bluuebunny/crossref_metadata_2025 huggingface dataset:
1270-P: A Neural Network Model for the Prediction of Comorbid Cardiometabolic Diseases—Proof of Concept Using UK Primary Care Data
Authors: KRENTZ ANDREW , BRUNSCHWIG LUCAS S. , DIBNER YARON , MICHEL HUGO , JAUN ANDRÉ
Published: June 2023

Background and Aims: Cardiometabolic comorbidities frequently develop in individuals with hypertension, type 2 diabetes, or hypercholesterolemia. When present in combination, the risks of vascular disease are additively increased.

Methods: We created an artificial intelligence neural network to forecast the development of additional comorbidities when a single cardiometabolic disorder was present. The neural network was first taught diagnostic criteria to reproduce current clinical guidelines with 95% accuracy and, in a second step, trained on the outcome of anonymized electronic medical records of 48225 adults from South London primary care clinics, where 6127 had hypertension, 3001 had type 2 diabetes, and 5630 were treated for hypercholesterolemia. Among these cohorts, 2142, 1482 and 724 developed a second morbidity within a 3 year follow up period.

Results: Prediction of an initial comorbidity had a sensitivity of 0.94±0.14, 0.85±0.32, 0.83±0.36 and specificity of 0.87±0.24, 0.90±0.19, 0.93±0.14 up to 1, 2 and 3 years prior to the diagnosis respectively. A second comorbidity was then predicted with a sensitivity of 0.63±0.1, 0.63±0.1, 0.52±0.21 for patients with hypertension who developed type 2 diabetes and 0.76±0.09, 0.70±0.08, 0.85±0.13 for patients with type 2 diabetes who developed hypertension.

Interpretation: This proof-of-concept analysis demonstrates the utility of a neural network to predict the development of one or more comorbidities based on data routinely collected in primary care. At the level of individual patients knowledge of the probability of acquiring additional comorbidities could provide opportunities for prevention. Non-pharmacological and specific pharmacological interventions could be directed at avoiding or postponing additional cardiometabolic risk factors.

Disclosure

A.Krentz: None. L.S.Brunschwig: Employee; Metadvice SA. Y.Dibner: Employee; Metadvice. H.Michel: None. A.Jaun: Board Member; Metadvice.
1271-P: Associations of Combined Socioeconomic, Behavioral, and Metabolic Factors with Undiagnosed Diabetes and Prediabetes among Different Racial and Ethnic Groups
Authors: DING QINGLAN , LU YUAN , HERRIN JEPH , ZHANG TIANYI , MARRERO DAVID G.
Published: June 2023

Background: The study aimed to utilize socioeconomic, behavioral, and metabolic factors to classify adults without diagnosed diabetes into distinct cardiometabolic risk clusters. Racial/ethnic differences in the associations between clusters and undiagnosed diabetes and prediabetes were also explored.

Methods: Data were obtained from the National Health and Nutrition Examination Survey (1999-2018). The k-prototypes clustering algorithm was used to identify clusters using 21 factors. Logistic regression was used to assess differences in the associations between clusters and undiagnosed diabetes or prediabetes by race/ethnicity.

Results: Among 38,476 adults without diagnosed diabetes, we identified 3 clusters. Cluster 1 contained the highest proportions of alcohol consumers, had shortest sleep duration and poorest diet quality. Cluster 2 comprised healthy younger adults with lowest income, and lowest rates of healthcare access. Cluster 3 was mostly older males with chronic conditions; they were least physically active, and more likely to have healthcare access. Regardless of race/ethnicity, the adjusted undiagnosed diabetes risk was 14.9 times higher (95% CI 10.9, 20.2) in Cluster 3 and 3.7 times (95% CI 2.8, 4.8) higher in Cluster 1 (vs. Cluster 2). An elevated prediabetes risk was observed for Clusters 3 and 1 among non-Hispanic Whites, non-Hispanic Blacks, and Hispanic. Among other races/ethnicities, there were no significant differences in prediabetes risk between Clusters 3 and 2.

Conclusion: Clustering analysis using a large number of socioeconomic, behavioral, and metabolic factors revealed three distinct groups of adults, with substantially different risks of undiagnosed diabetes and prediabetes. Incorporating socioeconomic and behavioral factors into traditional clinical risk measures may lead to better identification of subgroups at higher risk for undiagnosed diabetes and prediabetes.

Disclosure

Q.Ding: None. Y.Lu: None. J.Herrin: Consultant; Johnson & Johnson Medical Devices Companies. T.Zhang: None. D.G.Marrero: None.

Funding

Clifford B. Kinley Trust
1275-P: Incident Diabetes Before and During the COVID-19 Pandemic among Youth in Kaiser Permanente Southern California
Authors: MEFFORD MATTHEW T. , WEI RONG , LUSTIGOVA EVA , MARTIN JOHN P. , REYNOLDS KRISTI
Published: June 2023

Background: Prior research found increases in type 1 and type 2 diabetes (T1D/T2D) among youth during the COVID-19 pandemic but did not focus on age, sex, or race/ethnicity variation. We examined incidence rates from 2016-2021 in Kaiser Permanente Southern California (KPSC), a large, integrated healthcare delivery system.

Methods: KPSC members <20 years old, with no diabetes prior to their incidence year were followed using electronic health records for diabetes defined using diagnoses, labs, and diabetes medications. We calculated age- and sex-standardized incidence rates per 100,000 person-years (PY) for T1D and T2D between 2016-2021 overall and by age, sex, and race/ethnicity. We used Poisson regression to calculate incidence rate ratios (IRR) comparing 2020-2021 to 2016-2019.

Results: Incidence of T1D increased from 18.5/100,000 PY in 2016-2019 to 22.4/100,000 PY in 2020-2021 with increased IRR among 10-19-year-olds, both sexes, and Hispanic individuals. (Table) Incidence of T2D increased from 14.8/100,000 PY in 2016-2019 to 24.7/100,000 PY in 2020-2021 with increased IRR among 10-19-year-olds, both sexes, and those with non-Hispanic Black, Hispanic, and other/unknown race/ethnicity.

Conclusion: Incidence of both T1D and T2D increased following the start of the pandemic. Future research to understand potential underlying physiologic and behavioral risk factors is warranted.

Disclosure

M.T.Mefford: None. R.Wei: None. E.Lustigova: None. J.P.Martin: None. K.Reynolds: Research Support; Novartis Pharmaceuticals Corporation.
1281-P: Variants of Unknown Significance (VUS) in Maturity-Onset Diabetes of the Young (MODY)—High Rate of Conundrum Resolution via Reanalysis of VUS
Authors: ALARCON GUIDO , REDONDO MARIA J. , TOSUR MUSTAFA
Published: June 2023

In the era of next-generation sequencing, clinicians frequently encounter VUS on genetic tests for MODY. Pathogenicity ascertainment of those variants may have substantial impact on optimal diabetes care. We aimed to determine the usefulness of reanalyzing previous VUS results in MODY. We performed a retrospective chart review to identify subjects with a VUS on a MODY genetic test performed > 3 years before the study and requested reanalysis of their genetic data at Athena Diagnostics. We identified 10 subjects with at least one VUS on MODY genetic testing (mean age at diagnosis: 13.4 ± 3.4 years, 60% female, 60% Hispanic, 20% African American and 20% non-Hispanic White). After reanalysis, 50% were recategorized to a different category: 30% “likely pathogenic” and 20% “benign”. All newly reclassified pathogenic variants were in HNF1A, and benign variants were in HNF1B and PDX1. The median time to reclassification since MODY testing was 8 years (range 4-10 years). The mean random C-peptide at diagnosis was 1.17 ± 0.17, 2.24 ± 0.8 and 2.96 ± 1.4 ng/mL for those with variants reclassified as benign, likely pathogenic and those who remained as VUS, respectively. In sum, periodic reanalysis of the genetic data of cases with a VUS on MODY tests may provide high-yield diagnostic information. Further studies are warranted to identify the optimal time and frequency for such analyses.

Disclosure

G.Alarcon: None. M.J.Redondo: None. M.Tosur: Advisory Panel; Provention Bio, Inc.
1282-P: Interactive Tool to Estimate Probability of Partial Clinical Remission in Adult-Onset Type 1 Diabetes
Authors: GRZELKA-WOZNIAK AGATA , JANUSZEWSKI ANDRZEJ S. , FLOTYNSKA JUSTYNA , JENKINS ALICIA , ZOZULINSKA-ZIOLKIEWICZ DOROTA , URUSKA ALEKSANDRA
Published: June 2023

Introduction: Type 1 diabetes (T1D) diagnosis is often (in adults) followed by a (‘honeymoon’) period of reduced insulin need, also called partial clinical remission (pCR), which is associated with better outcomes. Various definitions of pCR exist.

Aim: To create an online calculator to predict probability of pCR in adult-onset T1D 12-mths post-diagnosis.

Methods: We analysed data from 133 adults at T1D diagnosis (mean±SD age: 27±6, HbA1c: 11.1±2.0%, BMI: 22.5±3.7 kg/m2), 3-mths and 12-mths later. All were enrolled in the prospective observational InLipODiab (NCT02306005) study. We used 4 definitions for pCR 12-mths post-diagnosis: 1) insulin dose-adjusted HbA1c≤9%; 2) insulin dose<0.3U/kg/24h and HbA1c≤6.4%; 3) insulin dose<0.5U/kg/24h and HbA1c<7%; 4) stimulated C-peptide >300pmol/L. Exhaustive search was used to find the best models (based on AIC) based on usually available data at diagnosis and 3-mths. Calculator (Figure 1) available at http://www.bit.ly/T1D-partial-remission.

Results: There was low concordance between pCR definitions (Cohen’s weighted kappa 0.01-0.61.) Combination of age, HbA1c, diastolic BP, triglycerides and smoking at T1D onset predicted pCR (12-mths) with AUC=0.84. HbA1c, triglycerides and insulin dose 3-mths post-diagnosis had an AUC=0.89.

Conclusion: A new online calculator can predict pCR in adult-onset T1D for clinical and research use.

Disclosure

A.Grzelka-wozniak: None. A.S.Januszewski: None. J.Flotynska: 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. D.Zozulinska-ziolkiewicz: Advisory Panel; Abbott, Lilly, Lilly, Novo Nordisk, Medtronic, Speaker's Bureau; Abbott, Ascensia Diabetes Care, Novo Nordisk, Medtronic, Boehringer-Ingelheim, AstraZeneca. A.Uruska: Other Relationship; Lilly, Boehringer-Ingelheim, AstraZeneca, Ascensia Diabetes Care, Sanofi.
1287-P: Identifying When Incident Diabetes Was Diagnosed in Children and Young Adults, Using Natural Language Processing of Clinical Notes
Authors: WONG ANTHONY , ZHONG VICTOR W. , ROSENMAN MARC
Published: June 2023

Identifying when an incident diabetes (DM) diagnosis was made is complicated using retrospective, structured electronic health record (EHR) data alone. Unstructured clinical notes have been underused but contain valuable information that could complement traditional methods. However, manually reviewing clinical notes is time-consuming. We developed and validated a simple rule-based Natural Language Processing (NLP) method to extract incident DM timing from clinical notes.

In a single center we used structured EHR data to identify a cohort (age <45 as of 12/31/19) with likely type 1 (T1D) or type 2 (T2D) DM based on 2016-2019 records: (≥1 T1D ICD-10 code and insulin and no other DM medication) or ([≥2 T2D and no T1D codes] or [≥1 T2D code and a DM medication besides insulin or metformin]).

This cohort had 2,654 patients (548,316 clinical notes, 2003-present). We randomly selected 58,450 clinical notes (1,465 patients) as a training set to look for relevant text patterns. We handcrafted the rules into our NLP tool. We required 3 distinct concepts at the sentence level to determine an incident DM diagnosis: DM (not, e.g., epilepsy), an onset attribute (e.g., “diagnosed in”), and a temporal component (e.g., 8/2008). We pre-defined all related keywords and date formats for these concepts in our training notes. We then tested the NLP algorithm against manual review in an independent set of 100 randomly selected patients from the cohort. Analysis was at the patient level (true+: ≥1 true+ note per patient).

NLP in the training set found 1,268 patients with at least 1 of the 3 concepts and 826 patients with all 3. In the test set, we excluded 4 patients without substantive notes. NLP correctly detected incident DM timing in 73 of 96 patients. The NLP had recall 88%, specificity 77%, precision (PPV) 96%, and NPV 50%.

NLP was helpful in finding incident DM timing and may complement structured EHR queries for identifying incident DM. Refinement of our NLP algorithm is ongoing.

Disclosure

A.Wong: None. V.W.Zhong: None. M.Rosenman: None.

Funding

Centers for Disease Control and Prevention (1U18DP006693-01-00)
1291-P: Participants in Annual Workplace Health Evaluation Program Had Lower Risk for Developing Diabetes
Authors: TONG CARMEN H. , JALANDONI-BUSTAMANTE MICHELLE , FRAGALA MAREN S. , BIRSE CHARLES E.
Published: June 2023

Background: We asked whether the risk of developing diabetes would be reduced in individuals who participated in annual employer-sponsored workplace health evaluations compared to those not participating in the program.

Methods: We studied a cohort of all employees with 5 years of administrative claims data (2017-2021) and no diabetes-related pharmacy claims in the baseline year (2017). The health evaluation group was defined as individuals who participated in annual workplace health assessments for 5 consecutive years. The non-health evaluation group did not participate in workplace assessments in any year. The association between health evaluation status and incident diabetes was assessed in Cox regression models that adjusted for variables that differed between the 2 groups at baseline (Table). Incidence of diabetes was defined as any diabetes-related pharmacy claims during follow-up (2018 to 2021).

Results: Of 9,021 participants, 67.8% were female; mean baseline age (standard deviation) was 46.1 (10.4) years. After adjustment (Table footnote), annual workplace health evaluation participants (n=7,957) had a 33% lower in risk of developing diabetes compared to the non-health evaluation group (n=1,064) (Table).

Conclusions: Individuals participating in annual health evaluations in a workplace setting had lower risk of developing diabetes than non-participants.

Disclosure

C.H.Tong: None. M.Jalandoni-bustamante: Employee; Quest Diagnostics. M.S.Fragala: Employee; Quest Diagnostics, Stock/Shareholder; Quest Diagnostics. C.E.Birse: Employee; Quest Diagnostics.
13-LB: Treatment Patterns of Patients with Type 2 Diabetes Mellitus and Chronic Kidney Disease in Colombia
Authors: MACHADO MANUEL , GAVIRIA-MENDOZA ANDRÉS , FRANCO JUAN S. , FORERO MARIA D.R. , VIZCAYA DAVID , VALLADALES RESTREPO LUIS F. , MACHADO-ALBA JORGE E.
Published: June 2023

Aim: Describe treatment patterns of patients with type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) in outpatient setting from Colombia.

Methods: We conducted a cross-sectional study characterizing treatment patterns of T2DM and CKD using the Audifarma S.A. drug dispensing database and included all patients with both diagnoses using ICD-10 codes and at least one disease-related prescription from April 1st 2019 to March 31st 2020. Sociodemographic variables, comorbidities, treatment received and combinations were evaluated. Drugs were classified as those for management of T2DM (oral antidiabetic agents, insulins, SGLT2i, GLP-1 analogs (GLP1a), dipeptidyl peptidase-4 inhibitors (DPP4i)), and others including renin angiotensin aldosterone system blockers (angiotensin converting enzyme inhibitors-ACEI, angiotensin receptor antagonists-ARBs) and mineralocorticoid receptor antagonists (MRAs). A descriptive analysis with frequencies and proportions, means and standard deviation was carried out.

Results: Of a total of 194,023 patients with a primary diagnosis of T2DM, it was possible to identify that 14,722 (7.5%) had concomitant CKD, during the observation period. A total of 7513 (51%) were men, and the mean age was 74.7±10.9 years. The main comorbidities were hypertension (n=10665; 72.4%) and hypothyroidism (n=1138; 7.7%). The most used drugs were metformin (n=9901; 67.3%) alone or associated with some other antidiabetic, followed by 52.2% used DPP4i (n=7691), 17.0% an SGLT2i (n=2500), and 5.2% GLP-1a (n=766). Additionally, 67.2% (n=9895) of patients were under treatment with ARBs, 15.8% (n=2325) with ACEIs and 10.9% (n=1598) with MRAs.

Conclusions: This contemporary study from Colombia further highlights the complexity and heterogeneity of treating patients with T2DM and CKD, which could be improved if the beneficial properties of newer agents that have shown positive anti-hyperglycemic and renal outcomes were implemented in the local treatment strategy.

Disclosure

M. Machado: Research Support; Bayer Inc., Pfizer Inc. A. Gaviria-mendoza: Employee; Audifarma S. A, Research Support; Bayer Inc., Pfizer Inc. J. S. Franco: Employee; Bayer Inc. M. D. R. Forero: Employee; Bayer Inc. D. Vizcaya: Employee; Bayer Inc. L. F. Valladales restrepo: Research Support; Bayer Inc., Pfizer Inc. J. E. Machado-alba: None.

Funding

Bayer AG
13-OR: Medication Use among Youth-Onset Diabetes in India—An Analysis of Socioeconomic Factors and Cost of Care
Authors: SAM VARGHESE JITHIN , VARGHESE NAMITHA M. , VENKAT NARAYAN K.M.
Published: June 2023

Background: Reported prevalence of youth-onset diabetes (15-30y) in India range from 1 to 1.5% with half the cases being diagnosed. National estimates indicate only 2 in 5 diagnosed cases are taking medication. Yet, data are scarce on the socio-economic predictors and financial burden associated with medication use in this population.

Methods: Using data from the National Family Health Survey 2019-21 among youth (n = 4682) with diagnosed diabetes, we estimated the association of socio-economic factors (i.e., household wealth quintile, urbanicity, and household members with diagnosed diabetes) and medication use. We used robust survey-weighted Poisson regression adjusting for sex, age, high school completion and state fixed effects. Using the National Sample Survey 2017-18, we benchmarked the average cost of inpatient and outpatient diabetes medication among youth with diabetes (n = 120) as a proportion of national net per-capita income (Rs. 115,224).

Results: Nationally, 1.2% (1.1 - 1.3) of youth 15-30 years old had diabetes, 75% of these cases were diagnosed and 30.9% (95%CI: 28.8, 33.0) of those diagnosed were talking medications. Urban residence (Prevalence ratio, PR: 1.30 [1.13, 1.51]) and increasing household wealth (highest (ref: lowest) 1.28 [1.02, 1.59]) were associated with higher medication use. A household member with diabetes was associated with lower medication use (0.45 [0.32, 0.63]). Out-of-pocket expenses corresponded to 47.0% (31.7, 62.3) of national per capita income. Medications accounted for 35.9% (22.9, 49.0) and 44.9% (33.1, 56.8) of the annual expenses for in-patient (Rs. 35511 [14935, 56088]) and out-patient (Rs. 18651 [9025, 28275]) care respectively.

Conclusions: Out of pocket expense for persons with youth-onset diabetes in India is, on average, over 40% of per capita income, with medication cost being the biggest driver. These data call for social safety nets to protect family income of those with youth-onset diabetes in India.

Disclosure

J.Varghese: None. N.M.Varghese: None. K.Narayan: None.

Funding

National Institutes of Health (P30DK111024)
130-OR: Tirzepatide Attenuates Hepatic Insulin Resistance and Glucagon Action Independent of Weight Loss and GIP Action in Diet-Induced Obese Mice
Authors: KIM BUKYUNG , TAUER LAUREN A. , HU XIAODI , KIM JASON K.
Published: June 2023

As a dual GLP-1 receptor and GIP agonist, Tirzepatide (TZP) induces weight loss and improves glycemic control in patients with type 2 diabetes. Here, we performed insulin clamp and glucagon clamp under euglycemic conditions in male C57BL/6J mice fed a high-fat diet (HFD; 12 weeks) after once-daily treatment with TZP (3 nmol/kg) or GIP (25 nmol/kg) for 5 days (n=5). TZP and GIP caused HFD-fed mice to lose 10~15% of weight, but their fat mass remained 7-fold higher than chow-fed controls (C) (Fig. 1). Insulin clamp showed that GIP caused a 37% decrease in hepatic insulin action in chow-fed mice (Fig. 2). In HFD-fed mice, TZP induced significant increases in hepatic insulin action (4-fold) and glucose turnover (25%) compared to GIP, restoring insulin sensitivity to levels comparable to controls (Fig. 2-3). TZP also increased glucose metabolism in brown fat (1,528±155 vs. 798±166 nmol/g/min in GIP). Glucagon clamp showed that TZP significantly reduced hepatic glucose production (HGP) by ~50% compared to controls and GIP (Fig. 4). CONCLUSION: These data indicate that TZP improves insulin action and reduces hepatic glucagon action in obese mice while GIP causes hepatic insulin resistance in lean mice. Our findings suggest that TZP’s glycemic control may involve amelioration of insulin resistance and glucagon resistance, independent of weight loss and GIP action in the liver.

Disclosure

B.Kim: None. L.A.Tauer: None. X.Hu: None. J.K.Kim: None.

Funding

National Institutes of Health (5U2CDK093000)
1303-P: Screening for Metabolic Dysfunction–Associated Fatty Liver Disease (MAFLD) in Asian-Indians with Type 2 Diabetes Using Vibration-Controlled Transient Elastography—A Cross-Sectional Observational Study
Authors: CHANDEL SHIVANI , RAVI TEJA K.V.
Published: June 2023

Background: Metabolic dysfunction associated fatty liver disease (MAFLD) is a common finding in people with type 2 diabetes (T2D).

Aims: To evaluate the association of liver steatosis and fibrosis in Asian-Indians with T2D using Vibration-Controlled Transient Elastography (VCTE).

Methods: A total of 120 patients underwent NAFLD screening from July 2022 to December 2022 after excluding alcoholics and nondiabetes patients we had 73 people with T2D, recruited from Liver Clinic of Endocrine speciality centre. VCTE (Fibroscan 430 Mini Plus, Echosens, France) was used for Liver Stiffness measurement (LSM) in KiloPascals (KPa) and Controlled Attenuation Parameter (CAP) in Decibels per meter (dB/m). CAP score cut-offs used for steatosis: Grade 0 < 237 dB/m, Grade I is 238 - 259 dB/m Grade II is 260 - 292 dB/m and Grade III > 292 dB/m. LSM cut-off values used: F0 < 7 kPa, F1 is 7 - 10 kPa, F2 is 10 - 13 kPa, F3 is 13 - 16 kPa and F4 > 16 kPa.

Results: The mean age was 53.4 ± 12.5 years and 26% (n=19) were women. Overweight seen in 21.9 % (n=16) and obesity in 67.1 % (n=49). We found liver steatosis in 73.7% (n=56) having Grade I in 16.4 % (n=12), Grade II in 34.2 % (n=25) and Grade III in 26 % (n=19). Liver fibrosis was detected in 30.1 % (n=22) with Mild fibrosis (F1) in 20.5 % (n=15) and clinically significant in 9.5 % (n=7) i.e., Moderate fibrosis (F2) in 6.8 % (n=5) and Cirrhosis grade (F4) in 2.7 % (n=2). We noticed that CAP score had significant positive correlation with BMI (P=0.01) and LSM had significant positive correlation with BMI (p=0.001), SGOT (p=0.01), SGPT (p=0.015) and Platelet count (P=0.04).

Conclusions: Our data demonstrated that people with T2D have a high prevalence of steatosis and fibrosis which can lead to the development and progression of complications with high morbidity and mortality rates. So, we suggest screening for MAFLD should be a universal approach in diabetes co-morbidities management.

Disclosure

S. Chandel: None.K. Ravi Teja: None.
1304-P: Exocrine Pancreatic Insufficiency (EPI) Likely Overlooked in Diabetes as Common Cause of Gastrointestinal-Related Symptoms
Authors: LEWIS DANA M.
Published: June 2023

Background: Exocrine Pancreatic Insufficiency (EPI/PEI) occurs when the pancreas no longer makes enough enzymes to support digestion. Awareness among diabetes care providers does not match the likely rates of prevalence and contributes to underscreening and underdiagnosis of EPI among people with diabetes.

Methods: A systematic review of EPI was performed. Resulting articles were analyzed for whether the articles were on diabetes or other co-conditions. Articles on EPI and diabetes were analyzed for type of diabetes, prevalence of EPI reported in diabetes, and publication name. A subsequent literature review of prevalence studies of gastrointestinal conditions in people with diabetes was also performed and data was analyzed to estimate prevalence and compare rates of gastroparesis, celiac, and EPI among people with diabetes.

Results: The systematic review of EPI found 644 articles, of which only 40 were focused on EPI and diabetes (12 Type 1, 7 Type 2, 20 both T1/T2 or all types; 1 neonatal). They represent 9.6% of the EPI co-condition literature (n=418) and were published in 29 journals, of which only 9 were diabetes journals. Most were studies on prevalence or diagnosis; whereas one recent article demonstrates a method for evaluating improved glycemic variability following treatment for EPI. The literature review on other GI conditions in people with diabetes found prevalence of 1.3% for gastroparesis, with differing estimates in Type 1 (up to 5% for those who sought care) and Type 2 (1%), and 5% for celiac in Type 1. Prevalence reported for EPI in people with diabetes is higher: estimates vary from 20-50%.

Conclusion: Gastroparesis and celiac are often top of mind for diabetes providers, yet EPI/PEI is ~10 times more common among people with diabetes. Healthcare providers who see people with diabetes should increase the screening of fecal elastase (FEL-1) for people with diabetes who mention gastrointestinal symptoms.

Disclosure

D.M.Lewis: None.
1309-P: Dietary Iron and Kidney Function in Youth and Young Adults with Type 1 Diabetes
Authors: CONWAY REBECCA B. , CRUME TESSA L. , PERNG WEI , MCCLAIN DONALD A. , DABELEA DANA
Published: June 2023

The association of markers of body iron stores with kidney disease in type 1 diabetes (T1D) is complex, with both positive and inverse relationships observed. Little data are available on the relationship of dietary iron (DI) intake with markers of kidney function, prior to occult disease, in youth and young adults with T1D. We tested the association of DI with albumin-to-creatinine ratio (ACR), both measured at multiple time points over a 14-year period in youth and young adults with T1D. Study participants (n=629) were from the Colorado site of the SEARCH for Diabetes in Youth study who completed research visits at baseline and (<1yr diabetes duration) and at least one follow-up visit over 14 years. We applied linear mixed models (repeated measures analysis) to test the hypothesis that higher DI over time is longitudinally associated with a higher ACR, which was natural log-transformed prior to regression analysis. Results: Mean age and diabetes duration at study baseline were 10.2 (std 4.2) years and 10.4 (std 6.8) months, respectively. Older age at baseline (p=0.009), female sex (vs. male, p=0.002), and Black race (vs Non-Hispanic White, p<0.001) were each associated with higher ACR levels across follow-up. Contrary to our hypothesis, average DI intake was inversely associated with ACR levels in analyses adjusted for age, sex, and race (p<0.05). This inverse relationship persisted after further controlling for average body mass index (BMI) over time. However, controlling for average HbA1c levels over time, which were positively associated with ACR (p=0.001), attenuated the relationship between DI intake and ACR (p=0.12). In conclusion, total DI intake in children and young adults was associated with a lower ACR over 14 years, but the association was confounded by HbA1c, suggesting that DI may be a marker of total glycemic load. Whether this relationship varies by heme/non-heme content needs to be further explored. These data highlight the important role of diet in the early years after T1D onset.

Disclosure

R.B.Conway: None. T.L.Crume: None. W.Perng: None. D.A.Mcclain: None. D.Dabelea: None.
1322-P: Association of Long-Term Blood Pressure Variability and Decrease in GFR on Type 2 Diabetes Mellitus Patients with Hypertension
Authors: SAKAMOTO MASAYA , YUKI MASAHIRO , MIYASHITA KAZUTOSHI , YAMAZAKI TSUTOMU
Published: June 2023

Introduction: Increased long-term blood pressure variability (BPV), defined as monthly to yearly BPV, has been reported a risk factor of cardiovascular events independent of mean BP level. However, the relationship between long-term BPV and decrease in GFR remains unknown. In this study, we examined the association of Long-Term BPV and decrease in GFR.

Methods: We included 214,443 type 2 diabetes mellitus patients with hypertension, registered in the Japan Diabetes Data Management Study Group, whose BP and HbA1c were simultaneously measured at least 4 times per year for 5 years from 2014-2018. BPV was defined as the 5-year coefficient of variation (CV), and the relationship between BPV and eGFR was examined. We also examined the relationship between BPV and the following background factors: (1) age (2) duration of diabetes (3) HbA1c (4) antihypertensive medications. The Ca-antagonist group was patients who took only Ca-antagonists during the 5-year period, and the ARB group was patients who took only ARBs. This study was a retrospective analysis. Data analyses were performed using the SPSS 28.0 software.

Results: The group with greater 5-year BPV had lower eGFR than the group with smaller BPV, independent of mean BP (P<0.001). Regarding BPV and patient background, (1) BPV tended to increase with increasing age, and was significantly greater in patients over 50 years of age compared to those in their 30s (P<0.001). (2) The longer diabetic duration, the greater the BPV (P<0.001). Especially in patients more than 20 years’ diabetic duration, BPV was significantly larger than that of less than 5 years (P<0.001). (3) There was no association between HbA1c and BPV. (4) BPV was significantly lower in the Ca antagonist group compared with the ARB group over 5 years (0.069 vs. 0.078 P<0.001). Conclusion: Increased long-term BPV was observed older age and long duration of diabetes, but was not related to HbA1c. Interestingly, Patients with greater BPV had lower eGFR at 5 years.

Disclosure

M.Sakamoto: None. M.Yuki: None. K.Miyashita: None. T.Yamazaki: None.
1323-P: Meta-analysis of Multiple Comorbidities Associated with Type 2 Diabetes
Authors: KHACHIKYAN LIANNA , WORKU HELINA , RAPISORA KRIZIA , PEREZ ELIZABETH , CHIU CHIA , KABO JOHN M. , HO NHUT
Published: June 2023

Many meta-analyses focus on one comorbidity associated with Type 2 diabetes mellitus (T2DM). However, people living with T2DM experience more than one comorbidity. The primary objective of this study was to conduct a comprehensive systematic review and meta-analysis on recent published data, considering 43 individual comorbidities which we grouped into 11 disease categories to identify the most prevalent comorbidities occurring with people living with T2DM. PubMed database was searched for studies on T2DM and comorbidities prevalence in adults from 2015 - 2020. Meta-analysis estimates of comorbidities prevalence were generated using a random-effects model. ANOVA analysis, Bonferroni test, and chi-square analysis were conducted to examine the statistical significance of our results; see Figure 1. 22 studies with nearly 90 million patients were eligible and included. Hyperlipidemia/Obesity (33%) and acute circulatory diseases (28%) occur more frequently compared to other comorbidities in patients with T2DM. Our analysis shows acute circulatory diseases and hyperlipidemia/obesity are the most prevalent comorbidities for patients with T2DM.

Disclosure

L.Khachikyan: None. H.Worku: None. K.Rapisora: None. E.Perez: None. C.Chiu: Employee; Medtronic. J.M.Kabo: None. N.Ho: None.
1326-P: Diabetes Is Associated with a Higher Hearing Loss Risk in an Observational and Mendelian Randomization Study
Authors: LI TONGTONG , GAN WEI , FENG CHENGWU , LIU YUNAN , CAO YAYING , HAN HAN , FU DONGHENG , XING HUADONG , QIN HAIQIANG , SUN MENG , WANG MENG , ZONG GENG
Published: June 2023

Observational studies on diabetes and hearing loss have been controversial, and their potential causal relationship has not been investigated. We conducted Mendelian randomization (MR) analyses to determine whether type 1 diabetes (T1D), type 2 diabetes (T2D), fasting insulin (FI), 2-h glucose (2hG), fasting glucose (FG), and glycated hemoglobin (HbA1c) were associated with hearing loss. Among 497,998 individuals in the UK biobank, T1D and T2D were identified by medical history in questionnaires and clinical records. Hearing loss was primarily defined by speech-in-noise tests in the better ear (SiN hearing loss, SiNHL) and secondarily identified by International Classification of Diseases code (ICD-defined hearing loss, ICDHL) and self-reported data (hearing difficulty, HDiff; hearing difficulty with noise, HDiffn; and hearing aid use, HAid). In observational analyses, odds ratios (ORs) in people with T1D than those without diabetes were 1.27 (95% CI 1.06-1.53) for SiNHL, 1.36 (1.14-1.62) for HAid, and 1.78 (1.49-2.12) for ICDHL. The corresponding ORs in people with T2D were 1.17 (1.09-1.24), 1.16 (1.08-1.23), and 1.25 (1.16-1.34), respectively. In MR analyses, genetically predicted T1D and T2D were associated with a higher risk of SiNHL (OR 1.02 per 1-unit higher log-odds of T1D 1.02 [1.00-1.03]; T2D 1.03 [0.99-1.06]). Further analysis of glycemic traits supported an inverse association of genetically elevated FI on SiNHL (per 1-log unit increase in pmol/L FI 0.71 [0.54-0.94]), and a positive association for genetically elevated 2hG (per 1-log unit increase in mmol/L 2hG 1.18 [1.06-1.31]). Results were largely robust to sensitivity analyses accounting for horizontal pleiotropy, sample overlap, and definitions of hearing loss. Our study suggested a potential causal relationship between diabetes and hearing loss risk. The finding warrants confirmation by larger population-based studies and experimental studies on potential biological pathways.

Disclosure

T.Li: None. M.Sun: None. M.Wang: None. G.Zong: None. W.Gan: Employee; Novo Nordisk A/S. C.Feng: None. Y.Liu: None. Y.Cao: None. H.Han: None. D.Fu: None. H.Xing: None. H.Qin: None.

Funding

National Science Fund for Excellent Young Scholars (81922060)
1328-P: Impact of Early Childhood-Onset Type 1 Diabetes on Brain Structural Trajectories (CLARiFY Study)
Authors: GBADEYAN OYETUNDE , MORAN CHRIS , BROWN AMY , SAKOWSKI STACEY A. , SRIKANTH VELANDAI , CAMERON FERGUS , NORTHAM ELISABETH A. , FELDMAN EVA L. , BEARE RICHARD
Published: June 2023

Although childhood-onset of Type 1 diabetes (T1D) is associated with alterations in structural brain development, the influence of T1D over time remains poorly understood. We aimed to compare the trajectories of brain structure change in a sample of children with T1D to age-matched children without T1D. We recruited children presenting to a tertiary hospital in Australia between 1990 - 1992 into this prospective cohort study (Cognition and Longitudinal Assessment of Risk Factors over 30 Years (CLARiFY) Study). Brain magnetic resonance imaging (MRI) was performed at two time points, approximately 20 years apart. We examined for between-group differences in normalized brain volumes and cortical thickness (CT) across time using linear mixed models. A total of 127 images were available at timepoint 1 (77 with T1D, mean age=20 years, 43% female) and 68 at timepoint 2 (36 with T1D, mean age=37 years, 49% female). At timepoint 1, those with T1D had lower subcortical gray matter volume than those without T1D (p=0.01) but the remaining measures were similar. Across time, those with T1D had greater decline in cortical thickness (β=-2280, p=0.03) than those without T1D, with trajectories in other measures being similar (Table). In conclusion, these preliminary findings suggest that childhood-onset T1D is associated with lower subcortical gray matter and altered development of cortical gray matter over time.

Disclosure

O.Gbadeyan: None. C.Moran: None. A.Brown: None. S.A.Sakowski: None. V.Srikanth: None. F.Cameron: None. E.A.Northam: None. E.L.Feldman: None. R.Beare: None.

Funding

National Institutes of Health (R01DK129320)
133-LB: Proof-of-Concept Study Results with a New Osmotic-Pressure–Based Continuous Glucose Sensor
Authors: PFÜTZNER ANDREAS , HANNA MINA , THOMÉ NICOLE , JENSCH HENDRICK
Published: June 2023

Background: The Sencell sensor (Lifecare AS, Bergen, Norway) uses glucose induced changes in an osmotic pressure chamber for continuous measurement of glucose concentrations in the subcutaneous tissue. A close to linear correlation between the raw sensor signal and the glucose concentration and a very long duration of use (of up to 6-12 months or longer) are theoretically to be expected. The final device is planned to have the size of a grain of rice and to be implanted employing wireless energy and data transfer.

Method: For a first clinical proof of concept study in humans, a wired version of the core sensing technology was embedded into a 4 mm needle and inserted into the abdominal subcutaneous tissue of healthy volunteers. The study was conducted to collect first human proof-of-concept performance data for algorithm development during meal experiments and for further device optimization. The raw data was analyzed after one-point calibration and minor trend correction in comparison to the Statstrip blood glucose meter and the Freestyle Libre 2 glucose sensor.

Results: Seven participants (5 female, 2 male, age: 49±11 years) delivered a total of 105 direct comparator data-points (vs. Statstrip blood glucose meter) during repeated meal experiments with observation periods between 2 h and up to 72 days. The osmotic-pressure sensor followed glucose changes similar to the FreeStyle Libre device and reached an MARD of 9.8% in comparison to StatStrip (87 % and 13 % of the datapoints were lying in zones A and B of the consensus error grid, respectively).

Conclusions: In this first human proof-of-concept study, the osmotic-pressure based continuous glucose sensor was shown to track s.c. glucose concentrations in a comparable manner as the Libre 2 needle sensor. The clinical performance characteristics of the first wired prototypes provide an encouraging perspective for the upcoming next development steps.

Disclosure

A. Pfützner: Consultant; Novo Nordisk A/S, Research Support; LifeScan Diabetes Institute, Speaker's Bureau; AstraZeneca, Stock/Shareholder; Lifecare A/S, Diakard. M. Hanna: None. N. Thomé: None. H. Jensch: None.

Funding

Lifecare AS (LIFC-SEN-001)
1336-P: Predicting the Progression of Stages of Neuropathy Using Routine Eye and Kidney Tests—An Application of Novel Statistical Methods in the Diabetes Control and Complications Trial (DCCT)
Authors: ERIK LOVBLOM LEIF , BRIOLLAIS LAURENT , TOMLINSON GEORGE , PERKINS BRUCE A.
Published: June 2023

Despite recent advances, neuropathy screening is not consistently performed in clinical practice. We aimed to determine if neuropathy risk could be predicted using the trajectories of routinely-performed eye and kidney screening tests in T1D. We used 28-year data from the DCCT/EDIC study, available via the NIH public repository. We used the Early Treatment Diabetic Retinopathy Study Research (ETDRS) Group 23-point scale, albumin excretion rate (AER), and eGFR treated as longitudinal outcomes. Simultaneously, we represented neuropathy as a 3-state progressive multistate outcome using nerve conduction studies and the Michigan Neuropathy Screening Instrument (MNSI) for early-stage neuropathy and the occurrence of serious foot ulcer or amputation for late-stage neuropathy. To model these interrelated disease processes, we used and developed joint models with multistate submodels. Our “joint multistate model” accounted for interval censoring: due to the visit schedule, the exact time of transition to early-stage neuropathy was known only to occur in between consecutive visits. A Bayesian estimation procedure was used. We found that the risk of transition from no to early-stage neuropathy was affected by the current value of ETDRS, the current slope of ETDRS, and the current value of AER. For example, controlling for all covariates including eGFR, the there was a 23% higher rate of occurrence of this early-stage for a 3-step higher ETDRS scale. In the same model controlling for all covariates, progression from early-stage to late-stage neuropathy was affected mainly by AER (11% higher rate for a doubling of AER). Routinely-performed clinical eye and kidney test results can be leveraged to help identify the risk of neuropathy. Future work will develop dynamic predictions integrated into an electronic medical record.

Disclosure

L.Lovblom: None. L.Briollais: None. G.Tomlinson: None. B.A.Perkins: Advisory Panel; Dexcom, Inc., Insulet Corporation, Novo Nordisk, Sanofi, Vertex Pharmaceuticals Incorporated, Other Relationship; Abbott, Medtronic, Sanofi, Research Support; Novo Nordisk, Bank of Montreal (BMO).
1337-P: Association of Uncontrolled Diabetes with Periodontal Disease in U.S. Adults
Authors: VU GIANG , LITTLE BERT B. , KING CHRISTIAN , GURUPUR VARADRAJ P. , SHAKIB SHAMINUL
Published: June 2023

Objectives: The purpose of this study was to analyze the relationship between uncontrolled diabetes with periodontal disease (PD) among adults in the US.

Methods: The study sample from the 2009-2014 National Health and Nutrition Examination Survey data included 10,071 US participants aged ≥ 30 years in a probability weighted sample. We used the Centers for Disease Control and Prevention/American Academy of Periodontology’s standard to measure PD status by using means of a full-month oral examination at 6 sites per tooth for periodontal probing depth and clinical attachment loss. We used self-reported response to the diabetes questionnaire and laboratory report of HbA1c to assess the participant’s diabetes status (no diabetes, diabetes with HbA1c < 9%, diabetes with HbA1c ≥ 9%). Multiple logistic regression analysis was performed to examine the relationship between diabetes status with PD.

Results: Multiple logistic regression showed that PD was significantly associated with controlled diabetes (adjusted odds ratio (OR) = 1.32, 95% confidence interval (CI): 1.01 - 1.73, p <0.05) and uncontrolled diabetes (OR = 2.48, 95% CI: 1.52 - 4.04, p <0.001) after adjusting for covariates. PD’s protective factors of PD included annual dental visit, female gender, and college education. PD’s risk factors were smoking status, racial minorities, income <200% Federal Poverty Guidelines, and older age.

Conclusions: Uncontrolled diabetes was significantly associated with a higher risk of periodontal disease among adults in the US. Physicians should work with dentists to strongly recommend patients with diabetes to check their glycemic level and have an annual dental visit.

Disclosure

G.Vu: None. B.B.Little: None. C.King: None. V.P.Gurupur: None. S.Shakib: None.
1338-P: Characteristics of Patients with Type 2 Diabetes without Nonalcoholic Fatty Liver Disease (NAFLD)
Authors: VALDEZ SAENZ ENRIQUE , GODINEZ LEIVA EDDISON , LOMONACO ROMINA , MARANGI STEPHEN A. , KALAVALAPALLI SRILAXMI , GONZALEZ MARIA A. , CHI XIAOFEI , ORTIZ ROCHA ANDREA , MOHSENI YASMINE , BARB DIANA , GURKA MATTHEW J. , SHARMA ANU , CUSI KENNETH
Published: June 2023

About 70% of patients with type 2 diabetes mellitus (T2DM) have NAFLD which is a risk factor for cirrhosis and hepatocellular carcinoma. Many factors may be associated with more severe disease (i.e., insulin resistance, obesity). However, the metabolic profile of T2DM patients spared from having NAFLD and liver fibrosis is unclear. To this end, we recruited 266 patients with a history of T2DM without a known history of NAFLD (age: 59 ± 10 years; female 58.3 %; BMI: 33.0 ± 6.3 kg/m2, A1c: 7.0 ± 1.4 %) attending the outpatient university clinics. We performed a medical history, physical exam and measured routine/metabolic laboratories, liver fat (by CAP score ≥ 274 dB/m) and fibrosis (by liver stiffness measurement or LSM ≥7.0 kPa or F≥1) by elastography. A total of 32% patients did not have NAFLD, but when compared to NAFLD patients there were no differences in terms of age, gender, or race. Those without NAFLD had a lower mean BMI ± SD (29.6 ± 5.2 vs. 34.6 ± 6.2 kg/m2) and better glycemic control (mean A1c: 6.7 ± 1.3% vs. 7.2 ± 1.4%, both p<0.05). Patients without NAFLD had lower plasma ALT levels (mean 21 ± 12 vs. 28 ± 19 U/L; p<0.05). Patients with NAFLD had more severe (hepatic) insulin resistance (IR) (HOMA-IR: 3.0 ± 2.3 vs. 4.9 ± 3.2, p<0.05), with more people having a HOMA-IR ≥3.0 (35% vs. 72%, p<0.05). In multiple regression analysis, with a 95% CI, obesity (OR 4.0, 2.3-7.1), HOMA-IR (OR 3.1, 1.0-5.7), and worse glycemic control (A1c) (OR 1.7, 1.1-2.9) accounted for most of the difference between subjects with vs. without NAFLD. In NAFLD patients, comparing those with vs. without fibrosis, obesity (OR 2.8, 1.6-4.9) and elevated aminotransferases (OR 2.1, 1.3-3.2) accounted for most of the difference among patient. Conclusion: Patients with type 2 diabetes mellitus without NAFLD are usually more insulin sensitive and have a more favorable cardiometabolic profile than those with NAFLD. This highlights the role of insulin resistance and lipotoxicity in the development of NAFLD in this population.

Disclosure

E.Valdez saenz: None. D.Barb: None. M.J.Gurka: None. A.Sharma: None. K.Cusi: Consultant; Poxel SA, 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, Research Support; Echosens, Inventiva, LabCorp, Zydus. E.Godinez leiva: None. R.Lomonaco: None. S.A.Marangi: None. S.Kalavalapalli: None. M.A.Gonzalez: None. X.Chi: None. A.Ortiz rocha: None. Y.Mohseni: None.

Funding

National Institutes of Health (R01120331-01A1)