bluuebunny/crossref_metadata_2025_split huggingface dataset:
869-P: Using CGM as Feedback Tool in Diabetes Mellitus Patients Management: A Retrospective Real-World Evidence Study Conducted in India
Authors: SABHARWAL MUDIT , PALUKURI SRIVANI , DEKA SAURAV , CHANANA GARIMA , KUMAR ROHIT 
Published: June 2020

Introduction: Since many new diabetic medications are costly and often have side effects, quick feedback would allow for timely decisions. The current study present the role of CGM in titrate medication to achieve glycemic target of diabetes mellitus patients using 14 days CGM report (AGP).
Methodology: Retrospective AGP of 214 patients was collected from 2017 to 2019. Target glucose range was considered as 70-180 mg/dL, hypoglycemia was categorized as low (54-69 mg/dL) and very low (&lt;54 mg/dL) and hyperglycemia as high (180-250 mg/dL) and very high (&gt;250 mg/dL). The % of time a patient spent in above ranges was illustrated as time in target range (TIR), time below range (TBR), and time above range (TAR), respectively. The glycemic variability (GV) parameters included standard deviation (SD) and coefficient of variation (CV). Changes in diabetic medications were done, if required, after first week of CGM. Variation in TIR, TAR, TBR and CV were analyzed before (first week) and after medication (last week).
Results: Improvement was observed in mean glucose values and SD from 152.1 to 135.5 and 41.0 to 35.1 mg/dL, respectively, % of time in TIR from 57.9 to 64.5% and TAR from 25.9 to 16.9% (high: 16.9 to 12.6% and very high: 9.0 to 4.3%) from first to last week. However, % of time in hypoglycemia (TBR) was increased from 7.9 to 11.2% (low: 6.6 to 8.8% and very low: 1.3 to 2.4%). The patients count with high glycemic variability (CV &gt;36) was reduced from 27 to 21. The average eA1C was improved by 0.6 units (6.9 to 6.3).
Conclusion: The patients who were hyperglycemic were well controlled with medication, albeit with episodes of hypoglycemia during night-time. The treating clinicians can focus on these soft spots after first week instead of waiting long to intervene if they use CGM to titrate the medication. Thus, CGM can be instrumental in giving quick feedback in maintaining desired glycemic targets.

Disclosure
M. Sabharwal: None. S. Palukuri: None. S. Deka: None. G. Chanana: None. R. Kumar: None.
885-P: Evaluation of a Novel Continuous Glucose Monitoring System in Insulin-Treated Patients with Diabetes: A Pilot Study
Authors: TOMAH SHAHEEN , ELDIB AHMED H. , TASABEHJI MHD WAEL , BHATIA VIKAS , GARDNER HANNAH , HAMDY OSAMA 
Published: June 2020

Continuous glucose monitoring has been shown to be an effective tool in management of type 1 and type 2 diabetes. Non-invasive techniques may provide a convenient alternative to current invasive methods but their precision is lacking.
We evaluated the accuracy of “LabPatch”, a non-invasive continuous glucose monitoring system that uses micropipette technology to sip interstitial fluid in comparison to YSI® (laboratory reference glucose analyzer) and 2 glucose meters (Onetouch Verio® and Freestyle Lite®) in 30 insulin-treated patients with diabetes at multiple points over 6 hours. LabPatch glucose readings significantly correlated with those of YSI (R-square=0.23, p&lt;0.0001). Moreover, 85.69% of LabPatch glucose readings were within zones A and B of the Clarke Error Grid albeit B&gt;A. LabPatch had an absolute relative difference (ARD) of 35.5% compared with YSI indicating wide variation in glucose readings. For glucose values between 70-180 mg/dL, LabPatch readings were within +/-15% of YSI values with a lower one-sided 95 % confidence bound of 75.25%. Estimated average glucose value (eAGV) were the closest between LabPatch and YSI than between either of the 2 glucose meters and YSI. We conclude that first-generation LabPatch Precision technology has potential to identify glucose trends in situations that require close monitoring of diabetes over shorter intervals such as gestational diabetes, pre-pregnancy planning and patients preparing for elective surgery. Additionally, LabPatch has the potential to be used for diabetes screening due to its non-invasive nature. Larger sample size and more precision of manufacturing technology may make it a valid non-invasive and wireless glucose monitor.

Disclosure
S. Tomah: Stock/Shareholder; Self; Amarin Corporation. A.H. Eldib: None. M. Tasabehji: None. V. Bhatia: None. H. Gardner: None. O. Hamdy: Consultant; Self; Abbott, AstraZeneca, Merck & Co., Inc., Sanofi-Aventis. Research Support; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Healthimation, LLC.

Funding
Cambridge Medical Technologies, LLC
887-P: Development of the Noninvasive Diabetes Monitoring Method
Authors: AIHARA MASAKAZU , KUBOTA NAOTO , KADOWAKI TAKASHI 
Published: June 2020

Aims/Background: To prevent diabetic complications, strict glucose control and frequent monitoring of blood glucose levels with invasive methods are necessary. We considered monitoring of diabetes-related biomarkers in tears may be the possible methods for diabetes monitoring methods. Many studies about tear glucose levels have been reported and tear glucose levels correlate with blood glucose levels. This time, we focused on glycoalbumin (GA) levels, which reflect an average of blood glucose levels over the preceding 2 weeks, and studied the correlation between GA levels in blood and tears.
Methods: We recruited 100 diabetic subjects and collected blood and tear samples. GA levels in blood were measured by an enzymatic method, and GA levels in tears were measured by Liquid Chromatography/Mass Spectrometry (LC-MS/MS).
Results: The GA levels in tears of 99 out of 100 samples were appropriately measured by LC-MS/MS. GA levels in blood and tears were significantly correlated (P &lt; 0.001). Multiple regression analysis revealed that this correlation was maintained even after adjustment for age, gender, nephropathy stage, and obesity (P &lt; 0.001).
Conclusions: GA in tears was the first measured diabetes-related biomarker. GA levels in tears were strongly correlated with those in blood, considering various factors. As GA value is a ratio, GA levels in tears were not thought to be influenced by dilution or concentration of tears and showed strong correlation with those in blood. From the above, GA in tears could be a diabetes-related biomarker that can be measured noninvasively. In the future, we plan to optimize measurement conditions, develop measurement equipment and verify the effectiveness and usefulness of this diabetes monitoring method.

Disclosure
M. Aihara: None. N. Kubota: None. T. Kadowaki: Research Support; Self; Astellas Pharma Inc., Daiichi Sankyo, Mitsubishi Tanabe Pharma Corporation, MSD Corporation, Novartis Pharma K.K., Novo Nordisk Pharma Ltd., Ono Pharmaceutical Co., Ltd., Sanofi, Sumitomo Dainippon Pharma Co., Ltd., Takeda Pharmaceutical Company Limited. Speaker’s Bureau; Self; Abbott, Astellas Pharma Inc., AstraZeneca K.K., Boehringer Ingelheim Pharmaceuticals, Inc., Cosmic Corporation, Daiichi Sankyo, Eli Lilly Japan K.K., FUJIFILM, Kowa Company, Ltd., Kyowa Hakko Kirin Co., Ltd., Medscape Education, Medtronic, Mitsubishi Tanabe Pharma Corporation, MSD Corporation, NIPRO Medical Corporation, Novartis Pharma K.K., Novo Nordisk Pharma Ltd., Ono Pharmaceutical Co., Ltd., Sanofi, Sanwa Kagaku Kenkyusho, Sumitomo Dainippon Pharma Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Company Limited, Terumo Medical Corporation. Other Relationship; Self; Asahi Mutual Life Insurance.
888-P: Day vs. Nighttime Performance of Continuous Glucose Monitoring Systems in Children with Type 1 Diabetes during a Diabetes Summer Camp
Authors: RAMI-MERHAR BIRGIT , NAGL KATRIN , BERGER GABRIELE , SCHÜTZ ANNA , ABERER FELIX , MADER JULIA K. 
Published: June 2020

Continuous subcutaneous glucose monitoring (CGM) use is increasing in diabetes care. Still there are concerns with regard to sensor accuracy especially at night.
Aim of the Study: To assess accuracy of commonly used CGM systems at a 2 week diabetes camp in children with type 1 diabetes (T1D) ages 9-14 years.
Out of 38 children, 37 routinely wore a CGM system throughout the camp. Baseline characteristics: age 11.0 (9.9;12.1) years; 57% girls; HbA1c 7.2% (6.9; 7.7); diabetes duration 3.6 (2.7; 6.3) years (median (interquartile range)). Capillary glucose measurements were performed prior to main meals, at bedtime and whenever deemed necessary by medical staff after thoroughly cleaning the finger tips. Calibrations of Medtronic Enlite was performed twice daily when glycemia was stable. All concomitantly available data pairs were used for the analysis. Night-time was defined as period when children were supposed to be in bed (10 PM until 7 AM).
Sensor distribution: 51% Abbott Libre, 35% Medtronic Enlite, 14% Dexcom G6.
CGM accuracy shown in Table 1: MARD in % (interquartile range)).
Sensor performance of the adequately calibrated Medtronic system outperformed the factory-calibrated sensors in most situations. All sensors performed worse in hypoglycaemia. During the nights the MARD was higher, potentially due to pressure artefacts.

Disclosure
B. Rami-Merhar: Advisory Panel; Self; Abbott. Speaker’s Bureau; Self; Eli Lilly and Company, Medtronic. K. Nagl: None. G. Berger: None. A. Schütz: None. F. Aberer: None. J.K. Mader: Advisory Panel; Self; Becton, Dickinson and Company, Eli Lilly and Company, Medtronic, Prediktor Medical, Sanofi-Aventis. Speaker’s Bureau; Self; Abbott, Eli Lilly and Company, Medtronic, Novo Nordisk A/S, Roche Diabetes Care, Sanofi-Aventis.
889-P: Online Education Improves Clinical Knowledge/Competence Related to Use of Newer CGM Technologies and Standardized Reports
Authors: LARKIN AMY , LACOUTURE MICHAEL , LE ANNE 
Published: June 2020

Educational design included a “test, then teach” approach to elicit cognitive dissonance, with evidence-based feedback provided following each learner response. A repeated pairs pre-/post-assessment study design with 3 case-based questions and 1 confidence question was used. A chi-square test and Cramer’s V (&lt;0.05 no effect; 0.06-0.15 small effect, 0.16-0.30 medium effect, &gt;0.30 large effect) were used to measure educational impact. Data were collected from February 4, 2019 to March 4, 2019.In total, 84 ENDOs and 415 PCPs answered all pre-/post-assessment questions and were included in the analysis. In addition, 33% of ENDOs and 35% of PCPs reported increased confidence interpreting and using glucose data from an AGP report.
This study demonstrates the success of interactive, case-based education on improving interpretation and clinical application of data from an AGP report. Future education on this topic should focus on different patient case scenarios in cardiology in order to give cardiologists a chance to apply guidelines and data to various types of patients in real-world clinical scenarios.

Disclosure
A. Larkin: None. M. LaCouture: None. A. Le: None.

Funding
Abbott Diabetes Care
904-P: Therapeutic Decisions Based on Interval Analysis of Blood Glucose Curves of Ambulatory Glucose Profile Help Improving Blood Glucose and Glycemic Variability
Authors: MAKKAR BRIJ M. , SOOTA KIRTI , GUPTA VIPUL , SHARMA JUGAL K. , KHURANA GIRISH , CHAWLA RAJEEV , JAGGI SHALINI , THACKER HEMANT 
Published: June 2020

Background: India is a low-middle income country and cost constraints affect use of emerging technologies in diabetes management. Ambulatory Glucose Profile(AGP) using Libre-pro(Abbott) to assess 14 days ambulatory blood glucose(BG) levels and glucose variability(GV) is used sparingly due to cost concern. Many physicians use interval analysis based on AGP data retrieval at 5-7 days to modify treatment and also evaluate its impact on BG levels at 14 days. However, there is little or no published data on this.
Aim: To assess whether treatment modifications based on interval analysis of daily glucose curves during AGP can improve glucose levels and reduce glucose variability METHOD We analyzed records of 40 type 2 diabetes(T2D) patients(27 men, 13 women, age 17-78 years) who had undergone AGP using Libre-pro and in whom interval analysis of daily BG curves was performed at 7 days. In these patients data was retrieved and analyzed at 7th day during AGP and treatment was modified based 0-7day data. AGP was continued and complete data was retrieved at 14th day. Comparison was made for average BG and for time in-, above- and below target range, before and after the 7th day treatment modifications.
Results: Analysis of AGP records showed a significant reduction in 7-14 days mean BG levels after intervention at 7th day as compared to 0-7 days mean(152.11±35.29 vs. 173.23±46.4mg/dl, p=0.025). Time in target range increased from 32.33±22.51% to 41.82±21.67% but was not statistically significant(p=0.059). Time above target range decreased significantly from 62.78±25.54% to 50.85±25.86%(p=0.041) while change in time below target range was non-significant(4.97±6.91% vs. 6.62±7.66%, p=0.32).
Conclusion: Treatment decisions based on Interval analysis of AGP data are effective in significantly reducing blood glucose levels and glucose variability in type 2 diabetes patients. Time in range also increased but was statistically not significant.

Disclosure
B.M. Makkar: Advisory Panel; Self; Abbott, AstraZeneca, Biocon, Boehringer Ingelheim Pharmaceuticals, Inc., Eris Lifesciences, Novartis AG, Novo Nordisk Inc., Sanofi, USV Private Limited. Speaker’s Bureau; Self; Janssen Pharmaceuticals, Inc. K. Soota: None. V. Gupta: Advisory Panel; Self; Intas Pharmaceuticals Ltd., Sun Pharmaceutical Industries Ltd. J.K. Sharma: None. G. Khurana: None. R. Chawla: None. S. Jaggi: None. H. Thacker: None.
911-P: Independent Accuracy Verification of a Smartphone App’s Blood Glucose Prediction Algorithm
Authors: KRIVENTSOV STANISLAV , HAYERI AMIR 
Published: June 2020

Smartphone applications have become important health management tools for patients with diabetes. In particular, short-term blood glucose predictions offered by some apps can help reduce the frequency and duration of hypo- and hyperglycemic events, which makes the accuracy of such predictions essential for better glycemic control.
In this paper, we describe the results of an in-silico study designed to measure the predictive accuracy of the algorithm of our smartphone app. In this study, an FDA-approved blood glucose simulator was used by an independent third party to generate 180 days of realistic glycemic data for 300 virtual patients under 3 different study protocols. This data (about 225 million blood glucose points with accompanying food, insulin, and exercise information) was sent consecutively, one temporal point at a time to avoid the possibility of future data leakage, to our predictive module, which generated personalized predictions of blood glucose levels for the next 60 minutes and sent the results back to the third party to be used in accuracy metrics calculation. Several versions of the predictive algorithm were tested, including one using only CGM data, and another that also took into account recent food, insulin, and exercise events.
In the end, for CGM-only models trained on 20,000 prior blood glucose points from the same patient, 93.16% of 30-minute predictions and 79.54% of 60-minute predictions ended in Parkes Zone A (clinically accurate), and 99.71% of 30-minute predictions and 98.82% of 60-minute predictions in Parkes Zones A and B (clinically acceptable). For the models that used additional inputs, Parkes Zone A percentages improved to 98.67% of 30-minute predictions and 92.51% of 60-minute predictions, while Parkes Zones A and B percentages rose to 99.99% of 30-minute predictions and 99.72% of 60-minute predictions. For both models, the high degree of accuracy achieved in the study shows the usability of our approach for real-time glycemic predictions.

Disclosure
S. Kriventsov: Employee; Self; Bio Conscious Tech. A. Hayeri: Other Relationship; Self; Bio Conscious Technologies INC (DBA Diabits).
918-P: Effectiveness of Freestyle Libre Flash Glucose Monitoring System on the Diabetes Distress among Type 1 Diabetes: A Prospective Study
Authors: ALDAWISH MOHAMMED 
Published: June 2020

Aim: The purpose of this study was to investigate the intervention of flash glucose monitoring system (FGM) on the diabetes related distress among young type 1 diabetes.
Methods: A 12 weeks prospective study was carried out among 187 children and adolescents (aged 13-19 years, 56.7% female) with T1D, who used conventional finger-pricking method for self-testing the glucose. The trial was conducted between March 2019 and July 2019. For carrying out the study, the FGM sensors were placed on each participant, at the baseline visit, by a trained diabetes educator. In addition, a trained interviewer handed over the 28-item T1-Diabetes Distress Scale (T1-DDS) questionnaire to each patient, at the baseline and at 12 weeks of the study in order to collected Diabetes Distress (DD) score.
Results: In comparison to the baseline (finger pricks), the subdomains of DD such as: powerlessness (P = 0.0001), management distress (P = 0.0001), hypoglycemia distress (P = 0.0001), negative social perceptions (P = 0.0001), eating (P = 0.0001), physician distress (P = 0.0001), friend/family distress (P = 0.0001) and total T1-DDS score (P = 0.0001) were significantly decreased at 12 weeks after switching the patients from finger pricks to flash FGM. Similarly, after switching the patients to FGM, there were notable decrease were found on the clinical variable such as HbA1c at 12 weeks. After 12 weeks, we also observed significant decrease in hypoglycemia and interestingly, the frequency of glucose checking were increased among the FGM users.
Conclusion: the findings of this study evidently illustrated that after switching the patients from finger pricks to flash FGM, significant improvement were observed on DD related clinical parameters. However, further studies are required, for ascertaining whether the prolonged and consistent use of the FGM system will result in improved outcomes.

Disclosure
M. Aldawish: None.
92-LB: Linagliptin Improves CD34+ Progenitor Cells and Urine Exosomes
Authors: AWAL HASSAN , NANDULA SESHAGIRI RAO , KUNDU NABANITA , SEN SABYASACHI 
Published: June 2020

Introduction: Endothelial Progenitor cells (EPCs) has been shown to be dysfunctional in both type 2 diabetes and chronic kidney disease (CKD) leading to poor regeneration of endothelium. EPCs have been shown to be a robust cardiovascular disease (CVD) risk indicator. Cellular mechanisms of DPP-4 inhibitors such as Linagliptin (LG) on CVD risk in patients with type 2 diabetes with established CKD has not been established.
Hypothesis: Linagliptin, a DPP-4 inhibitor when added to insulin, metformin or both may improve endothelial dysfunction in a diabetic kidney disease (DKD)
Methods: 31 subjects taking metformin and/or Insulin were enrolled in this 12 weeks, double blind, randomized placebo matched trial, with 5 mg LG compared to placebo. Type 2 DM subjects (30-70 years old), A1c of 6.5-10%, CKD Stage 1-3 were included. CD34+ cell number, migratory function, gene expression along with vascular parameters such as Arterial stiffness, biochemistry, resting energy expenditure were measured. Data were collected at week 0, 6 and 12. A mixed model regression analysis was done with p value &lt;0.05 considered significant.
Results: A double positive CD34/CD184 cell count had a statistically significant increase (p&lt;0.02) as determined by flow cytometry in LG group where CD184 is SDF1a cell surface receptor. Though mRNA differences in CD34+ve was more pronounced CD34- cell mRNA analysis showed increase in antioxidants (SOD2, Catalase and CPX) and prominent endothelial markers (PECAM1, VEGF-A, vWF and NOS3). Arterial stiffness measures such as augmentation Index (AI) (p&lt;0.04) and pulse wave analysis (PWV) were improved (reduced in stiffness) in LG group. A reduction in LDL: HDL ratio was noted in treatment group (p &lt;0.04). Urinary exosome protein examining podocyte health (Podocalxyin, Wilms tumor and Nephrin) showed reduction or improvement.
Conclusions: In DKD subjects, Linagliptin promotes an increase in CXCR4 expression on CD34+ progenitor cells with a concomitant improvement in vascular and renal parameters at 12 weeks.

Disclosure
H. Awal: None. S. Nandula: None. N. Kundu: None. S. Sen: None.
921-P: Liraglutide Improves NAFLD in Patients with Type 2 Diabetes
Authors: BASU DEBASIS , CHAUDHURI SOUMYABRATA ROY , DEKA NILAKSHI 
Published: June 2020

Introduction: The present study was conducted to evaluate the effects of Liraglutide on NAFLD in patients with type 2 diabetes mellitus (T2DM) with elevated transaminases.
Methods: A total of 62 patients (male-38, female-24) with age group of 30-75 years, treated with Liraglutide 1.2 mg/1.8 mg OD were included in the study. Selected clinical and demographic profile were recorded for all patients at baseline and follow-up. The hepatic steatosis was assessed using liver elastography (Fibroscan).
Results: After a mean follow-up of 26 weeks, in 62 patients (meeting appropriate present inclusion criteria), there was significant reduction in weight from 88.63±8.6 kg (Mean ± SD) to 80.47±6.7 kg (p&lt;0.001), as computed by paired t-test. The Mc-Nemar’s test also demonstrated a significant higher proportion of patients with reversibility of stage of fibrosis from baseline to follow-up, p=0.003. This is accompanied by significant reduction in the AFRI score from a baseline median(IQR) of 1.84 (1.61-2.73) to 1.26(1.19-1.48) (p&lt;0.001), as computed by Wilcoxon signed rank test. At baseline, 6 had fibrosis stage 2, of which 4 regressed to stage 1 and 2 had no significant fibrosis at baseline; 24 had stage 3 fibrosis, of which 20 regressed to stage 2, 2 to stage 1 and 2 had no significant fibrosis at follow-up. Remaining 32 had stage 4 fibrosis, of which 12 had stage 3, 18 had stage 2 and only 2 had stage 1 fibrosis at follow-up. ALT and AST decreased from 47.65±4.65 to 24.31±5.43 and 29.67±2.21 to 17.65±4.59 respectively. There was also significant improvement in glycaemic control with reduction in HbA1c from 8.56 ± 0.56% to 7.21 ± 0.34%, p&lt;0.001 along with significant reduction in systolic blood pressure from 133.26±11.39 mmHg to 122.81±7.29 mmHg (p&lt;0.001) and diastolic blood pressure from 87.17±6.04 mmHg to 82.91±4.33 mmHg (p&lt;0.001).
Conclusion: Liraglutide significantly reduces hepatic fibrosis and effectively cause reversal of elevated transaminases along with weight loss and blood pressure reduction in addition to good glycaemic control.

Disclosure
D. Basu: None. S. Roy Chaudhuri: None. N. Deka: None.