national information about the extent to which a diverse population of U.S. adults with diabetes receive the American Diabetes Association (ADA) recommended comprehensive diabetes care.

Methods: We conducted a cross-sectional analysis of 4,114 adults aged ≥20 with self-reported diabetes from the National Health and Nutrition and Examination Survey (NHANES) 2005-2016. We estimated the prevalence and identified predictors of receipt of comprehensive diabetes care (i.e., meeting all 5 criteria in the past year: having a primary doctor for diabetes care and number of visits for this doctor ≥1, HbA1c testing, eye exam, foot exam, and cholesterol test).

Results: Among adults with diabetes, 10.9% (95% CI, 9.3-12.6%) had received comprehensive care in the past year (all 5 criteria). Overall, 71.7% (95% CI, 69.6-73.7%) met ≥3 criteria. In a fully adjusted model, those less likely to receive comprehensive care were current smokers, and adults with lower socioeconomic status, lack of insurance, or depression (Table).

Conclusions: Only 1 out of 10 U.S. adults with diabetes receive ADA recommended comprehensive diabetes care. Efforts are needed to improve health care delivery and equity in diabetes care. Insurance status and depression are important modifiable determinants of comprehensive care.

Disclosure

J. Shin: None. D. Wang: None. G. Fernandes: Employee; Spouse/Partner; Janssen Pharmaceuticals, Inc. Employee; Self; Merck Sharp & Dohme Corp. N.R. Daya: None. M. Grams: Other Relationship; Self; DCI. S. Golden: None. S. Rajpathak: Employee; Self; Menarini Group. E. Selvin: None.
16-OR: Codesigning an Intervention for Adults with New-Onset Type 1 Diabetes to Improve Psychological and Social Adaptation
Authors: DUE-CHRISTENSEN METTE , JOENSEN LENE E. , SARRE SOPHIE , WAD JULIE L. , ROMANCZUK EWA , FORDE RITA , WILLAING INGRID , FORBES ANGUS
Published: June 2020

Adults newly diagnosed with type 1 diabetes (T1D) can experience significant psychosocial disruption, leading to maladaptive emotional and behavioral responses which may increase the risk of future complications. The aim of the study was to co-design an intervention with people with diabetes (PWD) and healthcare-professionals (HCPs) to address the psychosocial disruption associated with new onset T1D in adults. We used a co-design approach to stimulate the target populations to reflect on their experiences and generate ideas for the intervention. This involved the use of illustrations depicting common experiences of the time of diagnosis identified in a previous study among PWD and HCPs. Illustrations were used as conversation tools in six parallel workshops exclusively for PWD (n=24) and HCPs (n=55); and four workshops that brought PWD (n=31) and HCPs (n=19) together to prioritize intervention components. Data comprising of transcribed audio recordings and notes from participants were analyzed thematically with a view to intervention development. The workshops identified that the intervention should be phasic, with an initial focus on the psychosocial disruption of diagnosis, followed by the early experience of diabetes and how to adapt positively to a life with it. Participants constructed two integrated intervention components: 1) one-to-one sessions soon after diagnosis, with a HCP trained in using a psychologically modelled conversation tool addressing PWD’s experiences, thoughts and feelings about the diagnosis; and 2) a group-based intervention addressing common diabetes challenges, emotional issues and thinking traps, focusing on normalizing emotions and developing strategies for managing diabetes in day-to-day life. The co-design process revealed the benefit of adopting a bio-psycho-social perspective and introducing methods of support involving both HCPs and peers to activate positive adaptive strategies in adults with new onset T1D.

Disclosure

M. Due-Christensen: Research Support; Self; Novo Nordisk Foundation. Stock/Shareholder; Self; Novo Nordisk A/S. L.E. Joensen: None. S. Sarre: None. J.L. Wad: None. E. Romanczuk: None. R. Forde: None. I. Willaing: None. A. Forbes: None.

Funding

National Institute for Health Research (PB-PG-0317-20012); Novo Nordisk Foundation (NNF17OC0028274)
1609-P: Diabetes and Risk of All-Cause and Cancer-Specific Mortality in Breast, Prostate, and Colorectal Cancer Survivors
Authors: CHEN XIONG , XIAO JIAN , WANG YAFENG , SHEN FEIXIA
Published: June 2020

Aims: To determine whether diabetes is associated with all-cause, cancer-related and cardiovascular disease (CVD) mortality and examine the effect of duration of diabetes on mortality in breast, prostate and colorectal cancer survivors.

Methods: National Health Interview Survey (NHIS) was used to select 37,993 adults cancer survivors from 1997 to 2013 linked data retrieved from the National Death Index through December 31, 2015. Cox proportional-hazards models were used to assess associations between diabetes and all-cause and cause-specific mortality.

Results: Over a median follow-up period of 13 years, 2,346 all-cause, 698 cancer and 506 CVD deaths occurred. Among all cancer survivors, patients with diabetes had hazard ratios (HR) of 1.36 (95% CI=1.28-1.44) for all-cause mortality, 1.14 for cancer-specific mortality (95% CI=1.03-1.27), 1.36 for CVD mortality (95% CI=1.18-1.55), 17.18 for diabetes related mortality (95% CI=11.51-25.64) and 2.51 for kidney disease mortality (95% CI=1.65-3.82). For specific cancer sites, the HRs for all-cause mortality among survivors with diabetes diagnosed with breast cancer, prostate cancer and colorectal cancer. Diabetes increased the risk of cancer-specific mortality among colorectal cancer survivors compared to nondiabetic survivors. However, there is no the increasing risk in breast or prostate cancer survivors with diabetes. Diabetes was associated with higher risk of diabetes related mortality when compared to nondiabetic breast, prostate and colorectal cancer survivors. Cancer survivors with diabetes had similar risk of all-cause and CVD mortality during the second 5 years of diabetes and above 10 years of diabetes as compared to nondiabetic patients.

Conclusions: Diabetes increased the risk of all-cause mortality among breast, prostate, and colorectal cancer survivors. Greater attention on diabetes management is warranted in cancer survivors with diabetes.

Disclosure

X. Chen: None. J. Xiao: None. Y. Wang: None. F. Shen: None.

Funding

Natural Science Foundation of Zhejiang Province (LWY20H020001); China Scholarship Council (201908330235); Science and Technology Project of Wenzhou Science and Technology Bureau (Y20190125); First Affiliated Hospital of Wenzhou Medical University (FHY2019015)
1614-P: Targeting People with Unknown Diabetes in Health Insurance Databases through Artificial Intelligence
Authors: FUENTES SONSOLES , HRZIC ROK , KAB SOFIANE , HANEEF ROMANA , FOSSE-EDORH SANDRINE , COSSON EMMANUEL
Published: June 2020

Background: The studies on unknown diabetes are usually based on small samples of population. Information from the entire population can be accessible through health insurance databases like the French National Health Data System (SNDS) comprising data on reimbursement of out-of-hospital dispensed health care and from public and private hospitals from the 66 million people living in France. The objective of our study was to develop an algorithm to identify unknown diabetes cases in the SNDS using artificial intelligence (AI).

Methods: Data from the Constances cohort were used to develop the algorithm since individual information recorded in self-administered questionnaire, medical examination and biological tests is linked with data from the SNDS. We applied a supervised machine learning method, involving eight steps. First, the reference database was selected (n=44,185 participants), after excluding known diabetes cases. Then, the unknown diabetes cases - fasting blood glucose ≥7 mmol/L- were identified as target positive (n = 655). The following steps were: codification of the SNDS variables, split the referenced database into training and testing databases, selection of variables and training, validation and selection of algorithms.

Results: Among the 3471 variables coded, 12 variables were selected based on their ability to discriminate the target: unknown diabetes cases versus no diabetes. The final algorithm is a logistic regression model based on the 5 most discriminating variables: age, sex and number of out-of-hospital reimbursements in the previous year for blood lipid profile tests, general practitioner consultations and blood glucose tests. The specificity, sensitivity and precision of the algorithm were 70%, 71% and 69%, respectively.

Conclusion: AI opens many perspectives in terms of diabetes prevention. Thus, unknown diabetes cases could be ascertained for development and evaluation of prevention policies at a national, regional or local level.

Disclosure

S. Fuentes: None. R. Hrzic: None. S. Kab: Employee; Spouse/Partner; Sanofi. R. Haneef: None. S. Fosse-Edorh: None. E. Cosson: None.
1622-P: Glycemic Outcomes among Rural Patients in the Type 1 Diabetes Exchange Registry, January 2016 to March 2018
Authors: GILL ARASHPREET K. , GOTHARD MICHAEL D. , EARLY KATHALEEN BRIGGS
Published: June 2020

Rural Americans with type 1 diabetes face health disparities that can contribute to diabetes-related complications. This study sought to examine glycemic outcomes among rural participants in the Type 1 Diabetes (T1D) Exchange clinic registry between January 1, 2016 and March 31, 2018. Data were identified by rural status as defined by the Centers for Medicaid and Medicare, and stratified by age range, and eventually multivariate regression modeling was performed to isolate glycemic differences based on hemoglobin A1c (HbA1c) levels. A full multivariate regression model including all significant (p<0.05 via two-sided testing) differential factors was determined with an additional indicator for rural status. Finally, the multivariate model was reduced using backwards elimination stepwise procedures until only significant (p<0.05 via two-sided testing) factors were included. Mean HbA1c levels for all rural participants (n=1837) were significantly higher (mean 8.71% [SD 1.66%]) compared to the non-rural group (mean 8.48% [SD 1.63%]), p<0.001. Rural children under age 13 (n=224) had a significantly higher average HbA1c (8.65% [1.17%]) compared to the non-rural group (8.45% [1.19%]), p=0.022. Rural adolescents between ages 13-18 (n=609) had a significantly higher average HbA1c (9.39% [1.73%]) than the non-rural group (9.14% [1.69%]), p<0.001. Rural young adults between ages 18-26 had a higher average HbA1c (9.07% [1.77%]) than the non-rural group (8.88% [1.78%]), p=0.042. The average HbA1c among rural adults (n=589) over age 26 was not significantly different (7.72% [1.21%] than those of non-rural adults (7.76% [1.15%]), p=0.503. There is a clear pattern in glycemic outcome disparities even after adjustment for characteristic differences between rural and non-rural participants in the T1D Exchange, most strikingly among youth. The full extent of this disparity and the contributing factors need to be more thoroughly studied to provide effective solutions.

Disclosure

A.K. Gill: None. M.D. Gothard: None. K. Briggs Early: None.