bluuebunny/crossref_metadata_2025_split huggingface dataset:
87-LB: Glycemic Variability in People with Impaired Glucose Tolerance/Prediabetes
Authors: DOUGLAS KEVIN , ANNAMALAI NARAYAN , MOORE PATRICK J. , THOMSON SCOTT 
Published: June 2020

The use of continuous glucose monitoring has been suggested as a method of determining glucose control in prediabetes, including understanding glucose variability, which may be a risk factor in the progression to type 2 diabetes. This pilot research study aimed to determine glycemic variability (%CV) in people diagnosed with impaired glucose tolerance (IGT)/prediabetes. The study included people aged 18 or over, with their most recent HbA1c 5.7-6.4% (39-47 mmol/mol) recorded in medical notes in the last 12 months. Pregnant patients were excluded, as were patients with diabetes. A total of 43 participants (60.5% female) from 5 primary care sites in the UK enrolled in the 2-week single arm study, wearing a FreeStyle Libre Pro Flash Glucose Monitoring SystemTM (glucose data was not available to participants). On average, HbA1c was 6.06±0.25% (42.7±2.6 mmol/mol), age was 62.5±8.3 years, BMI was 32.1±6.6 kg/m2, average time since diagnosis was 18±19 months, average Q diabetes score was 28.4±23.7% (mean±SD). Glucose variability (%CV) was 17.3±3.8%, %CV was greater during daytime hours (06:00 to 23:00) than at night (23:00 to 06:00), 17.7±4.1% and 12.9±3.5% respectively (mean±SD). %CV was greater in those with BMI&lt;30 kg/m2 compared to those ≥30 kg/m2; 18.9±3.3% and 15.8±3.5% respectively (mean±SD). Mean glucose was 101.2±10.0 mg/dL, time in hyperglycemia (&gt;180 mg/dL, 10.0 mmol/L) was 0.09±0.23 hours per day (mean±SD). Ten anticipated sensor insertion site symptoms were experienced by five participants: erythema (n=2, well-defined redness), pain (n=1), bruising (n=1), itching (n=2), rash (n=2), bleeding (n=1) and other (n=1, ‘skin irritation’), all were mild in severity and resolved. This population, with prediabetes experienced glucose variability of 17.3% (%CV). This was greater during daytime hours and in those with lower BMI (&lt;30 kg/m2).

Disclosure
K. Douglas: None. N. Annamalai: None. P.J. Moore: None. S. Thomson: Research Support; Self; Abbott. Research Support; Spouse/Partner; Abbott.
87-OR: NF Kappa B Expression Is Related to Diabetes and Impaired Respiratory Capacity of Human Ventricular Myocardium
Authors: ZWECK ELRIC , SCHEIBER DANIEL , JELENIK TOMAS , HORN PATRICK , PESTA DOMINIK , LASSNER DIRK , SCHULTHEISS HEINZ-PETER , BOEKEN UDO , AKHYARI PAYAM , LICHTENBERG ARTUR , KELM MALTE , RODEN MICHAEL , WESTENFELD RALF , SZENDROEDI JULIA 
Published: June 2020

Nuclear factor kappa-B (NFkB) has been postulated to induce cardiac fibrosis and dysfunction in heart failure and triggers inflammatory pathways. NFkB can be induced by damaged mitochondria. Its association with myocardial mitochondrial respiratory function in non-ischemic diabetes-related heart failure in humans is yet unclear. We hypothesized that human ventricular myocardial NFkB expression (i) is increased by type 2 diabetes mellitus (T2DM), and (ii) relates to reduced myocardial mitochondrial respiration. Heart transplant recipients with or without T2DM (as determined by oral glucose tolerance test), about to undergo post-transplant surveillance endomyocardial biopsies, were included, if they had received hearts from donors without T2DM. Thus, time since transplantation equaled diabetes-exposure of the transplanted hearts (2.9±2.4 years). We assessed normalized NFkB p105 subunit (NFkB1) mRNA expression using real-time PCR and myocardial mitochondrial respiration using high-resolution respirometry. Study participants (T2DM: n=17, Non-DM: n=32) had no histological signs of allograft rejection, heart failure (left ventricular ejection fraction 66.2±6.5%) or coronary artery disease. Age and sex distribution were similar between Non-DM and T2DM (p=0.50; p=0.40, respectively). Myocardial NFkB1 expression was 60% higher in T2DM than in Non-DM (0.28 [0.21-0.44] vs. 0.45 [0.29-0.71] arbitrary units, p&lt;0.05). Fasting blood glucose, but not fasting free fatty acids (p=0.55), related to myocardial NFkB1 mRNA expression (r=0.31; p&lt;0.05). NFkB1 expression related inversely to state 3 respiration of fatty acids and glutamate (r=-0.33; p&lt;0.05), suggesting impaired complex I-related respiration. Our findings support the concept of a key role of NFkB in diabetes-related heart failure via altered myocardial respiratory function in humans. NFkB1 might therefore serve as a future target for treating diabetes-related heart disease.

Disclosure
E. Zweck: None. D. Scheiber: None. T. Jelenik: Employee; Self; Boehringer Ingelheim Pharmaceuticals, Inc. P. Horn: None. D. Pesta: None. D. Lassner: None. H. Schultheiss: None. U. Boeken: None. P. AKhyari: None. A. Lichtenberg: None. M. Kelm: None. M. Roden: Advisory Panel; Self; Servier. Board Member; Self; Poxel SA. Consultant; Self; Eli Lilly and Company, Gilead Sciences, Inc., ProSciento, TARGET PharmaSolutions. Research Support; Self; Boehringer Ingelheim International GmbH, Novartis Pharma K.K., Sanofi US. Speaker’s Bureau; Self; Novo Nordisk A/S. R. Westenfeld: None. J. Szendroedi: None.

Funding
German Research Council (SFB1116); Heinrich-Heine University
872-P: Improved HbA1c Estimation Using CGM Data
Authors: GROSSMAN JOSHUA , WARD ANDREW T. , MAAHS DAVID M. , PRAHALAD PRIYA , SCHEINKER DAVID 
Published: June 2020

The Glucose Management Indicator (GMI) is the accepted method to estimate HbA1c from mean CGM glucose. We hypothesize that HbA1c estimation could be improved with machine learning (ML) methods that account for additional covariates.
CGM, HbA1c, and demographic data were aggregated from five studies (3,550 HbA1c measurements, 1,095 participants). For each HbA1c, the following statistics were derived from all CGM data recorded up to 30 days before and 5 days after measuring HbA1c: mean, SD, CV, and % time in various ranges. Using HbA1c as the outcome and all CGM glucose statistics and demographics as covariates, the ML models LASSO, LASSO with all two-way interactions, and random forest were tuned via 5-fold cross validation (CV). Top performing models were compared to GMI via 5-fold CV and the paired Wilcoxon signed-rank test.
Random forest performed best, with 20% lower estimation error than GMI (p &lt; 0.001). After restricting HbA1c measurements to those for which an additional HbA1c had been measured for the same patient at least 70 days prior (1,833 HbA1c measurements, 755 participants), the models were re-trained with prior HbA1c as a covariate. LASSO performed best, with 27% lower estimation error than GMI (p &lt; 0.001). An ordinary least squares (OLS) model accounting for mean glucose, race, and prior HbA1c had an estimation error only 0.3% higher than LASSO, suggesting that augmenting GMI with just two additional covariates could substantially improve estimation.

Disclosure
J. Grossman: None. A.T. Ward: None. D.M. Maahs: Advisory Panel; Self; Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S. Consultant; Self; Abbott, Sanofi. Research Support; Self; Bigfoot Biomedical, Dexcom, Inc., Roche Diabetes Care, Tandem Diabetes Care. P. Prahalad: None. D. Scheinker: None.
876-P: Accuracy of Continuous Glucose Monitoring Compared with Capillary Blood and Venous Plasma Glucose Measurements in Medical Intensive Care Unit Patients
Authors: TINGSARAT WANNITA , LAICHUTHAI NITCHAKARN , BOONCHAYA-ANANT PATCHAYA , BURANASUPKAJORN PATINUT , KHOVIDHUNKIT WEERAPAN 
Published: June 2020

Objective: To assess the accuracy of the subcutaneous continuous glucose monitoring (CGM) sensor by comparing to the capillary blood glucose (CBG) and venous plasma glucose (VPG) measurements in the medical intensive care unit (MICU) patients.
Subjects and Methods: In a prospective study in patients in the MICUs, Medtronic Enlite sensor was inserted in the abdominal area. Paired sensor glucose readings with reference glucose values (CBG and VPG) were collected from MICU patients receiving intravenous insulin infusion therapy. The accuracy was assessed using the mean absolute relative difference (MARD), surveillance error grid (SEG) analysis and modified Bland-Altman plot.
Results: Twelve patients completed the study (age 69.3 ± 11.6 years; BMI 21.6 ± 2.9 kg/m2; APACHE II score 21.8 ± 6.3 and duration of CGM use 108.7 ± 41.1 hours). A total of 353 paired CGM and CBG glucose readings and 125 paired CGM and VPG readings were included in the analysis. Using CBG as the reference, MARD was 7.2%. The modified Bland-Altman plot showed 95% of the limit of agreement (LoA) was -18.4% to 19.2%. The SEG analysis showed that 100% of paired glucose values were within zones A or B. No clinically significant difference in the accuracy was seen between subgroups of vasopressor use (MARD 6.1% in the vasopressor group vs. 6.8% in the non-vasopressor group, p = NS). Using VPG as the reference, the MARD was 8.8%. The modified Bland-Altman plot showed 95% LoA of - 22.6% to 28.2%. The SEG analysis showed 95.2% of glucose readings were within zones A or B.
Conclusion: The accuracy of the subcutaneous CGM sensor in MICU patients was comparable to that observed in non-critical care settings, with no device-related adverse events. The sensor accuracy remained within the similar range when using VPG as the references compared to using CBG as the references. No differences in terms of accuracy between the vasopressor and non-vasopressor groups were found in this study.

Disclosure
N. Laichuthai: None. P. Buranasupkajorn: None. W. Khovidhunkit: Speaker’s Bureau; Self; Amgen, AstraZeneca.

Funding
Quality Improvement Fund; King Chulalongkorn Memorial Hospital; Thai Red Cross Society (1-62-30101-A-11)
878-P: Real-World Data from U.S. Patients Using a Long-Term Implantable Continuous Glucose Monitoring (CGM) System: Age Effect on Glycemic Control
Authors: TWEDEN KATHERINE , GHOSH-DASTIDAR SAMANWOY , DEHENNIS ANDREW D. , KAUFMAN FRANCINE 
Published: June 2020

Background: Data from the first ∼200 adult real-world U.S. users of the implantable 90-day fluorescence-based glucose sensor, Eversense CGM System, showed 62.3% time in range (TIR, glucose 70-180mg/dL) and 4.1% time &lt;70mg/dL. This report describes CGM data by age in a large cohort (&gt;1600) of users with Eversense.
Methods: Sensor glucose (SG) data were analyzed for users who reached a 90-day wear period. Mean SG, variability measures (SD, CV), glucose management indicator (GMI), and CGM metrics for 18-24.9, 25-44.9, 45-64.9, ≥65 years of age subgroups were computed. Transmitter wear time was calculated in users with at least 30 wear days.
Results: We evaluated 1656 users (997 with T1D, 261 with T2D, 408 unreported). Percent time in range (TIR), time below ranges (&lt;70 mg/dL and &lt;54 mg/dL), and time above ranges (&gt;180 mg/dL and &gt;250 mg/dL) improved with age, with 52.6% and 69.0% TIR in the youngest and oldest groups, respectively (Table). Transmitter wear time was 82% overall and improved to 87% in those ≥65 years. Percent users achieving goals for targets also improved with age.
Conclusion: Glycemic outcomes improved with age in a large cohort using the implantable Eversense CGM System. Younger adults had favorable outcomes compared to data from the T1D Exchange. Overall, these data suggest that the implanted Eversense CGM system is a valuable tool for management of diabetes.

Disclosure
K. Tweden: Employee; Self; Senseonics. S. Ghosh-Dastidar: Employee; Self; Senseonics. A.D. Dehennis: Employee; Self; Senseonics. F. Kaufman: Advisory Panel; Self; Virta Health Corp. Employee; Self; Senseonics. Stock/Shareholder; Self; Medtronic.
881-P: Remission through Early Monitored Insulin Therapy: Duration Month
Authors: SOBEL SANDRA I. , RUPPERT KRISTINE , MCCARTHY PATRICK M. , SIMINERIO LINDA M. , ROMETO DAVID A. 
Published: June 2020

Background: Studies show titrating insulin in the hospital for 2-4 weeks at diagnosis of type 2 diabetes mellitus (T2DM) can restore production of endogenous insulin to achieve remission. The purpose of the Remission through Early Monitored Insulin Therapy- Duration Month (REMIT-DM) pilot study was to evaluate if individuals with T2DM in an outpatient setting could self-titrate insulin with an innovative titration algorithm using glucose values and trends from a real-time continuous glucose monitor (CGM).
Methods: A diabetes educator trained 10 insulin naïve T2DM participants on use of a basal-bolus multiple daily insulin injection algorithm designed to achieve euglycemia (fasting glucose (FG) &lt; 100 mg/dL, 2-hour (2h) post-prandial glucose (PPG) &lt; 120 mg/dL) during 4 weeks of insulin therapy based on Dexcom G6 real-time CGM values and trends. Primary outcome was participant ability to do algorithm titrations using CGM readings. Secondary outcomes included achievement of goal FG and 2h-PPG, time in days to achievement of goals, CGM time in range (TIR), patient distress via the PAID-5 scale prior to and at completion of the 4-week intervention, and assessment of satisfaction with REMIT-DM experience.
Results: Nine of 10 participants were able to use the self-titration algorithm while 7 achieved goal FG and 8 goal 2h-PPG over 4 weeks of insulin therapy. Mean time to FG and 2h-PPG goals were 9.75 ± 6.01 and 7.11 ± 4.64 days, respectively. Mean CGM TIR during insulin therapy was 80.67 ± 10.7%. Mean PAID-5 scores pre-post use of titration protocol was 8.9 and 7.6, respectively. Scores &gt;8 indicate possible diabetes-related distress. All reported high satisfaction with experience.
Conclusions: Insulin naïve patients were able to follow and self-titrate insulin using real-time CGM values and trends according to an innovative remission insulin algorithm in an outpatient setting. DM-related distress was reduced while all reported satisfaction. Insulin titration at diagnosis warrants further exploration.

Disclosure
S.I. Sobel: None. K. Ruppert: None. P.M. McCarthy: None. L.M. Siminerio: Research Support; Self; Becton, Dickinson and Company. D.A. Rometo: None.

Funding
University of Pittsburgh Clinical and Translational Science Institute
883-P: Utility of CGM Technology in the Inpatient Setting
Authors: ALOI JOSEPH A. , PRICE CATHERINE E. 
Published: June 2020

Effective inpatient insulin management is an important safety issue for our patients. Barriers to appropriate insulin use include incorrect timing of prandial insulin administration, failure to administer basal insulin to persons with type 1 DM, and insulin dosage overtreatment resulting in severe hypoglycemia. We studied the use of Abbott professional (blinded) Libre sensor in patients either on basal bolus insulin therapy (n=20) or on IV insulin (n=20) as a potential aide in minimizing insulin errors. The Wake Forest Baptist Health IRB approved the study and all subjects studied signed informed consent. Continuous BG data were aggregated for each subject and compared to point of care blood glucose (BG), iStat, or lab chemistry values. BG results were assessed for comparability (CGM versus Standard BG testing) and in ability to detect hypoglycemia early in those subjects experiencing hypoglycemia.
Analysis of the basal bolus insulin arm revealed that an average difference of standard of care versus CGM glucose reading of 44.80 mg/dL. Differences in basal bolus arm BG comparing 24-hour average CGM glucometric data to standard of care was similar at 43.56 mg/dL. One third of participants in the basal bolus arm had at least one episode of hypoglycemia (BG &lt; 70 mg/dL.) The average BG value in those experiencing a hypoglycemic event in our study group was 59 mg/dL on Standard BG testing. In retrospective review, all episodes of hypoglycemia were detected earlier on CGM technology. In one occurrence, hypoglycemia noted 6 hours sooner on CGM. CGM data consistently shows lower BG values than those using standard methods. Additional data including difference in insulin dosing based on CGM vs. Standard BG testing following completion of the IV insulin arm will be discussed.

Disclosure
J.A. Aloi: Consultant; Self; Medtronic. Research Support; Self; Medtronic. C.E. Price: None.

Funding
Wake Forest Baptist Medical Center
886-P: Saliva 1,5-Anhydroglucitol Detected by Liquid Chromatography-Mass Spectrometry Is a New Marker for Diabetes Screening
Authors: BAO YUQIAN , JIAN CHAOHUI , ZHAO AIHUA , MA XIAOJING , GE KUN , LU WEI , ZHU WEI , WANG YUFEI , ZHOU JIAN , JIA WEI 
Published: June 2020

Context: Unlike other commonly used invasive blood glucose monitoring methods, saliva detection prevents patients from suffering the physical uneasiness. Serum 1,5-anhydroglucitol (1,5-AG) is a new indicator for assessing short-term glycemic control. However, there are currently few studies on saliva 1,5-AG in diabetes mellitus (DM).
Objective: This study aimed to evaluate the effectiveness of saliva 1,5-AG in diabetes screening in a Chinese population.
Design and Participants: A total of 641 subjects without a valid diabetic history (251 men and 390 women) were recruited from September 2018 to June 2019 and underwent an oral glucose tolerance test (OGTT). Fasting saliva 1,5-AG (1,5-AG0) and postload 2-hour saliva 1,5-AG (1,5-AG120) were measured with liquid chromatography-mass spectrometry. Serum 1,5-AG0 and 1,5-AG120 were measured with enzymatic method.
Results: Saliva 1,5-AG levels in DM subjects were lower than those in nondiabetes mellitus subjects (both P &lt; 0.05). Saliva 1,5-AG was positively correlated with serum 1,5-AG and negatively correlated with blood glucose and glycated hemoglobin (HbA1c) (all P &lt; 0.05). The optimal cutoff points of saliva 1,5-AG0 and 1,5-AG120 for diabetes screening were 0.436 μg/mL and 0.438 μg/mL, respectively. Fasting plasma glucose (FPG) combined with saliva 1,5-AG0 and HbA1c combined with saliva 1,5-AG120 reduced the proportion of people who required an OGTT by 47.22% and 51.41% compared with FPG alone and HbA1c combined with FPG, respectively.
Conclusion: The optimal cutoff point of saliva 1,5-AG for diabetes screening was 0.44 μg/mL. Saliva 1,5-AG combined with FPG or HbA1c improved the efficiency of diabetes screening. Saliva 1,5-AG is robust in nonfasting measurements and a noninvasive and convenient tool for diabetes screening.

Disclosure
Y. Bao: None. C. Jian: None. A. Zhao: None. X. Ma: None. K. Ge: None. W. Lu: None. W. Zhu: None. Y. Wang: None. J. Zhou: None. W. Jia: None.
895-P: Improved Glycemic Control with Insulin Glargine 300 U/mL vs. Glargine 100 U/mL in Type 1 Diabetes
Authors: PAOLA LUCIDI , CIOLI PATRIZIA , CANDELORO PAOLA , ANDREOLI ANNA MARINELLI , BOLLI GEREMIA B. , FANELLI CARMINE G. , PORCELLATI FRANCESCA 
Published: June 2020

PK/PD of clinical doses of Glargine 300 U/mL (Gla-300) and Gla-100 differ (Diabetes Care 2019;42:85), but any clinical relevance has been difficult to demonstrate.
Aim: to demonstrate that PK/PD differences of individual doses of Gla-300 vs. Gla-100 translate into clinical benefits in T1DM, as shown by interstitial glucose (IG) (CGM).
Methods: 18 persons with T1DM (age 40±12 yrs, diabetes duration 26±12 yrs, A1C 7.2±0.5 %, 55±6 mmol/mol) were randomized to Gla-300 or Gla-100 titrated for 3 months, followed by 2 month washout, and alternate treatment for 3 more months. Titrated mealtime rapid-acting insulin analogs were continued with both Gla-300 and Gla-100. Blinded CGM (iPro, Medtronic) was used during last 2 weeks of each 3-month treatment period.
Results: After 3 months, A1C was no different with Gla-300 vs. Gla-100 (both 6.9±0.5 %, 52±6 mmol/mol). CGM revealed lower 24 h IG (Figure); % time in range (70-180 mg/dl) was higher (82±8 vs. 72±10), whereas % time above range (&gt;180 mg/dl, 16±7 vs. 24±8), % time below range (particularly from midnight to pre-breakfast) (&lt;70 mg/dl, 2±3 vs. 4±4) and IG nocturnal variability (% CV 25±7 vs. 37±12) were lower with Gla-300 vs. Gla-100 (p&lt;0.05). Dose was higher with Gla-300 (0.35±0.08 U/kg) vs. Gla-100 (0.28±0.07 U/kg).
Conclusions: Titrated Gla-300 improves glucose control, reduces variability and hypoglycemia risk vs. Gla-100, as predicted from PK/PD differences of individual doses.

Disclosure
L. Paola: None. P. Cioli: None. P. Candeloro: None. A. Marinelli Andreoli: None. G.B. Bolli: Consultant; Self; Sanofi. C.G. Fanelli: Advisory Panel; Self; Eli Lilly and Company, Sanofi. F. Porcellati: None.

Funding
Sanofi
910-P: Relationship between Continuous Glucose Monitoring Metrics and Oxidative Stress in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study
Authors: KOHATA YO , OHARA MAKOTO , FUJIKAWA TOMOKI , NAGAIKE HIROE , KUSHIMA HIDEKI , HIROMURA MUNENORI , TERASAKI MICHISHIGE , MORI YUSAKU , FUKUI TOMOYASU , HIRANO TSUTOMU , YAMAGISHI SHO-ICHI 
Published: June 2020

Aims: Standardized continuous glucose monitoring (CGM) metrics for clinical care were announced in 2019. There have been no reports, however, on the relationship between standardized CGM metrics and oxidative stress. We therefore decided to investigate the relationships between standardized CGM metrics, classical glycemic variability, and oxidative stress.
Methods: This study was a cross-sectional analysis of 117 patients with type 2 diabetes mellitus (T2DM). Oxidative stress was estimated using the diacron-reactive oxygen metabolites (d-ROMs) test. The following parameters were used as CGM metrics: mean glucose level (MGL), percentage coefficient of variation for glucose (%CV), time above range (TAR), time in range (TIR), time below range (TBR), standard deviation (SD), and mean amplitude of glycemic excursions (MAGE), a classic index.
Results: A total of 117 patients (mean age of 64.1 ± 12.6 years, mean disease duration of 13.1 ± 11.5 years, and HbA1c of 8.3 ± 1.5%) who met the study inclusion criteria were finally analyzed. The univariate analysis showed that age, triglyceride, HbA1c, MGL, %CV, SD, MAGE, and TAR were significantly correlated with d-ROMs. Further, a stepwise multiple regression analysis identified SD, MAGE, and sex as independent contributors to d-ROMs.
Conclusions: Oxidative stress was associated with the SD and MAGE, two parameters affected by the mean glucose level, as CGM metrics in patients with T2DM.

Disclosure
Y. Kohata: None. M. Ohara: None. T. Fujikawa: None. H. Nagaike: None. H. Kushima: None. M. Hiromura: None. Y. Mori: Research Support; Self; Taisho Pharmaceutical Co., Ltd. T. Fukui: None. T. Hirano: None. S. Yamagishi: None.