bluuebunny/crossref_metadata_2025 huggingface dataset:
1233-P: The Association between Subgingival Microbiome, Subclinical Cardiovascular Disease, and Type 1 Diabetes
Authors: XIAO MIANLI , SARKAR ANUJIT , SNELL-BERGEON JANET K. , CHANDRASEKARAN SANGEETHA , JOHNSON LONNIE R. , BURKHARDT BRANT R. , PETROSINO JOSEPH , ALMAN AMY C.
Published: June 2023

Background: Dysbiosis in the subgingival microbiome is the root cause of periodontal disease, a risk factor of cardiovascular disease (CVD), but its association with subclinical CVD, particularly among those with type 1 diabetes (T1D) is unclear.

Methods: We included 283 subjects with (n=141) and without (n=142) T1D. We performed 16S rDNA sequencing on subgingival plaque samples and identified amplicon sequence variants. Subclinical CVD was measured by carotid intima-media thickness (cIMT), pulse wave velocity (PWV), and brachial artery distensibility (BrachD).

Results: Beta diversity differed between T1D and the nondiabetes (ND) group (F = 1.66, P=0.024). As shown in Figure 1, in the stratified generalized linear model (adjusted for age, gender, race, smoking, alcohol drinking, BMI, and additionally HbA1c in the T1D model), we observed 4 taxa in the T1D group and 28 taxa in the ND group to be associated with cIMT (all Padj< 0.05). Moreover, 8 and 17 taxa were associated with BrachD (lower value suggests worse status) in T1D and ND groups, and 6 and 5 for PWV (all Padj < 0.05). Some associations were in opposite directions by diabetes status, especially for cIMT.

Conclusion: We observed differences in the subgingival microbiome profile between those with and without T1D. Subgingival microbiome taxa were associated with subclinical CVD measures, with some differences observed by diabetes status.

Disclosure

M. Xiao: None. A. Sarkar: None. J.K. Snell-Bergeon: None. S. Chandrasekaran: None. L.R. Johnson: None. B.R. Burkhardt: None. J. Petrosino: None. A.C. Alman: None.

Funding

National Institutes of Health (5R01DE026480)
1243-P: Usefulness of New Criteria for Metabolic Syndrome Optimized for Prediction of Cardiovascular Diseases in Japanese
Authors: MITSUMA YURIE , FUJIHARA KAZUYA , MURAI KOSHIRO , SATO TAKAAKI , YAGUCHI YUTA , YAMADA MAYUKO H. , YAMAMOTO MASAHIKO , OSAWA TAEKO , KITAZAWA MASARU , MATSUBAYASHI YASUHIRO , IWANAGA MIDORI , YAMADA TAKAHO , KATO KIMINORI , SONE HIROHITO
Published: June 2023

The use of multiple diagnostic criteria for metabolic syndrome (MetS) may miss high-risk populations for cardiovascular disease. Moreover, since women are more likely to have subcutaneous fat deposits than men, the predictive ability of cardiovascular disease may be improved by optimizing the cut-off value of each component of criteria according to sex and considering whether to include waist circumference (WC) as a required component. In a nationwide cohort of 565,079 men and women from 2008 to 2016 in Japan, we analyzed the association between MetS and each component and the development of CAD, CVD, or CAD/CVD using multivariate Cox regression. Of these 3,934 men (1.19%) and 893 women (0.38%) developed CAD/CVD, with a 1.3- to 2.9-fold increased risk of CAD/CVD when current MetS components were met. The optimal thresholds for predicting CAD/CVD by ROC analysis in men and women were WC 83 and 77 cm, triglycerides 130 and 90 mg/dl, HDL-C 50 and 65 mg/dl, BP 130/80 and 120/80 mmHg, and FPG of 100 and 90 mg/dl, respectively. Although no significant difference was detected between the current MetS criteria and our modified criteria in the ability to predict CAD/CVD, using the new criteria increased prevalence of MetS and significantly improved sensitivity (Table). Optimizing MetS criteria could significantly reduce the number of high-risk individuals overlooked by the current criteria.

Disclosure

Y.Mitsuma: None. Y.Matsubayashi: None. M.Iwanaga: None. T.Yamada: None. K.Kato: None. H.Sone: Research Support; Novo Nordisk, Astellas Pharma Inc., Kyowa Kirin Co., Ltd., Taisho Pharmaceutical Holdings Co., Ltd., Ono Pharmaceutical Co., Ltd., Eisai Co., Ltd., Takeda Pharmaceutical Co., Ltd. K.Fujihara: None. K.Murai: None. T.Sato: None. Y.Yaguchi: None. M.H.Yamada: None. M.Yamamoto: None. T.Osawa: None. M.Kitazawa: None.
1254-P: Assessing Prediabetes and Diabetes Screening Eligibility and Detection in Adults by ADA and USPSTF Guidelines in the NIH’s All of Us Research Program
Authors: ZENG CHENJIE , CASSINI THOMAS , FERRARA TRACEY M. , SCHLUETER DAVID , TRAN TAM C. , DENNY JOSH
Published: June 2023

ADA and USPSTF recommended diabetes screening starting at age 35 recently. We estimated the percentage of adults with undiagnosed prediabetes or diabetes who can be detected by USPSTF and ADA guidelines in all and by racial/ethnicity groups in the All of Us cohort. We then identified predictors of incident T2D. Among 50,705 eligible participants, we identified 20,150 with undiagnosed prediabetes and 1,860 with undiagnosed diabetes at enrollment, >99% of whom met the ADA 2022 screening criteria, which outperformed USPTSF ones (57.4% and 67.4%). All results were similar to findings from a recent NHANES study. Substantial racial disparities were identified in stratified analyses. The percentage of undiagnosed prediabetes was 37.7%, 50.8% and 38.2% in White, Black and Hispanic populations, respectively and it was 2.6%, 7.8% and 3.8%, respectively, for undiagnosed diabetes (all p<2e-16). However, the ADA 2022 guideline can detect almost all (>98.8%) the undiagnosed, particularly in the understudied populations. During the 4 year follow up, 23% of the undiagnosed diabetes were subsequently diagnosed, with race, income, education, and insurance being the strongest predictors. In summary, the new ADA guideline can effectively facilitate early detection of diabetes across all populations, but barriers still exist to effectively screen and diagnose equitably.

Disclosure

C.Zeng: None. T.Cassini: None. T.M.Ferrara: None. D.Schlueter: None. T.C.Tran: None. J.Denny: None.

Funding

National Institutes of Health (HG200417)
1257-P: Changes in Circulating Pancreatic Islet-Specific MicroRNA-375 Levels and Improvements in Insulin Sensitivity and Glucose Metabolism in Response to Weight-Loss Diets with Different Compositions of Macronutrients—The POUNDS Lost Trial
Authors: HEIANZA YORIKO , XUE QIAOCHU , MA HAO , BRAY GEORGE , SACKS FRANK , QI LU
Published: June 2023

Pancreatic islet-specific microRNA-375 (miR-375) regulates insulin secretion and has an essential role in β-cell compensation when escalating insulin demand. We recently reported that changes in circulating miR-375 were associated with improved diabetogenic fat depots. Here, we investigated whether changes in circulating miR-375 induced by weight-loss diet interventions with different macronutrient intakes (fat, carbohydrate (carb), and protein) were related to improved insulin sensitivity and glucose metabolism. This study included participants from the POUNDS Lost trial with available data on circulating miR-375-3p at baseline (n=520) and its changes from baseline to 6 months after weight-loss diet interventions (n=508). At baseline, higher levels of miR-375 were related to lower degrees of BMI, total adipose tissue mass, and whole-body fat content (P <0.05 for all). There was a significant increase in miR-375 levels from baseline to 6 months (P by paired t-test <0.001). We found that associations of changes in miR-375 with changes in fasting insulin, glucose, and insulin resistance (HOMA-IR) were significantly modified by carb and fat intakes (P interaction <0.05 for all). In response to a low-fat and high-carb diet, a greater increase in miR-375 was significantly associated with larger reductions of fasting insulin and HOMA-IR at 6 months, regardless of baseline miR-375 levels. On the other hand, in response to a high-fat and low-carb diet intervention, there were significant positive associations between miR-375 changes and changes in glucose, insulin, and HOMA-IR. These results suggest that changes in the pancreatic islet-specific miRNA expression are associated with weight-loss diet intervention outcomes on insulin sensitivity and glucose metabolism. Different macronutrient intakes may modify these associations.

Disclosure

Y.Heianza: None. Q.Xue: None. H.Ma: None. G.Bray: Advisory Panel; Medifast, Inc., Herbalife International of America, Inc. F.Sacks: None. L.Qi: None.

Funding

National Institutes of Health (DK091718, DK100383, DK115679)
1258-P: Gestational Diabetes by IADPSG Criteria and Risk of Adverse Birth Outcomes
Authors: CARTER SARAH A. , LIN JANE C. , CHOW TING , MARTINEZ MAYRA P. , KLARA FELDMAN R. , PAGE KATHLEEN A. , XIANG ANNY
Published: June 2023

This study assessed risk of adverse birth outcomes (ABO) associated with GDM by Carpenter-Coustan (C&C) and International Association of the Diabetes and Pregnancy Study Groups (IADPSG) with and without abnormal fasting at OGTT screening. Data included 355,506 singletons born in a single healthcare system. Data on demographics, maternal GDM status with or without abnormal fasting, and six ABOs [caesarean section (CS), shoulder dystocia (SD), fetal distress (FD), neonatal hypoglycemia (NH), preterm birth (PTB), and large-for gestational age (LGA)] were extracted from electronic medical records. Logistic regression was used to assess associations adjusting for covariates. In this cohort, 27,990 (7.9%) were diagnosed by C&C and 21,464 (6.0%) by IADPSG. In the C&C group, 37.3% had abnormal fasting (C&C_AF); among IADPSG, 23.3% met OGTT fasting thresholds (IADPSG_AF). Table 1 shows odds ratios (OR) of ABOs associated with GDM diagnostic types relative to no GDM. GDM by C&C or IADPSG with or without abnormal fasting was associated with higher odds of CS, PTB (except IADPSG_AF), and LGA (except C&C without abnormal fasting). IADPSG without abnormal fasting was associated with higher odds of SD and NH, and C&C_AF was associated with higher odds of SD but lower odds FD and NH. These data suggest GDM by IADPSG was associated with risk of some ABOs; this group may benefit from diabetes care in pregnancy to reduce risk of ABOs.

Disclosure

S.A.Carter: None. J.C.Lin: None. T.Chow: None. M.P.Martinez: None. R.Feldman: None. K.A.Page: None. A.Xiang: None.
1263-P: Gender Differences in the Impact of Low Muscle Mass on Type 2 Diabetes Incidence—Eighteen-Year Follow-up Data from the Prospective Korean Genome and Epidemiology Study
Authors: SOOK KIM EUN , CHO YUNJUNG , HONG OAK-KEE , MOON SUNGDAE , HAN JEHO , JIB YOO SOON , CHO NAM H.
Published: June 2023

Background: Current evidence suggests that diminished muscle mass is associated with an increased risk of diabetes. This study aimed to investigate whether the effect of low muscle mass (LMM) on incident diabetes varied depending on the tracking period using a prospective, longitudinal design.

Methods: We recruited 6968 subjects without diabetes, aged 40 to 69 years, from the Korean Genomes and Epidemiology study and followed them to monitor the development of type 2 diabetes mellitus (T2DM). A standard 75-g oral glucose tolerance test was conducted at every 2-year follow-up visit. Skeletal muscle mass was assessed using bioelectrical impedance analysis, and a weight-adjusted skeletal muscle mass was defined as muscle mass index (MMI). We assessed the relationship between LMM, the sex-specific lowest tertile of MMI, and the risk of developing T2DM using Cox regression models.

Results: Of 6968 (47.4% men), 1846 progressed diabetes during the 18-year follow-up. LMM was associated with an increased risk of T2DM at 10 years and 10-18 years of follow-up in both genders after adjustment for confoundings. After additional adjustment for waist circumference, men with LMM were at significant risk of incident diabetes during the 10-year follow-up (hazard ratio [HR] 1.54, 95% confidence interval [CI] 1.28-1.86) but lost significance in 10-18 years., whereas women with LMM were at significantly increased risk (HR 1.32, 95% CI 1.03-1.69) only in 10-18 years. Over 18 years, LMM in men was consistently associated with an increased risk of diabetes from the initial period (at 2-year follow-up), whereas LMM in women has been shown to increase risk in the late period (from 12-year follow-up).

Conclusion: This study showed that LMM is an independent risk factor for T2DM with gender differences over time. LMM was a constant risk factor for diabetes in men, whereas it affected the later onset of diabetes in women.

Disclosure

E.Kim: None. Y.Cho: None. O.Hong: None. S.Moon: None. J.Han: None. S.Yoo: None. N.H.Cho: None.
1264-P: Trends in Incidence and Prevalence of CFRD from the U.S. Cystic Fibrosis Foundation Patient Registry (CFFPR)
Authors: KOHLER CELIA L. , VIGERS TIMOTHY B. , SAKAMOTO CASEY , MORAN ANTOINETTE , SAGEL SCOTT , CHAN CHRISTINE L.
Published: June 2023

Intro: The US CFFPR includes data from ~30,000 individuals with cystic fibrosis (CF). We aimed to examine trends in incidence and prevalence alongside screening rates of cystic fibrosis related diabetes (CFRD) from 2003-2018.

Methods: Prevalence of CFRD was defined as the percent of patients with CFRD in the registry in a given year. Annual incidence of CFRD was calculated as the number of new diagnoses per 1,000 person-years. Annual screening rates were defined as the percent of individuals without CFRD who underwent an oral glucose tolerance test (OGTT). Individuals <10 years were excluded, and data were grouped by age decade.

Results: (Table 1) CFRD screening rates increased from 2003-2018, particularly in 10-18 yr olds. Although screening rates increased in adults as well, overall rates remain low. In 10-18 yr olds, the incidence of CFRD did not increase, and incident cases in adults decreased. The prevalence of CFRD is gradually increasing in adults.

Conclusions: Despite increased screening, the incidence of CFRD is stable or declining. CFRD prevalence is steadily rising in older adults. Screening rates and trends in CFRD incidence support a need for revised and potentially targeted screening algorithms. With increasing longevity in people with CF and rising prevalence of CFRD, there is great need for more specialists trained to care for a growing population of adults with CFRD.

Disclosure

C.L.Kohler: None. T.B.Vigers: None. C.Sakamoto: None. A.Moran: Advisory Panel; Abata Therapeutics, Dompé, Other Relationship; Novo Nordisk, Research Support; Abbott Diabetes. S.Sagel: None. C.L.Chan: None.
1268-P: One-Hour Glucose Thresholds for T2D Prediction—A Longitudinal Validation Study in the Korean Genome and Epidemiology Study (KoGES)
Authors: IM MYUNGSOO , RYANG SOREE , KIM DOOHWA , YI WOOK , KIM JINMI , KANG HYUK , JIN KIM YOUNG , JIN KIM YEONG , KIM MINSOO , JOO KIM IN , CHUNG STEPHANIE T. , SHERMAN ARTHUR , HA JOON , SOO KIM SANG
Published: June 2023

One-hour glucose to predict prediabetes (PreDM=155mg/dL) and type 2 diabetes (T2D= 209 mg/dl) could improve detection with a shorter 1-hour OGTT, but thresholds need validation in longitudinal cohorts. We determined the risk of incident diabetes using the proposed thresholds with a 16-year longitudinal Korean data set (N=6381, BMI=24±4.0 kg/m2; Age 51.2±8.6 y). OGTT was conducted every 2 y, and 3 groups were assigned at baseline: low one-hour plasma glucose (1h-PG) with normal glucose tolerance (NGT) (low 1h-PG: FPG<100, 2h-PG<140, 1h-PG<155), high 1h-PG with NGT (high 1h-PG: FPG<100, 2h-PG<140, 1h-PG≥155), and PreDM (100≤FPG<126 or 140≤2h-PG<200). Time to T2D was compared by the group in a subset (N=230). T2D risk was higher in high 1h-PG and PreDM than low 1h-PG group (HR:4.9 [3.5, 6.8] and 8.8 [6.5, 11.8]). With the subset of progressors, a linear mixed effect model showed that times to T2D from low and high 1h-PG were 24.8±18.5 y and 19.5±12.4 y (P<0.05). The 1h-PG threshold for T2D, 209 mg/dl, was reached 7.5±14.5 y earlier than the 2h-PG threshold, 200 mg/dl. Conclusion: NGT with high 1h-PG is an intermediate state between low 1h-PG NGT and PreDM, and the 1h-PG threshold for T2D allows earlier diagnosis than the current 2h-PG threshold.

Disclosure

M.Im: None. I.Kim: None. S.T.Chung: None. A.Sherman: None. J.Ha: None. S.Kim: None. S.Ryang: None. D.Kim: None. W.Yi: None. J.Kim: None. H.Kang: None. Y.Kim: None. Y.Kim: None. M.Kim: None.

Funding

Busan Economic Promotion Agency; National Research Foundation of Korea (2022H1D3A2A01063552); Korea Health Industry Development Institute (HI18C2383); dkNET New Investigator Pilot Program in Bioinformatics; National Institute of Diabetes and Digestive and Kidney Diseases
1269-P: Trajectories of MicroRNAs Are Associated with Trajectories of Weight but Not Fasting Blood Glucose in the Diabetes Prevention Program Trial
Authors: LEWIS KIMBERLY A. , FLOREZ JOSE C. , AOUIZERAT BRADLEY , KANAYA ALKA M. , FLOWERS ELENA
Published: June 2023

Introduction: Circulating microRNAs (miRs) are emerging as promising biomarkers of risk for type 2 diabetes (T2D) and responses to risk-reduction interventions, but no prior study has examined longitudinal associations between miRs and fasting blood glucose (FBG) or weight in adults at high risk for T2D. Prior studies have been cross-sectional or only measured longitudinal outcomes. We determined the association between longitudinal trajectories of miRs, FBG, and weight in a subset of participants from the Diabetes Prevention Program (DPP).

Methods: This study was a secondary analysis of a subset of participants (N=150) from DPP. A custom Fireplex assay was used to quantify 58 miRs from banked plasma samples collected at baseline, 1-year, and 2-years. Generalized linear mixed models were used to analyze associations between the miRs, FBG (mg/dL), and weight (kg) over time, adjusting for covariates (i.e., age, body mass index, race or ethnicity, gender, trial arm, and high density lipoprotein cholesterol). The Benjamini-Hochberg false discovery rate method was used to adjust for multiple comparisons.

Results: The sample was 73% female, 19% Black, 14% Hispanic, and mean age was 51 ± 11 years. At baseline, the participants were normotensive, obese, and had dyslipidemia and prediabetes. After adjusting for multiple comparisons, 39 miRs were significantly associated with weight, of which 12 miRs (let-7c-5p, miR-1066-5p, miR-1287-5p, miR-133b, miR-15a-5p, miR-15b-5p, miR-181c-3p, miR-197-5p, miR-23b-5p, miR-296-5p, miR-877-5p, miR-98-5p) remained significant after adjusting for covariates. In the FBG model, none of the miRs were significant.

Conclusions: Twelve miRs were associated with longitudinal weight but no miRs were associated with FBG trajectories in a subset of participants from the DPP trial. These miRs may provide mechanistic, diagnostic, or therapeutic insights about T2D prevention.

Disclosure

K.A.Lewis: None. J.C.Florez: Consultant; AstraZeneca, Novo Nordisk, Other Relationship; AstraZeneca, Merck & Co., Inc. B.Aouizerat: None. A.M.Kanaya: None. E.Flowers: None.

Funding

National Institute of Diabetes and Digestive and Kidney Diseases (R01DK124228, X01DK115999)
127-OR: The Effect of Tirzepatide during Weight Loss on Metabolic Adaption, Fat Oxidation, and Food Intake in People with Obesity
Authors: RAVUSSIN ERIC , SANCHEZ-DELGADO GUILLERMO , MARTIN CORBY K. , NISHIYAMA HIROSHI , LI JING , URVA SHWETA , PRATT EDWARD J. , COSKUN TAMER , MILICEVIC ZVONKO , HAUPT AXEL
Published: June 2023

We hypothesized that tirzepatide (TZP) causes body weight loss by reducing food intake and, according to pre-clinical studies, decreasing metabolic adaptation during weight loss. In a randomized blinded clinical trial in people with obesity (PWO) undergoing caloric restriction, we investigated the effect of TZP vs Placebo (PBO) on energy metabolism after targeting a 10% (±2%) weight loss. In this 18wk phase 1 study, 55 PWO, were randomized (1:1) to TZP 15 mg or PBO (mean baseline body weight 102.5 vs 103.1 kg, respectively). The primary objective was to investigate the change from baseline in sleeping metabolic rate (SMR) measured by whole-room indirect calorimetry. Secondary measures were changes in 24-hr sedentary energy expenditure, 24-hr respiratory quotient (RQ), sleeping RQ, substrate utilization, body composition (BC) and food intake. TZP caused greater weight loss than PBO (-16.7 kg vs -8.3 kg; p<0.001). The decreases in SMR and 24-hr energy expenditure were not different between groups after adjusting for changes in body weight and BC. However, TZP significantly reduced 24-hr RQ and sleeping RQ compared to PBO; thus, significantly increasing fat oxidation while decreasing carbohydrate and protein oxidation rates. TZP also significantly reduced food intake. Overall, TZP did not affect metabolic adaptation but significantly increased fat oxidation.

Disclosure

E.Ravussin: Advisory Panel; Novartis, Research Support; Eli Lilly and Company, Novartis AG. A.Haupt: Employee; Lilly, Stock/Shareholder; Lilly. G.Sanchez-delgado: Research Support; Eli Lilly and Company, Novo Nordisk, Abbott, Maastricht instruments, Vyaire Medical, ParvoMedics, Cosmed, Speaker's Bureau; Eli Lilly and Company. C.K.Martin: Board Member; EHE Health, Wondr Health, Other Relationship; ABGIL, Research Support; Pack Health, Evidation Health, Lilly, WW International, Inc. H.Nishiyama: None. J.Li: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. S.Urva: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. E.J.Pratt: Employee; Eli Lilly and Company. T.Coskun: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. Z.Milicevic: Employee; Eli Lilly and Company.

Funding

Eli Lilly and Company
1272-P: Fatty Liver Change and Type 2 Diabetes in Older Adults with Prediabetes
Authors: HWAN PARK JUNG , CHUL WON JONG
Published: June 2023

Background: No data are available on the association between changes in fatty liver disease (FLD) and the risk of type 2 diabetes in elderly individuals with prediabetes.

Methods: A total of 156,984 elderly subjects with prediabetes who underwent national health screening in 2009 and 2011 were followed up. FLD was defined as a change in the fatty liver index (FLI) with a cut-off of 60 for steatosis and 30 as a reference. Multivariable Cox proportional hazards regression was used to calculate the hazard ratio (HR) and confidence intervals (CIs) for type 2 diabetes according to the changed status of the FLD.

Results: During a median of 8.35 years of follow-up, 29,422 (18.7%) elderly individuals with prediabetes developed type 2 diabetes. Multivariable adjusted HRs of type 2 diabetes according to FLI change were 2.22 (95% CI 2.11-2.34) in individuals with both FLI ≥ 60 compared to those with both FLI < 30. Although weight loss ≥5% was associated with a 7% lower risk of type 2 diabetes (95% CI 0.90-0.96), those with resolved FLD, new FLD, and persistent FLD along with weight loss at the same time period had an increased risk of type 2 diabetes by 30%, 36%, and 53%, respectively. The risk of type 2 diabetes did not increase in individuals with FLD-free status, regardless of weight change.

Conclusions: The presence and change of FLD is an important factor for the development of type 2 diabetes in elderly individuals with prediabetes.

Disclosure

J.Park: None. J.Won: None.
1274-P: High Prevalence of Type 2 Diabetes without Traditional Risk Factors among Men Who Inject Drugs in Chennai, India
Authors: CHEBROLU PUJA , MCFALL ALLISON , BROWN TODD , SRIKRISHNAN AK , SURESH KUMAR M. , SYED IQBAL H. , MATHAD JYOTI S. , LUCAS GREGORY , SOLOMON SUNIL S. , MEHTA SHRUTI
Published: June 2023

South Asians with type 2 diabetes (T2DM) are predominately normal- or underweight, due to early loss of beta cell function in addition to insulin resistance. Substances of misuse are an additional stressor on beta cells and may lead to an increased prevalence of T2DM. We determined the prevalence of T2DM and its correlates among people who inject drugs (PWID) in Chennai. We conducted a cross-sectional analysis among male PWID. T2DM was defined as fasting glucose ≥126mg/dL or a prior diagnosis. Logistic regression was used to identify correlates of T2DM. Among 1039 PWID, median age was 38.9 years (IQR 32.1, 44.9) and median BMI was 19.7 kg/m2 (IQR 17.8, 22.9). The most common injected substance was heroin (94.8%, n=998). T2DM prevalence was 8.4% (n=87), among whom 60% were underweight or normal weight and 64% had normal waist circumference. On univariable regression analysis, T2DM was not associated with greater frequency of drug use, type of drug, HIV, or Hepatitis C. On multivariable analysis, age >40 years (OR 3.0, 95% CI 1.3-6.8) and high waist circumference (OR 1.9, 95% CI 1.1-3.2) were associated with T2DM. The prevalence of T2DM among PWID is similar to India as a whole, though most cases would not be detected by screening using weight or waist circumference. Integrating universal metabolic disease screening into substance abuse treatment programs may help reduce morbidity and mortality from T2DM.

Disclosure

P.Chebrolu: None. S.Mehta: Research Support; Abbott Diagnostics. A.Mcfall: None. T.Brown: Advisory Panel; Merck & Co., Inc., Gilead Sciences, Inc., ViiV Healthcare, Jannsen. A.Srikrishnan: None. M.Kumar: None. H.Iqbal: None. J.S.Mathad: None. G.Lucas: None. S.S.Solomon: Research Support; Gilead Sciences, Inc., Abbott.

Funding

National Institute on Drug Abuse (R01DA026727); Fogarty International Center (D43TW009337); Weill Cornell Department of Medicine; National Institute of Allergy and Infectious Diseases (K24AI120834 to T.B.)
1276-P: Level of Injury Affects Body Mass Changes but Has No Influence on Alteration in Glycaemic Index in Persons with Spinal Cord Injury—A Prospective Cohort Study
Authors: HOEKSTRA SVEN , MADER MICHAEL J. , TRBOVICH MICHELLE , SALEHI MARZIEH
Published: June 2023

In able-bodied individuals, an increase in body mass index (BMI) enhances the risk of glucose tolerance deterioration and diabetes mellitus (DM). This relationship can be altered after spinal cord injury (SCI) due to muscle atrophy and the potential effects of autonomic dysfunction on glucose metabolism, which are more exaggerated in those with tetraplegia (TP) compared to paraplegia (PP). Here, we investigated the relationship between longitudinal changes in BMI and glycated haemoglobin (HbA1c), as well as the effect of level of injury (LOI) on this relationship, among nondiabetic patients with SCI. In a retrospective cohort of veterans with SCI, electronic data of BMI, LOI, glucose concentration and HbA1c were obtained from Jan 2001 to Dec 2021. A total of 728 patients without DM at baseline were identified (LOI: 350 TP/378 PP, age: 52±15 years, sex: 690 male/38 female), and followed up for a mean of 94 months (TP) and 114 months (PP). At baseline, using the SCI-specific BMI classification (normal weight BMI<22 kg/m2, obesity BMI> 25 kg/m2), 48% of TP and 65% of PP were obese at baseline (BMI TP: 25.6±5.9 kg/m2; PP: 28.0±6.6 kg/m2,; p<0.001). HbA1c at baseline was similar between TP and PP (5.21±0.59% vs 5.27±0.70%, p = 0.175). At the end of follow-up, BMI was increased to a larger extent in PP compared with TP (-0.02±4.11 kg/m2 in TP, +0.55±4.31 kg/m2 in PP; p = 0.05). However, HbA1c changes did not differ between TP versus PP (p = 0.323). The final BMI was associated with baseline BMI (p<0.001) and LOI (p = 0.007), but the last HbA1c value was only associated with baseline HbA1c (p<0.001) and not LOI (p = 0.821) or baseline BMI (p = 0.605). Together, these findings indicate that neither LOI nor BMI appear useful predictors of DM development in persons with SCI.

Disclosure

S. Hoekstra: None. M.J. Mader: None. M. Trbovich: None. M. Salehi: None.
1285-P: Disparities in Screening, Diagnosis, and Treatment of Type 2 Diabetes Mellitus among Persons with HIV
Authors: MILLMAN NINA , KOETHE JOHN , TURNER MEGAN , BOURGI KASSEM , STERLING TIMOTHY , REBEIRO PETER
Published: June 2023

Background: Persons with HIV (PWH) have normal life expectancy on antiretroviral therapy (ART), but a rising burden of type 2 diabetes mellitus (DM) disproportionately affecting women and Black individuals threatens these gains. We therefore assessed whether disparities in DM incidence are reflected in disease screening and treatment by HIV providers.

Methods: PWH on ART with ≥2 clinic visits at a large HIV clinic in the southeast from 2007-2022 contributed data, if they did not have prevalent DM at enrollment: existing ICD-9/10 diagnoses of DM, antidiabetic medication, hemoglobin A1c (A1c) ≥6.5%, or random glucose ≥200 mg/dL. We assessed the association of demographic and clinical factors with DM screening by A1c and, among those with incident DM by A1c or ICD-9/10 diagnosis or random glucose, DM treatment and achievement of goal (i.e., A1c ≤7.0%). For each “care continuum” step, we used modified Poisson regression to estimate adjusted incidence rate ratios (IRRs) of reaching the next step by these factors.

Results: Among 5450 PWH enrolling, 3762 (69%) were screened for DM by A1c, of whom 1001 (27%) had dysglycemia (A1c >5.7%) and 162 (4.3%) were diagnosed with DM. Among 186 PWH with incident DM, 136 (73%) initiated antidiabetic medication and 94 (84%) achieved an A1c ≤7.0%. Older, Black, and overweight or obese PWH were more likely to be screened (IRRs=1.0-1.1, p<0.05 each) and diagnosed with DM (IRRs=1.8-2.8, p<0.05 each), but there was no significant sex difference in the adjusted model. Of those screened and diagnosed with DM, no clinical or demographic factors were associated with DM treatment initiation or achieving A1c goal.

Conclusions: Older, Black, and overweight/obese PWH were more likely to be screened for and diagnosed with DM. However, we found no disparities in initiating DM medications or achieving an A1c goal. While DM screening among PWH warrants improvement, women and Black PWH, two groups with a higher risk of DM, did not appear to be treated disparately in this population.

Disclosure

N.Millman: None. J.Koethe: Advisory Panel; Merck Sharp & Dohme Corp., Janssen Pharmaceuticals, Inc., Gilead Sciences, Inc., Theratechnologies, Research Support; Merck Sharp & Dohme Corp. M.Turner: None. K.Bourgi: Advisory Panel; Gilead Sciences, Inc., Theratechnologies, Research Support; Gilead Sciences, Inc. T.Sterling: None. P.Rebeiro: Consultant; Gilead Sciences, Inc., Janssen Pharmaceuticals, Inc., Research Support; National Institutes of Health.

Funding

National Institutes of Health (P30AI110527)
1288-P: Predictive Modeling of Type 2 Diabetes and Complications Using Machine Learning
Authors: KHATTAB AHMED , CHEN SHANG-FU , SADAEI HOSSEIN J. , TORKAMANI ALI
Published: June 2023

Background: Given the prevalence of T2D worldwide, early detection and prevention of both T2D and its complications are of utmost importance. We propose comprehensive person-centered machine learning (ML) risk prediction models for T2D and complications.

Methods: From the UK biobank (UKBB), we identified a prevalent T2D group at baseline (9,136 cases and 108,615 controls), an incident T2D group over 10 years of follow-up (29,845 cases and 354,818 controls), and an incident diabetic kidney disease (DKD) group (4435 cases and 33083 controls). We included 3 types of risk factors: clinical (biomarkers and diseases with known diabetes risk like CVD), genetic in the form of polygenic risk scores (PRS) for the pathogenesis of T2D and other clinical risks, and lifestyle. For each group, we trained a model using decision-tree-based ensemble ML algorithm. We then used SHAP values to determine feature importance and chose the top 10 predictors to build a final model.

Results: The T2D prevalence model included 74 features and had an AUC of 0.97, and area under the precision-recall curve (PR AUC) of 0.83. The final model with the top features (HbA1c, T2D PRS, primary HTN, LDL, major dietary changes in the last 5 years, age, plasma glucose, waist circumference, and total cholesterol) had an AUC of 0.98, and PR AUC of 0.88. The T2D incidence model included the same 74 features and had an AUC of 0.92, and PR AUC of 0.57. The final model with the top features had an AUC of 0.93, and PR AUC of 0.65. The DKD risk prediction model comprised 85 features, and it had an AUC of 0.81, and PR AUC of 0.37. The final model with the top features (Cystatin C, primary HTN, eGFR, age, HbA1c, T2D PRS, urea, BMI, BMI PRS, NAFLD PRS) had an AUC of 0.80, and PR AUC of 0.39.

Conclusions: This study is an ongoing work; our interim results show the capability of ML to identify relevant risk factors and that comprehensive ML models could help clinicians decide on more precise and individualized T2D screening and treatment approaches to prevent T2D and complications.

Disclosure

A.Khattab: None. S.Chen: None. H.J.Sadaei: None. A.Torkamani: None.
129-LB: A Comparison of CGM Metrics in People with Type 1 Diabetes Treated with Different Insulin Modalities
Authors: NØRGAARD KIRSTEN , RANJAN AJENTHEN G. , LAUGESEN CHRISTIAN , TIDEMAND KATRINE G. , ANDERSEN HENRIK U. , SVENSSON JANNET , SELMER CHRISTIAN , GREEN ALLAN , VISTISEN DORTE , CARSTENSEN BENDIX
Published: June 2023

Background: There is a lack of real-world data comparing CGM data across different insulin treatment modalities. This study examined the association between CGM-measured glycemic metrics and different insulin treatment modalities in a large type 1 diabetes clinic.

Methods: Individuals with type 1 diabetes attending Steno Diabetes Center Copenhagen, Denmark, were eligible for inclusion if they had ≥70% CGM data available within a four-week period within the past year. Participants were divided into four groups based on their insulin treatment: multiple daily injections (MDI +/- alarms), sensor unintegrated insulin pumps (SUP +/- alarms), sensor-augmented insulin pumps (SAP), and automated insulin delivery systems (AID). The latest measured HbA1c and CGM were analyzed.

Results: Of 6,319 attendees, 2,689 met the inclusion criteria: 1405 with MDI, 453 with SUP, 307 with SAP, and 524 with AID. Compared to the MDI - alarms group, a clinically relevant lower mean HbA1c was found in the SAP (0.5%; 95% CI:0.3-0.6) and the AID group (0.7%; 95% CI:0.6-0.9) (adjusted for sex, age and diabetes duration). CGM metrics for the four different treatment groups are presented.

Conclusion: The results suggest that AID was superior to all other insulin delivering systems with CGM. Although results may be affected by bias due to indication, the expansion of AID use to a wider type 1 population should be considered.

Disclosure

K. Nørgaard: Advisory Panel; Medtronic, Novo Nordisk, Research Support; Medtronic, Dexcom, Inc., Novo Nordisk, Zealand Pharma A/S, Speaker's Bureau; Medtronic, Novo Nordisk, Stock/Shareholder; Novo Nordisk. B. Carstensen: Stock/Shareholder; Novo Nordisk. A. G. Ranjan: None. C. Laugesen: Employee; Novo Nordisk A/S, Stock/Shareholder; Novo Nordisk A/S. K. G. Tidemand: None. H. U. Andersen: None. J. Svensson: Other Relationship; Medtronic, Sanofi, Rubin MEdical, Research Support; Novo Nordisk, Medtronic, Stock/Shareholder; Novo Nordisk. C. Selmer: Other Relationship; Boehringer-Ingelheim, Novo Nordisk. A. Green: None. D. Vistisen: Research Support; Bayer Inc., Sanofi, Boehringer-Ingelheim, Stock/Shareholder; Novo Nordisk A/S.
131-LB: Diabetes and Disparities in Continuous Glucose Monitoring in Community Health Care Settings
Authors: WALLIA AMISHA , AGARWAL SHIVANI , OWEN ANDREW L. , LAM EMILY L. , DAVIS KA'DERRICKA , BAILEY STACY , DELACEY SEAN E. , PACK ALLISON , ESPINOZA JUAN , BRIGHT DANA , EGGLESTON ALICE , O'BRIEN MATTHEW J.
Published: June 2023

Federally qualified health centers (FQHCs) serve vulnerable DM patients in primary care in underserved settings. The state of DM (glycemic control, complications) may differ and utilization of technologies (e.g. continuous glucose monitoring [CGM]) may be essential. But the current state of DM and CGM is poorly characterized. Using EHR data from a national FQHC network (2015-2021) we examined baseline demographic characteristics, CGM prescriptions, and their association. We included 47,579 with DM: n=1630 with T1D [3%], n= 45,949 T2D [97%], 38% Hispanic, 34% Black (Table 1). Notably, T1D pts [mean age 43 SD 16], had poor glycemic control (HbA1c 9.4 SD 2.4) with elevated DM complications severity index scores [mean DSCI 2.3 SD 4.7]. Overall CGM prescriptions were extremely low; 9% in T1D and only 1% in T2D. Among T1D, those who were Hispanic [OR 0.39, (CI 0.23, 0.66), p < 0.001] or Black [OR 0.52, (CI 0.33, 0.81), p = 0.003] were less likely to have CGM prescribed than White adults, after adjustment. Among T2D, those who were Hispanic [OR 0.42, CI 0.33, 0.55, p < 0.001] or Black [OR 0.68, CI 0.54, 0.85, p = 0.001] were similarly less likely to have CGM. Non-private insurance was also a significant factor. DM severity (poor control, complications) is notable in FQHCs, yet CGM is exceptionally low. These findings underscore the major translation gap in standard of care for FQHCs and the critical need to understand inequities.

Disclosure

A. Wallia: Research Support; UnitedHealth Group, Novo Nordisk, Eli Lilly and Company. D. Bright: None. A. Eggleston: None. M. J. O'brien: None. S. Agarwal: Advisory Panel; Medtronic, Consultant; Beta Bionics, Inc., Research Support; Abbott Diabetes, Dexcom, Inc. A. L. Owen: None. E. L. Lam: None. K. Davis: None. S. Bailey: Advisory Panel; Gilead Sciences, Inc., Consultant; Lundbeck, Pfizer Inc., Research Support; Eli Lilly and Company, Merck Sharp & Dohme Corp., Gilead Sciences, Inc., Lundbeck, Pfizer Inc. S. E. Delacey: None. A. Pack: Consultant; Gilead Sciences, Inc., Research Support; Merck & Co., Inc., Pfizer Inc., Gordon and Betty Moore Foundation, RRF Foundation for Aging, Lundbeck, Eli Lilly and Company, Gilead Sciences, Inc. J. Espinoza: Consultant; Sanofi, Research Support; NIH - National Institutes of Health, FDA, Speaker's Bureau; Glooko, Inc.

Funding

Centers for Diabetes Translation Research (5P30DK020541, 472P30DK092949-11A); National Pilot and Feasibility Grant for Diabetes Research Centers; Center for Diabetes Translation Research
133-OR: Insulin Dynamics across the Glucose Tolerance Spectrum in Youth with Obesity
Authors: CHO WONHEE , BACHA FIDA , TFAYLI HALA M. , LEE SOJUNG , MICHALISZYN SARA , YOUNG KIM JOON , ARSLANIAN SILVA A.
Published: June 2023

Despite β-cell failure in youth with dysglycemia (DYSG) (IGT + T2D), fasting insulin concentrations are elevated. Here, we examined 1) metabolic clearance rate of insulin (MCRI) in youth with normal glucose tolerance (NGT) and DYSG, 2) racial/ethnic differences in insulin dynamics and 3) physical and metabolic correlates of MCRI. In 95 Black (B) + 111 White (W) youth, age 14.4 ± 2.0 [SD] yrs., BMI 34.7 ± 6.4 kg/m2, MCRI and peripheral insulin sensitivity (PIS) were calculated from the hyperinsulinemic-euglycemic clamp, 1st-phase insulin (1stPhI) from the hyperglycemic clamp, disposition index (DI=PIS x 1stPhI), % body fat by DXA, visceral adipose tissue (VAT) by MRI. In DYSG vs NGT, MCRI was lower (261.6 ± 11.9 vs 334.1 ± 8.5 ml/m2/min, p<0.001) and fasting insulin was higher (46.9 ± 4.4 vs 32.9 ± 1.2 μU/mL, p<0.001). In B vs W youth (Image), MCRI was lower driven by DYSG. Lower PIS, lower MCRI and higher 1stPhI were characteristics of B youth with DYSG vs W with equally impaired DI. In B and W youth, positive correlates of MCRI were PIS and DI and negative correlates were fasting insulin, % body fat and VAT.

In conclusion, higher fasting insulin concentrations in DYSG despite a failing β-cell could be explained by decreased MCRI. Racial/ethnic contrast in insulin dynamics differs by glycemic status and is more pronounced in DYSG manifested by lower PIS and lower MCRI in B vs W youth with no difference in β-cell function relative to insulin sensitivity.

Disclosure

W.Cho: None. F.Bacha: Other Relationship; Takeda Pharmaceutical Co., Ltd., AstraZeneca. H.M.Tfayli: Other Relationship; Novo Nordisk, Research Support; Sanofi, Novartis. S.Lee: None. S.Michaliszyn: None. J.Kim: None. S.A.Arslanian: Advisory Panel; Novo Nordisk, Eli Lilly and Company, Consultant; Société des Produits Nestlé SA,, Other Relationship; Eli Lilly and Company, AstraZeneca, Research Support; Novo Nordisk, Eli Lilly and Company.

Funding

American Diabetes Association (7-08-JF-27 to S.L.); Eunice Kennedy Shriver National Institute of Child Health and Human Development (K24HD01357, R01HD27503); National Center for Advancing Translational Sciences (UL1TR000005); National Center for Research
1342-P: Are Plasma Aminotransferases of Value in Screening Patients with T2DM for NAFLD or Fibrosis?
Authors: ORTIZ ROCHA ANDREA , GODINEZ LEIVA EDDISON , KALAVALAPALLI SRILAXMI , LOMONACO ROMINA , SHETTY SHWETHA S. , MARANGI STEPHEN A. , VALDEZ SAENZ ENRIQUE , SHRESTHA SULAV , GONZALEZ MARIA A. , CHI XIAOFEI , GURKA MATTHEW J. , BARB DIANA , CUSI KENNETH
Published: June 2023

The ADA recommends to screen for NASH and liver fibrosis individuals with type 2 diabetes (T2DM), obesity (OB) and/or elevated alanine aminotransferase (ALT). However, recent studies have questioned the clinical value of measuring ALT and AST for the detection of patients at risk of nonalcoholic fatty liver disease (NAFLD) or advanced liver fibrosis or cirrhosis. The aim of this study was to assess the clinical value of ALT and AST ≥40 IU/L, or their lower cut-offs ≥30 IU/L as recommended by recent AACE guidelines, to screen populations at risk. To this end, we recruited 714 participants (age: 56 ± 11 years, male: 42%; BMI: 30.8 ± 6.5 kg/m2; T2DM: 35%; A1c: 6.0 ± 1.2%) from primary care or endocrinology clinics, unaware of having NAFLD/fibrosis. Screening for NAFLD included laboratory tests and imaging with elastography (steatosis by controlled attenuation parameter [CAP]; fibrosis by liver stiffness measurement [LSM]). Elevated transaminases were more common in patients with vs. without T2DM, with ALT ≥40 IU/L occurring in 13% vs. 8% and AST in 9% vs. 3% of patients (both p<0.05). If using a cutoff of ≥30 IU/L: 25% vs. 18% and 20% vs. 13%; respectively (both p<0.05). Elevated ALT ≥30 IU/L was the highest in patients with T2DM and OB (n=164) vs. controls (without T2DM or OB; n=269; 27% vs 15%; p=0.02). The sensitivity for diagnosing steatosis by ALT or AST was very low, with ALT and AST ≥40 IU/L present in only 16% and 9%, respectively. However, steatosis by imaging (CAP) was often present if ALT or AST were high (81 and 90%, respectively). An ALT ≥40 IU/L was also not useful for diagnosing patients with fibrosis of any stage (LSM ≥7.0), missing the diagnosis in 63% of patients, and this did not improve when examining only those with more advanced fibrosis (≥F3) being elevated in only 40%. Conclusions: Plasma aminotransferases are of limited diagnostic value when screening patients with T2DM for NAFLD or fibrosis. This supports the ADA recent guidelines for using FIB-4 and additional noninvasive testing for screening.

Disclosure

A. Ortiz Rocha: None. E. Godinez Leiva: None. S. Kalavalapalli: None. R. Lomonaco: None. S.S. Shetty: None. S.A. Marangi: None. E. Valdez Saenz: None. S. Shrestha: None. M.A. Gonzalez: None. X. Chi: None. M.J. Gurka: None. D. Barb: None. K. Cusi: Research Support; Echosens, Inventiva. Consultant; Poxel SA. Research Support; LabCorp, Zydus. Consultant; Altimmune, Arrowhead Pharmaceuticals, Inc., AstraZeneca, 89bio, Inc., Bristol-Myers Squibb Company, Lilly, Madrigal Pharmaceuticals, Inc., Merck & Co., Inc., Medscape, Myovant, Novo Nordisk, ProSciento, Quest Diagnostics, Sagimet, Sonic Incytes, Terns.

Funding

National Institutes of Health (R01120331-01A1)
135-LB: A Variable Impact of the Wave 1 and Wave 2 Lockdowns of the COVID-19 Pandemic on Glycemic Control—A Longitudinal Analysis of FGM Adult Users From Poland
Authors: HOHENDORFF JERZY , KAO KALVIN , BRANDNER LAURA , MALECKI MACIEJ
Published: June 2023

WHO declared COVID19 pandemic in March 2020. In Poland, the particularly severe restrictions related to COVID19 pandemic were implemented during Wave 1. All activities were prohibited except necessary everyday ones. From late May to July 2020 restrictions were gradually lifted. In October 2020, due to Wave 2 of COVID19 pandemic some restrictions were reimplemented, however, their impact on everyday life was smaller than during the Wave 1. The aim of the study was to analyze the impact of different phases of COVID19 pandemic on glycemic control in patients with diabetes using FGM. Longitudinal data of 469 adults aged 18-64 were analyzed. Analyzed time periods were every first 45 days of each quarter of the year 2020. Q1 stands for the first pre-pandemic quarter of 2020, Q2 correspondences to the severe lockdown of Wave 1, Q3 to time of most restrictions lifted, and Q4 to less strict lockdown of Wave 2. Mean glycemic indices are shown in Table 1.

In summary, Wave 1 and Wave 2 of COVID19 pandemic had different impact on glycemic control in patients with diabetes. The severe lockdown of the first wave resulted in adults with diabetes in improvement of glycemic indices, particularly TIR. Common findings during both lockdowns were reduction in TBR and lower glycemic variability as compared to the preceding periods.

Disclosure

J. Hohendorff: Speaker's Bureau; Abbott, Novo Nordisk, Ascensia Diabetes Care, Dexcom, Inc., Bayer Inc. K. Kao: Employee; Abbott Diabetes. L. Brandner: Employee; Abbott Diabetes. M. Malecki: Advisory Panel; Abbott Diabetes. Speaker's Bureau; AstraZeneca, AlfaSigma. Advisory Panel; Novo Nordisk, Lilly, Sanofi. Speaker's Bureau; Merck & Co., Inc. Research Support; Medtronic. Advisory Panel; Dexcom, Inc. Speaker's Bureau; BIOTON S. A., Servier Laboratories, KRKA. Advisory Panel; Bayer Inc.
1350-P: Risk Models for the Development of Cardiovascular and Microvascular Events in Adults with Type 2 Diabetes in the FIELD Study
Authors: LEUNG ONG KWOK , O'CONNELL RACHEL L. , JANUSZEWSKI ANDRZEJ S. , DONOGHOE MARK W. , GEBSKI VAL , SULLIVAN DAVID , ANN RYE KERRY , SCOTT RUSSELL S. , BEST JAMES D. , TASKINEN MARJA-RIITTA , SIMES ROBERT J. , JENKINS ALICIA , KEECH ANTHONY C.
Published: June 2023

Background: There are a few prediction models for chronic complications in people with type 2 diabetes (T2D). This study developed such risk models.

Methods: Data from 9795 adults with T2D in the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial were used to develop risk prediction models for total CVD events, cardiovascular mortality, amputations and new microvascular events using 27 candidate traditional risk factors and additional novel biomarkers (incl. vascular and systemic inflammation, oxidative stress; n=26) using exhaustive search methods.

Results: There were 1295 total first CVD events, 267 CVD deaths, 115 amputations and 1530 new microvascular events. A total of 19 and 18 traditional risk factors were selected in the clinical risk models for total CVD events and CVD mortality, with AUC of 0.723 and 0.821 respectively. For individual microvascular complications, the AUC of their models ranged from 0.656 to 0.895. The addition of novel biomarkers to the clinical risk models only resulted in modestly higher AUC (Table below).

Conclusion: New clinical risk models can be implemented as risk prediction tools for chronic complications in adults with T2D, including for sight-threatening retinopathy and amputations. Novel biomarkers may guide future research on disease mechanisms, but had limited predictive value over clinical variables.

Disclosure

K.Ong: None. M.Taskinen: Board Member; Novo Nordisk, Consultant; Eli Lilly and Company, Novartis, Akcea, Research Support; Novo Nordisk. R.J.Simes: None. A.Jenkins: Advisory Panel; Insulet Corporation, Board Member; Insulin for Life, Research Support; Abbott Diabetes, Medtronic, Hemsley Charitable Trust, Juvenile Diabetes Research Foundation (JDRF), National Institutes of Health. A.C.Keech: None. On behalf of the field study investigators: n/a. R.L.O'connell: None. A.S.Januszewski: None. M.W.Donoghoe: None. V.Gebski: None. D.Sullivan: None. K.Rye: None. R.S.Scott: None. J.D.Best: None.

Funding

Laboratories Fournier; National Health and Medical Research Council of Australia (457103, 1024105, 1037786)