bluuebunny/crossref_metadata_2025_split huggingface dataset:
411-P: Extended Generalized Metabolic Fluxes (GMF) Based Digital Twins for Predicting CKD
Authors: SURIAN NAVEENAH , BATAGOV ARSEN , WU ANDREW , LAI WEN B. , DALAN RINKOO 
Published: June 2024

Introduction: CKD is a prominent complication in diabetes patients. Our regulatory-approved digital twin model, HealthVector Diabetes (HVD), leverages generalized metabolic fluxes (GMF) to predict CKD within a 3-year timeframe using common biochemical and physiological parameters. HVD achieved an accuracy of 0.86 in our clinical validation studies. In this study, we aim to explore the expanded use case of HVD when incorporating specialized input parameters related to vascular dysfunction for the prediction of CKD.
Methods: A preliminary investigation involved collecting follow-up records from a previous T2DM clinical trial. Eligible patients had to be CKD-negative at baseline according to eGFR and ACR criteria and have either eGFR or ACR follow-up readings within 3 years from baseline. A total of 20 input parameters, including specialized ones (carotid intima-media thickness (CIMT), logarithmic reactive hyperemia index (lnRHI), pulse wave velocity (PWV), oxidized low density lipoprotein (ox-LDL), haptoglobin, ferritin, reactive oxygen metabolites (ROM), biological antioxidant potential (BAP), high sensitivity C-reactive protein (hs-CRP)), were gathered at baseline to calculate the GMF for predicting future CKD within 3 years.
Results: We identified 193 eligible patients based on our inclusion and exclusion criteria, with 22 developing CKD within 3 years. Extending HVD for prediction resulted in an AUC-ROC of 0.90.
Conclusion: The extension of our regulatory-approved software as a medical device digital twin model, HealthVector Diabetes continues to perform well. It accurately predicts CKD within 3 years with 90% accuracy using specialized inputs assessing vascular dysfunction.

Disclosure
N. Surian: Employee; Mesh Bio Pte. Ltd. A. Batagov: Employee; Mesh Bio. A. Wu: Employee; Mesh Bio. W.B. Lai: Employee; MESH BIO PTE LTD. R. Dalan: None.
425-P: Retrospective Analysis of Glycemic Profiles and Variabilities Using Continuous Glucose Monitoring in Elderly People with Type 2 Diabetes Undergoing Hemodialysis
Authors: HAYASHI AKINORI , MATOBA KENTA , SUZUKI AKIHIKO , MIYATSUKA TAKESHI 
Published: June 2024

People with type 2 diabetes undergoing hemodialysis (T2HD) exhibit distinct glycemic profiles. The details of glycemic profiles in elderly people with T2HD, however, remain unclear. Sensor glucose levels (SGLs) were analyzed using continuous glucose monitoring (CGM) in 116 subjects with T2HD, investigating differences in clinical parameters and CGM metrics between elderly group (≥ 65 years) and non-elderly group (&lt; 65 years). For retrospective analysis, 55 in elderly group (39 males, age 72 years, HbA1c 6.3%, glycated albumin (GA) 22.5%) and 61 in non-elderly group (41 males, age 52 years, HbA1c 6.7%, GA 19.8%) were selected. Among these, 30 (54.6%) in elderly group and 48 (78.7%) in non-elderly group were on insulin therapy (p=0.0057). While no difference was observed in HbA1c between the two groups, GA was significantly higher in elderly group (p=0.0401). Mean and SD of SGL showed no difference between the two groups, but %CV was significantly higher in elderly group (30.0±7.6% vs 37.0±7.7%, p=0.0357). There was no disparity in time in range (TIR, 70-180 mg/dL), time below range (TBR, &lt; 70 mg/dL), and time above range (TAR, &gt; 180 mg/dL). However, TBR (&lt; 54 mg/dL) was significantly higher in elderly group (0.63±0.19[SE]% vs 0.32±0.18[SE]%, p=0.0499). In elderly group, 30.9% experienced all-cause hypoglycemia, and 27.3% experienced hemodialysis-induced hypoglycemia, compared to 31.2% and 16.4% in non-elderly group.
In conclusion, although there was no difference in HbA1c and mean SGL between the two groups, glycemic variability and the incidence of severe hypoglycemia were significantly higher in the elderly group.

Disclosure
A. Hayashi: None. K. Matoba: None. A. Suzuki: None. T. Miyatsuka: None.

Funding
JSPS KAKENHI(22K15674), Grants for young researchers from Japan Association for Diabetes Education and Care (2021-YNG-028)
430-P: Development and Internal Validation of Machine-Learning Algorithms for Diabetic Kidney Disease Model of People with Type 2 Diabetes Mellitus
Authors: ZHANG LIN 
Published: June 2024

Objective: This study aims to establish DKD early screening model through different machine learning algorithms according to the clinical characteristics and biological indicators of type 2 diabetes patients, and compare its predictive value for DKD.
Methods: We selected 74,982 type 2 diabetes patients hospitalized in Beijing Tongren Hospital from 2013 to 2022. The collected-data included common clinical characteristics and biological indicators. 625 DKD cases was diagnosed with the increase of urine microalbumin or the decrease of eGFR and diabetes retinopathy, and 1336 cases were diagnosed as Non-DKD. Establish DKD early screening models through 7 machine learning algorithms: Deep Neural Network(DNN), RF, SVM, XGBoost, GMB, DRF, Naive Bayes.
Result: DNN were established for different feature dimensions: D0: blood routine, AUC=0.6911; D1: blood routine, DBP, SBP, WHR, AUC=0.7919; D2 : D1 dataset, biochemical indicators, AUC=0.8517. Evaluating the accuracy of the model, AUC of DNN is 0.902, while other algorithms have AUC between 0.81 and 0.88.
Conclusion: The best prediction result is D2 dataset, which is the most effective combined with biochemical indicators to predict DKD; The single blood routine index also has important value in predicting the development of DKD. DNN is the the best model compared to other machine learning algorithms.

Disclosure
L. Zhang: None.
447-P: Type 2 Diabetes Is Not a Coronary Artery Disease Risk Equivalent—Long-Term Results from a Prospective Cohort Study on Patients Who Underwent Coronary Angiography
Authors: PLATTNER THOMAS , LARCHER BARBARA , MADER ARTHUR , VONBANK ALEXANDER , LEIHERER ANDREAS , MUENDLEIN AXEL , DREXEL HEINZ , SAELY CHRISTOPH H. 
Published: June 2024

Type 2 Diabetes (T2DM) and pre-existing coronary artery disease (CAD) are strong and independent risk factors for cardiovascular events, and data from large cohort studies suggest that the cardiovascular risk conferred by T2DM in the absence of CAD is equivalent to that conferred by CAD in the absence of T2DM. However, because the presence of CAD in these studies was defined clinically rather than by visualization, unrecognized subclinical CAD in T2DM patients may have biased results. We therefore prospectively investigated patients with T2DM and nondiabetic subjects in whom the baseline CAD state was diagnosed angiographically. We recorded cardiovascular events over a follow-up period of 22 years in a large cohort of 1819 patients undergoing coronary angiography for the evaluation of established or suspected stable CAD. From our patients, 595 had neither significant CAD nor T2DM (CAD-/T2DM-), 171 had T2DM but not significant CAD (CAD-/T2DM+), 701 had significant CAD but not T2DM (CAD+/T2DM-) and 352 had both T2DM and significant CAD (CAD+/T2DM+). The incidence of cardiovascular events was lowest in CAD-/T2DM- patients (24.7%). Compared to this group it was significantly higher in CAD-/T2DM+ patients (36.1%; p&lt;0.001) and in CAD+/T2DM- patients (50.8%; p&lt;0.001) and highest (p=0.001) in CAD+/T2DM+ patients, in whom it was higher than in CAD-/T2DM+ (p&lt;0.001) or CAD+/T2DM- (p=0.001) patients. Importantly, CAD+/T2DM- patients were at a significantly higher risk of cardiovascular events than CAD-/T2DM+ patients (p&lt;0.001). In Cox regression analysis the risk increase conferred by CAD was higher (adjusted (HR 2.35 [1.92-2.89]; p&lt;0.001) than that conferred by T2DM (adjusted HR 1.54 [1.33-1.78]; p&lt; 0.001). From our long term results we conclude that angiographically diagnosed CAD is a stronger predictor of future cardiovascular events than T2DM. T2DM is not a CAD risk equivalent.

Disclosure
T. Plattner: None. B. Larcher: None. A. Mader: None. A. Vonbank: None. A. Leiherer: None. A. Muendlein: None. H. Drexel: None. C.H. Saely: None.
457-P: Association of System Inflammation Index with Risk of Cardiovascular Mortality among Individuals with Type 2 Diabetes
Authors: LI HAN , GUO WENWEN , LI YIXUAN , ZENG TIANSHU ,   ESQ., KONG WEN 
Published: June 2024

Introduction & Objective: This study aimed to examine the associations of system inflammation index, including system inflammation response index (SIRI) and system immune-inflammation index (SII), with cardiovascular mortality in adults with type 2 diabetes (T2D).
Methods: This analysis included 2,954 individuals from the National Health and Nutrition Examination Survey (NHANES) 1999-2010. Cardiovascular mortality was ascertained by linkage to National Death Index (NDI) records through 31 December 2019. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).
Results: During an average of 12.4 years of follow-up, 248 cardiovascular disease (CVD) deaths occurred. After multivariate adjustment, per one-unit increment in SIRI was significantly associated with a 16% higher risk of cardiovascular mortality (P &lt;0.0001) in a dose-response manner (P non-linear = 0.26). However, the association between SII and CVD deaths exhibits a J-shaped relationship (P non-linear = 0.03) and When extreme level of SII was compared, the multivariate-adjusted HR was 1.81 (95% CI 1.11, 2.95) for CVD deaths (P trend = 0.017).
Conclusion: Higher SIRI and very high SII were linearly associated with elevated risk of cardiovascular mortality among individuals with T2D.

Disclosure
H. Li: None. W. Guo: None. Y. Li: None. T. Zeng: None. W. Kong: None.

Funding
National Natural Science Foundation of China (Grant No. 81974107); Bethune-Merck Diabetes Research Foundation (Grant No. G-X-2019-056);
463-P: Remnant Cholesterol as a Predictor of Major Cardiovascular Events in Cardiovascular Disease Patients with Differing Glycemic State
Authors: DREXEL HEINZ , PLATTNER THOMAS , LARCHER BARBARA , MADER ARTHUR , VONBANK ALEXANDER , ELSNER PASCAL , LEIHERER ANDREAS , MUENDLEIN AXEL , SAELY CHRISTOPH H. 
Published: June 2024

Remnant cholesterol has attracted interest as a marker of cardiovascular event risk. The power of remnant cholesterol to predict major cardiovascular events (MACE) in patients with differing fasting glucose state is unclear and is addressed in the present study. We prospectively recorded MACE including cardiovascular death, non-fatal myocardial infarction and non-fatal stroke in a high-risk cohort of 1787 patients with cardiovascular disease,1472 had angiographically proven coronary artery disease and 315 had sonographically proven peripheral artery disease, over a mean follow-up period of 10.7±5.0 years. At baseline, remnant cholesterol significantly increased from patients with NFG (n=690) over those with IFG (n=505) to those with T2DM (n=592; 19±21 mg/dl, 24±23 mg/dl and 26±24 mg/dl, respectively; ptrend&lt;0.001). During follow-up, 719 of our patients suffered MACE; the incidence of MACE in subjects with NFG, IFG and T2DM was 37.8%, 34.4% and 49.1%, respectively, ptrend&lt;0.001.Remnant cholesterol in the total study population predicted MACE (standardized adjusted HR 1.17 [1.09-1.27], p&lt;0.001) in Cox regression models adjusting for age, sex, hypertension, smoking, body mass index and LDL cholesterol and also after additional adjustment for the baseline glycemic state (HR=1.15 [1.07-1.23], p&lt;0.001). In subgroup analyses, standardized adjusted HR were 1.19 [1.05-1.35], p=0.005), 1.12 [0.96-1.30], p=0.146) and 1.15 [1.02-1.29], p=0.025) in patients with NFG, IFG and T2DM, respectively. An interaction term remnant cholesterol by glycemic state was not significant (p=0.363), indicating that the glycemic state did not significantly impact the power of remnant cholesterol to predict MACE. From our data we conclude that remnant cholesterol is a predictor of MACE in CVD patients irrespective of the baseline glycemic state.

Disclosure
H. Drexel: None. T. Plattner: None. B. Larcher: None. A. Mader: None. A. Vonbank: None. P. Elsner: None. A. Leiherer: None. A. Muendlein: None. C.H. Saely: None.
473-P: Hyperglycemia Increases the Biomechanical Response in Endothelial Cells
Authors: SCHELLER STEPHEN , STEWARD ROBERT 
Published: June 2024

Introduction and Objective: Cardiovascular disease (CVD) is a common complication associated with diabetes. Hyperglycemia can lead to vascular changes resulting in endothelial dysfunction. While many studies have shown the molecular mechanisms by which hyperglycemia affects the vasculature, few studies have looked at how hyperglycemia affects the structure and mechanical function of the vasculature. We hypothesized that hyperglycemia will change the biomechanical response of endothelial cells.
Methods: Human Umbilical Vein Endothelial Cells (HUVECs) were cultured in media with normal glucose (5.0mM) or media with high glucose (13.9mM) for 8 days. To determine the biomechanical response, we used traction force microscopy and monolayer stress microscopy to measure cell-cell intercellular stresses and cell-substrate contractile forces (tractions) on day 8.
Results: Cells exposed to high glucose for 8 days had average normal intercellular stresses, maximum shear intercellular stresses, and tractions that were on average 121%, 22%, and 37%, respectively, higher compared to cells in normal glucose for 8 days.
Conclusion: A glucose level of 13.9mM (hyperglycemia) increased endothelial intercellular stresses and contractile forces compared to control. These results show that in addition to the molecular changes commonly seen in the vasculature after recurrent periods of hyperglycemia, there are also biomechanical changes occurring in the endothelial cells. Future studies are needed to determine if the biomechanical response of HUVECs can be recovered after a return to a euglycemic state.

Disclosure
S. Scheller: None. R. Steward: None.
476-P: Investigating C-Fiber Activation and Pain Sensitivity in Diabetic Sensorimotor Neuropathy with Transcutaneous Electrical Nerve Stimulation
Authors: ELDESOUKY OMAR , SEEBAUER LUKAS , RUKWIED ROMAN , CARR RICHARD , ROSHAN MANI , SULAJ ALBA , TSILINGIRIS DIMITRIOS , KOPF STEFAN , FLEMING THOMAS H. , SCHMELZ MARTIN , SZENDROEDI JULIA , KENDER ZOLTAN 
Published: June 2024

Introduction & Objective: We aimed to assess C-fiber excitability via transcutaneous-electrical nerve stimulation (TENS) in diabetic sensorimotor neuropathy (DSPN) and its association with epidermal innervation and quantitative sensory testing. Pain perception was evaluated in glucose-tolerant humans (n=14) and patients with type 2 diabetes: no-DSPN (n=15), possible-DSPN (n=21), probable-DSPN (n=19), and confirmed-DSPN (n=11). Subsequent analysis compared patients with positive (n=17) and negative symptoms (n=16).
Methods: Slow depolarizing transcutaneous currents of low-intensity with 4 Hz sinusoidal stimulation profile and single 500 ms half sine wave pulses were used to stimulate C-fibers. Pain perception quantified using (0-10)-Numeric-Rating-Scale, detection/pain thresholds and pain-change-dynamics were assessed.
Results: Confirmed-DSPN had diminished pain perception (1.72±0.50 vs 4.98±0.46), elevated detection (0.19±0.04 vs 0.05±0.01) and pain thresholds (0.28±0.04 vs 0.1±0.01) and reduced pain habituation compared to the control group. Elevated pain perception (pos:7.32±0.72 vs neg:3.81±0.98) and lowered detection/pain thresholds (pos:0.24±0.04 vs neg:0.13±0.03) were shown in the positive symptoms group compared to the negative symptoms group (p&lt;0.05). Over 50% of patients with DSPN experience elevated pain with electrical stimuli in regions with reduced heat pain sensitivity, while less than 6% show similar responses in areas with diminished mechanical pain sensitivity indicating axonal degeneration.
Conclusions: Our results suggest that DSPN proceeds via differential transductional disruption towards denervation. TENS results, influenced by positive symptoms, confirm C-fibers' role for the clinical burden of DSPN. TENS offers further insights into DSPN's natural course, aiding high-risk patient identification and guiding interventions.

Disclosure
O. Eldesouky: None. L. Seebauer: Other Relationship; Springer Medizin Verlag GmbH. R. Rukwied: None. R. Carr: None. M. Roshan: None. A. Sulaj: None. D. Tsilingiris: None. S. Kopf: Speaker's Bureau; Lilly Diabetes, Bayer Inc. T.H. Fleming: None. M. Schmelz: Consultant; Lilly GmbH, Merz Therapeutics, Bayer Inc., Medtronic GmbH. J. Szendroedi: None. Z. Kender: None.
487-P: In Vivo Vasculogenic Tissue Reprogramming and Rescue of Diabetic Ischemic Tissue
Authors: MOHANTY SUJIT K. , SINGH KANHAIYA , KUMAR MANISHEKHAR , VERMA SUMIT S. , ROY SASHWATI , SEN CHANDAN K. , GNYAWALI SURYA C. , YODER MERVIN C. 
Published: June 2024

Our recent work reported on the identification of the vasculogenic fibroblast (VF) that is capable of generating new blood vessels during tissue repair (Pal et al. Nat Com, 2023). While VF are physiologic and injury-inducible, inducible VF generation is blunted under conditions of diabetes. We report that such barrier may be overcome by the induction of fibroblast Etv2, Fli1 and Foxc2 (EFF) using tissue nanotransfection (TNT) technology (PMIDs: 28785092, 34837085, 35819852). To understand the mechanisms underlying VF function and significance, we developed EFFfl/fl COL1A2creER mice. In these mice, EFF regions in fibroblasts (COL1A2+ cells) are induced in response to tamoxifen. To gain insight into the significance of VF in vivo, hind limb ischemia (HLI) studies were performed. Significant overexpression of EFF was noted in laser capture dissected dermal fibroblast tissue elements of tamoxifen treated HLI mice (n=6, P &lt; 0.05). Tamoxifen treatment enhanced hindlimb perfusion, as determined by laser speckle perfusion imaging (Perimed Inc.), in HLI mice (n=7, P &lt; 0.05). This rescue was associated with increased abundance of COL1A2+VWF+ VF as compared to control (EFFfl/fl) (n=7, P&lt;0.05). These favorable rescue findings were reproduced in diabetic (db/db) mice subjected to HLI (n=7, P&lt;0.05).
In conclusion, vasculogenic reprogramming in vivo is capable rescuing ischemic tissue under both nondiabetic and diabetic conditions.

Disclosure
S.K. Mohanty: None. K. Singh: None. M. Kumar: None. S.S. Verma: None. S. Roy: None. C.K. Sen: Consultant; SouthWest Technologies. Board Member; VisopalExo. Consultant; Vomaris Inc. S.C. Gnyawali: None. M.C. Yoder: None.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (DK136814, DK128845, DK135447, DK125835); Department of Defense (W81XWH-21-1-0033, W81XWH-22-1-0146)
489-P: Vitamin D Deficiency's Role in Increasing Large-Fiber Neuropathy Risk in Elderly Type 2 Diabetics
Authors: FEI SIJIA , FAN JINGWEN , PAN QI 
Published: June 2024

Background: Previous research has linked Vitamin D deficiency (VDD) with diabetic peripheral neuropathy (DPN), yet the specific relationship between serum vitamin D levels and the extent of large and small fiber neuropathies in elderly patients with type 2 diabetes mellitus (T2DM) remains unclear.
Methods: In this single-center cross-sectional study, 257 elderly T2DM patients were enrolled. To achieve balance in age, sex, and duration of diabetes among study participants, propensity score matching was employed. VDD was identified with serum 25-hydroxyvitamin D (25(OH)D) concentrations below 20 ng/ml. Electromyograms were utilized to evaluate large nerve fiber lesions, while skin conductance measurements were used for assessing small nerve fiber lesions.
Results: In this study, DPN patients exhibited significantly lower serum 25(OH)D levels compared to non-DPN patients [15.05 vs. 18.4 ng/ml, P=0.018]. VDD was identified as an independent risk factor for DPN (odds ratio = 0.959, P = 0.049) in multivariate logistic regression analysis. Spearman's correlation showed that nerve latencies negatively correlated with vitamin D levels, while nerve velocities and amplitudes showed a positive correlation. The group with VDD had longer nerve latencies and motor-evoked potential latencies, yet no significant correlation was found between serum 25(OH)D levels and electrochemical skin conductance.
Conclusions: VDD is independently associated with a higher risk of DPN. VDD may promote the development of DPN by affecting large nerve fibers.
Keywords: diabetic peripheral neuropathy, elderly, propensity score matching, type 2 diabetes mellitus, vitamin D

Disclosure
S. Fei: None. J. Fan: None. Q. Pan: None.

Funding
National Natural Science Foundation of China (Grant No. 82270881)
49-PUB: Body Mass Index, Dietary Intake, Diet Quality, and Pubertal Status of a Cohort of Children with Clinical Partial Remission of Type 1 Diabetes
Authors: HUERTA-SAENZ LINA , VLIEM MCKAYLA , BENAVIDES-VASQUEZ JORGE A. , DENG ELEN , LUGONE CHELSEA , PETERSEN KRISTINA 
Published: June 2024

Objective: Some children with type 1 diabetes (T1D) develop a transient recovery phase of beta cell function after diagnosis, also called partial remission (PR). Our aim is to describe the body mass index (BMI), dietary intake/quality, and glycemic metrics of children with clinical PR of T1D one year after diagnosis and explore associations with pubertal stage.
Methods: Children aged 1-17 yo with T1D diagnosis ≥1 year, at least 1 positive T1D antibody, receiving care at the Penn State Pediatric Diabetes Clinic and with PR (defined by an insulin dose-adjusted HbA1C index [IDAA1C] ≤9 were included. Dietary intake was assessed by a single 24-hour recall (ASA24®). Diet quality was assessed by the Healthy Eating Index (HEI-2015). Data were reported as median ± interquartile ranges (IQR), frequencies and percentages. Comparisons by pubertal stage were performed using the Fisher’s exact and Wilcoxon rank-sum tests (p=0.05).
Results: We identified 21 remitters: 62% M, 10.9 ± 3.96 yo, 71% White, 57% pump users, and 90% private insurance. T1D duration= 29 ± 18 months, HbA1C= 6.06 ± 0.53%, blood glucose= 137.9 ± 19.56 mg/dL, IDAA1C= 8.06 ± 0.94, and 95% were on CGMs. BMI at diagnosis vs. enrollment= 18.63 ± 4.54 kg/m2 and 16.6 ± 2.92 kg/m2; and 62% were prepubertal at diagnosis. Most participants had healthier BMI at diagnosis vs. enrollment: 73.7% vs. 57.1% (p&lt;0.05). Dietary intake = 1792 ± 347.2 kcal; carbohydrates (CHO) = 40.1 ± 8.2%, fats 41.9 ± 8.05%, protein 17.7 ± 5.8%, CHO intake = 188.4 ± 59.5 g/day. HEI-2015 = 58 ± 12.6. Pre-pubertal participants had higher rates of overweight/obesity at enrollment than at diagnosis (p=0.0135).
Conclusion: Most remitters had lower BMI percentiles at diagnosis, but those who were pre-pubertal increased their BMI significantly during the course of the disease.

Disclosure
L. Huerta-Saenz: None. M. Vliem: None. J.A. Benavides-Vasquez: None. E. Deng: None. C. Lugone: Speaker's Bureau; Dexcom, Inc. Employee; Dexcom, Inc. Speaker's Bureau; Sanofi. K. Petersen: None.

Funding
The project described was partially supported by the National Center for Advancing Translational Sciences, Grant KL2 TR002015 to Pennsylvania State University - KL2 ESI award to Dr. Huerta-Saenz. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.