bluuebunny/crossref_metadata_2025_split huggingface dataset:
901-P: Evaluation of the Analytical Performance of YSI 2900D Compared with YSI 2300 STAT Plus for Glucose Concentration Measurements
Authors: HERNANDEZ MOISES , BEYSEN CARINE , HOMPESCH MARCUS , MORROW LINDA 
Published: June 2020

Background: The production of YSI 2300 STAT (YSI 2300), a widely used Class II in-vitro diagnostics medical device for calibrating blood glucose monitoring systems, has been discontinued and replaced by new generation analyzers such as the YSI 2900D Biochemistry Analyzer (YSI 2900). The aim of this study was to evaluate the analytical performance of the YSI 2900D (YSI 2900) laboratory instrument using the validated YSI 2300 STAT Plus™ (YSI 2300) medical device as the reference method.
Methods: Serum controls (YSI and NIST SRM 965b) and blood and plasma samples were used to assess precision, accuracy (bias) and linearity of both analyzers for glucose concentration measurements. Human blood (n= 4 subject) was collected to prepare blood and plasma samples with low (1-70 mg/dL), mid (70-125 mg/dL) and high (125-900 mg/dL) glucose concentrations. Both analyzers employed a glucose oxidase amperometric biosensor and were configured with the same parameters. Daily membrane integrity and linearity checks were performed prior to conducting sample analyses. Results: Both instruments passed the daily performance checks prior to sample analyses. The YSI 2900 analyzer demonstrated similar within-run precision as the YSI 2300 (CV &lt; 2% for each analyzer and each serum control tested). A total of 80 blood samples (range: 3.7-766.3 mg/dL) and 80 plasma samples (range: 4.7-880.7 mg/dL) were analyzed in triplicate on both analyzers. Paired results from the YSI 2900 and YSI 2300 showed a high correlation coefficient (R2 &gt; 0.99) and similar regression statistics for both blood and plasma samples. Both the YSI 2900 and the YSI 2300 analyzers met accuracy (bias) criteria and Clarke error grid analysis demonstrated clinical accuracy with 100% of blood and 100% of plasma results in zone A.
Conclusion: Results from this study demonstrates that the YSI 2900 analyzer is analytically comparable to the YSI 2300 for a wide range of blood and plasma glucose concentrations.

Disclosure
M. Hernandez: None. C. Beysen: Employee; Self; ProSciento. M. Hompesch: Board Member; Self; ProSciento. Employee; Self; ProSciento. Stock/Shareholder; Self; ProSciento. L. Morrow: Employee; Spouse/Partner; Lilly Diabetes. Employee; Self; ProSciento.

Funding
YSI
909-P: The Related Factors Accounting for the Discrepancy between Estimated Hemoglobin A1c Derived from CGMS and the Measured A1C in Patients with Type 2 Diabetes
Authors: LIN BEISI , XU WEN , LIU ZHIGU , YANG DAIZHI , SU YANNA , CHEN YALAN , YAN JINHUA , YAO BIN 
Published: June 2020

Objective: Continuous glucose monitoring system (CGMS) is emerging as an important tool in management of diabetes. Estimated glycated hemoglobin (eA1c), a CGM-derived metric, can be widely used if it is highly matched with the measured glycated hemoglobin (A1c). This study aimed to evaluate the relationship between eA1c and A1c measured by high performance liquid chromatography.
Methods: Data were collected from T2D patients between July 2017 and December 2019. Patients with abnormal hemoglobin levels and acute diabetic complications were excluded. Enrolled patients were divided into 3 groups based on the difference of eA1c and A1c (ΔA1c=eA1c-A1c): matched group (ΔA1c from -0.099% to 0.099%), overestimated group (ΔA1c ≥ +0.1%), and underestimated group (ΔA1c ≤ -0.1%). The indices of glycemic variability (GV) were obtained from CGMS.
Results: The 102 enrolled patients were 55.9(12.1) [mean (SD)] years old, with the measured A1c of 6.89(1.25)% and eA1c of 6.20(0.65)%. A positive correlation between eA1c and measured A1c (r= 0.50, p&lt;0.001) was found. Majority of the patients were allocated in the underestimated group (13.7%, 19.6% and 66.7% of the patients in the matched, overestimated and underestimated groups, respectively). ΔA1c was -0.027(0.06)%, 0.59(0.39)% and -1.20(1.03)% (p&lt;0.001) in these 3 groups, respectively. Age, BMI, duration of disease, type of hypoglycemic therapy, duration and intensity of hypoglycemia, blood pressure, lipid profiles, and the indices of intra-day GV among the 3 groups were similar. Multivariate logistic regression analysis revealed that gender (β=7.99, p=0.01), hematocrit (β=4.28, p=0.01) and mean of daily differences (MODD) (β=-7.44, p=0.02) were independently related with ΔA1c.
Conclusions: eA1c was generally underestimated compared to measured A1c in T2D patients. Gender, hematocrit and MODD were identified as significant factors accounting for this discrepancy.

Disclosure
B. Lin: None. W. Xu: None. Z. Liu: None. D. Yang: None. Y. Su: None. Y. Chen: None. J. Yan: None. B. Yao: None.

Funding
National Key Research and Development Program of China (2016YFC1304801)
912-P: Two Novel Pharmacokinetic Parameters Assess Dietary Glucose Concentration Changes in a Diabetic Patient Using Freestyle Libre Continuous Glucose Monitoring (CGM)
Authors: MELISH JOHN S. 
Published: June 2020

Background: CGM is used to monitor/assess diet related glucose excursions and suggest treatment changes in types 1 and 2 diabetes. Two CGM data derived parameters, timed glucose clearance (GLCL(T,I) and timed insulin sensitivity index Si(T,I) are developed to quantify treatment responses to food, medication, and activity.
Method: Glucose Clearance (GLCL) = Interstitial fluid volume (Vd)/time of the (t1) rise and return to baseline (t2) of the diet related glucose concentration curve. GLCL(T,I) indicates the time = T between insulin administration (t0) to the initial glucose concentration rise from baseline (t1). I = insulin dose. The Si(T,I) = GLCL(T,I)/rapid acting insulin dose administered. Vd = 0.15 * kg body weight * 10 expressed as deciliters (dL).
Result: Example #1 - Two similar breakfasts: oatmeal (1 cup), 6 strawberries, ½ cup blueberries and ½ cup cottage cheese (46 g CHO) ingested on two different occasions. Vd = 116 dL. Breakfast (A): T = 0 minutes, glucose curve duration = 180 min, I = 13 units, GLCL(0,13) = 64.4 ml/min and SI(0,13) = 5.0 mL/(min*unit). Breakfast (B): T = 45 min; curve duration = 90/min; I = 12 units, GLCL(45,12) = 129 mL/minute and SI(45,12) = 10.8 mL/(minute*unit).
Example #2 - Lunch: madras lentils and hot dog. T = 0 minutes, I = 14 units. Glucose curve duration = 270 min. GLCL(T,I) = 43 mL/min; Si(T,I) = 3.07 mL/(min*unit).
Conclusion: Two quantitative parameters assessed similar meals and showed marked differences in duration and height of the glucose concentration curves. They illustrate the importance of insulin injection timing and dosing. The calculations are also applied to a meal without carbohydrate (CHO) counting and can be compared with a comparable subsequent meal. The calculations do not depend on CHO counting and can be applied to Identical mixed meals. Straightforward calculations are applied retrospectively to CGM generated data beyond current more qualitative CGM data evaluations.

Disclosure
J.S. Melish: None.
916-P: Precision Evaluation of Clinical Laboratory Glucose Reference Systems
Authors: PHILLIPS STUART , SETFORD STEVEN J. , SHEARER DAVID M. , SMITH ANTONY , ROSS JONATHAN N. 
Published: June 2020

Background: In response to the discontinuation of the industry standard YSI 2300 STAT PLUS glucose analyser Lifescan, as a major manufacturer of blood glucose measurement systems, initiated a comparative evaluation of currently marketed point of care (POC) glucose measurement devices to identify a potential replacement comparator system within a clinical environment.
Method: Four POC devices were selected for in-depth assessment. Glucose measurement precision is a key performance metric for a comparator device, with higher standard deviation and coefficient of variation values imparting greater measurement uncertainty to diabetes test systems. This laboratory assessment used venous whole blood samples collected in Lithium Heparin coated tubes and tested within 12 hours of blood draw. All potential sources of variation such as donor and operator were controlled to give a best-case indication of performance.
Results: Precision data were generated for the YSI 2300 STAT PLUS and four POC devices. 20 replicates were obtained per device at each of four glucose concentrations (50, 100, 200 and 500 mg/dL). The Abbott i-STAT Alinity (using CG8+ cartridge) demonstrated consistently lower standard deviation and coefficient of variation values when compared to the YSI 2300 STAT PLUS and other tests systems.
Conclusions: A comparison of four currently marketed POC devices indicated that only one demonstrates precision performance that is equivalent or better than the YSI 2300 STAT PLUS across a wide range of glucose concentrations and thus is a strong candidate as a replacement clinical comparator system.

Disclosure
S. Phillips: Employee; Self; LifeScan, Inc. Employee; Spouse/Partner; LifeScan, Inc. S.J. Setford: Employee; Self; LifeScan Scotland. D.M. Shearer: None. A. Smith: Employee; Self; LifeScan, Inc. J.N. Ross: Employee; Self; LifeScan, Inc.
920-P: Continuous Glucose Monitor Utilization and Adherence in Children with Type 1 Diabetes
Authors: MONTGOMERY EMILY L. , JAWAD KAHIR S. , EUBANKS STEPHANY , WINTERGERST KUPPER A. , RUSH HEATHER M. , WATSON SARA 
Published: June 2020

Use of continuous glucose monitors (CGM) is associated with lower HbA1c, with the best effect seen for those using the sensor at least 6 of 7 days. Prior studies have shown youth with type 1 diabetes to have poor adherence to CGM use. We aim to evaluate CGM adherence during typical use in our patients with type 1 diabetes.
In this retrospective chart review, the medical records for all patients treated with type 1 diabetes mellitus at the University of Louisville Physicians Pediatric Endocrinology outpatient clinic who initiated CGM use between 2017-2019 were reviewed to determine CGM utilization. CGM use data for patients, ages 2-18 years, was extracted from downloads performed at each clinic visit. Data available for review was 14 or 30 days, determined by receiver type.
During the 2-year study period, CGM was initiated for 253 youth mean age 12 years (SD 3.78). Patients were followed for a mean of 13.4 months (SD 6.7), encompassing 784 follow-up visits (3.1 visits per patient, SD 1.94). Within this time, 64 patients (25%) discontinued use, with a mean of 4.7 months of use (SD 5.4), including 24 patients (9.5%) who received the device and never used it. Of the 190 who initiated CGM use, only 142 (56%) reported current CGM use at each follow-up visit during the study period. Continuous use was associated with younger age at initiation of CGM (p=0.001), shorter duration of diabetes (p=0.005), lower HbA1c (p&lt;0.005), and trial of professional CGM (p=0.001). CGM data was available for 429 of the follow-up visits, with 329 visits (77%) demonstrating the sensor was worn for at least 85% of the preceding 14-30 days.
For youth initiating CGM use during a 2-year period, we found a low rate of adherence to CGM use. However, the majority of those with consistent use wore the sensor at least 6 of 7 days, as recommended for effective use. Factors associated with continuous use included earlier implementation and prior professional CGM trial.

Disclosure
E.L. Montgomery: None. K.S. Jawad: None. S. Eubanks: None. K.A. Wintergerst: None. H.M. Rush: None. S. Watson: None.
922-P: LIRA-PRIME: A Randomized Trial in Primary Care Settings of Liraglutide vs. OAD for Glycemic Control in Patients with Type 2 Diabetes Not in Control on Metformin
Authors: UNGER JEFF , KALTOFT MARGIT , KOLHE DEVAYANI , PANDA JAYANT KUMAR , SARGıN MEHMET , WOLTHERS BENJAMIN OLE , ZOGHBI MAROUAN 
Published: June 2020

Most patients with type 2 diabetes (T2D) are treated in primary care, but data to guide evidence-based, shared decision making in this setting are scarce. LIRA-PRIME (NCT02730377) was a randomized, open-label, active-controlled trial in a primary care setting, comparing efficacy and safety of liraglutide vs. an oral antidiabetic drug (OAD) in patients with T2D inadequately controlled with metformin. Patients aged ≥18 years, with A1C 7.5-9.0%, recruited from nine countries (219 sites), were randomized 1:1 using an interactive web response system to liraglutide or an OAD (α-glucosidase inhibitor, DPP-4i, meglitinide, SGLT2i, SU or TZD, chosen by their physician) on top of metformin, for up to 104 weeks. Primary endpoint: time to inadequate glycemic control, defined as A1C &gt;7.0% at two consecutive visits after the first 26 weeks of treatment. Key secondary endpoints: time to premature treatment discontinuation, including for inadequate glycemic control, and occurrence of adverse events (AEs). From Mar 2016 to Aug 2017, patients were randomized to liraglutide (N=996) or OAD (N=995; 48% SGLT2i, 40% DPP-4i, 11% SU). Liraglutide significantly reduced the risk of inadequate glycemic control vs. OAD (416/996 [42%] vs. 547/995 [55%] patients, respectively; hazard ratio [95% CI] 0.58 [0.51;0.66]; p&lt;0.0001) and of premature treatment discontinuation (532/996 [53%] vs. 624/995 [63%], respectively; p&lt;0.0001). Median time to inadequate glycemic control (109 vs. 65 weeks; p&lt;0.0001) and premature treatment discontinuation (80 vs. 52 weeks; p&lt;0.0001) was longer with liraglutide vs. OAD. Rates of serious AEs and hypoglycemic episodes were similar, but more patients discontinued due to gastrointestinal AEs with liraglutide vs. OAD (54/980 [6%] vs. 9/984 [1%], respectively). Within global primary care settings, LIRA-PRIME demonstrated longer lasting glycemic control with liraglutide than with an OAD, when added to metformin.

Disclosure
J. Unger: Consultant; Self; Bayer. Research Support; Self; GlaxoSmithKline, Merck, Pfizer, Sanofi, Lilly, Janssen. Stock/Shareholder; Self; Tandem Diabetes. Other Relationship; Self; Abbott, Abbott Diabetes, Novo Nordisk. M. Kaltoft: Employee; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk A/S. D. Kolhe: Employee; Self; Novo Nordisk. J. Panda: None. M. Sargın: Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc., Pfizer Inc. B. Wolthers: Other Relationship; Self; Novo Nordisk. M. Zoghbi: Advisory Panel; Spouse/Partner; Janssen Pharmaceuticals, Inc., New Bridge. Advisory Panel; Self; Novartis AG. Advisory Panel; Spouse/Partner; Novartis AG. Advisory Panel; Self; Novo Nordisk A/S. Advisory Panel; Spouse/Partner; Pfizer Inc., Roche Pharma. Advisory Panel; Self; Sanofi.

Funding
Novo Nordisk A/S
932-P: Efficacy and Safety of Oral Semaglutide by Baseline Age in the PIONEER Clinical Trial Program
Authors: ARODA VANITA R. , BAUER ROBERT , HERTZ CHRISTIN L. , MONTANYA EDUARD , SØRRIG RASMUS , WARREN MARK L. , CARIOU BERTRAND 
Published: June 2020

In an exploratory analysis of 7 global phase 3a trials (PIONEER 1-5, 7, and 8) we evaluated the effect of age at baseline on efficacy (&lt;45, ≥45-&lt;65, or ≥65 years) and safety (&lt;65 or ≥65 years) for oral semaglutide (3, 7, 14 mg once daily) vs. comparators in patients with type 2 diabetes. Efficacy endpoints were change from baseline in HbA1c and body weight. Across all trials, there were 582, 3392, and 1683 patients aged &lt;45, ≥45-&lt;65, and ≥65 years, respectively. Baseline HbA1c was similar across age groups, whereas baseline body weight tended to be higher in younger patients. Overall, reductions in HbA1c were comparable across age groups for all trials and were generally larger with oral semaglutide than comparators, irrespective of age (Table). Body weight reductions were greater for oral semaglutide vs. comparators but without association between age and reductions in body weight. In general, proportions of patients with adverse advents (AEs) and AEs leading to treatment discontinuation were greater in the ≥65 vs. the &lt;65 age group for oral semaglutide and comparators (Table). To conclude, the greater effects of oral semaglutide vs. comparators on HbA1c and body weight were seen for patients regardless of age group in the global PIONEER trials. For the &lt;65 and ≥65 age groups, the safety profile of oral semaglutide was in line with other GLP-1RAs. Overall, there was a generally higher discontinuation rate in older patients.

Disclosure
V.R. Aroda: Consultant; Self; Duke, Novo Nordisk Inc., Sanofi. Employee; Spouse/Partner; Merck & Co., Inc. Research Support; Self; Applied Therapeutics, Fractyl Laboratories, Inc., Novo Nordisk Inc., Sanofi. Other Relationship; Self; IMNE, Medscape. R. Bauer: Employee; Self; Novo Nordisk A/S. C.L. Hertz: Employee; Self; Novo Nordisk A/S. E. Montanya: Advisory Panel; Self; Sanofi. Consultant; Self; Novartis Pharmaceuticals Corporation. Employee; Spouse/Partner; Almirall. Speaker’s Bureau; Self; AstraZeneca, Merck Sharp & Dohme Corp., Novo Nordisk A/S. R. Sørrig: Employee; Self; Novo Nordisk A/S. M.L. Warren: Advisory Panel; Self; Eli Lilly and Company, Novo Nordisk Inc., Sanofi. Research Support; Self; Eli Lilly and Company, Gan & Lee Pharmaceuticals, Novo Nordisk Inc., Sanofi. Speaker’s Bureau; Self; AstraZeneca, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. B. Cariou: Advisory Panel; Self; Bristol-Myers Squibb, Gilead Sciences, Inc., Lexicon Pharmaceuticals, Inc., Novo Nordisk Inc., Sanofi-Aventis. Board Member; Self; GENFIT. Research Support; Self; Amgen, Regeneron Pharmaceuticals. Speaker’s Bureau; Self; Abbott, AstraZeneca.

Funding
Novo Nordisk A/S
934-P: Association between CTRB1/2 RS7202877 (T&gt;G) Polymorphism and Glycemic Response to Liraglutide in Greek People with Type 2 Diabetes
Authors: KYRIAKIDOU ARTEMIS , KYRIAZOU ANGELIKI V. , KOUFAKIS THEOCHARIS , VASILOPOULOS YIANNIS , AVRAMIDIS IAKOVOS , BALTAGIANNIS STEFANOS , MANTHOU ELENI , GOULIS DIMITRIOS G. , ZEBEKAKIS PANTELIS , KOTSA KALLIOPI 
Published: June 2020

Previous research has demonstrated an association between genetic variation in the CTRB1/2 gene and response to incretin therapies. We aimed to evaluate the role of CTRB1/2 rs7202877 (T&gt;G) polymorphism in glycemic response to liraglutide among Greek people with T2D. 116 adults with T2D (51% female, mean BMI 35.4±6.4 kg/m2, mean age 68.3±10.9 years), who had been on treatment with liraglutide for at least 6 months were genotyped for the rs7202877 polymorphism, using real-time PCR. Responders met at least one of the following criteria: i) achievement of good glycemic control defined as HbA1c level of &lt;7%, either at 3 or 6 months after treatment initiation, ii) reduction of the baseline HbA1c levels by ≥1% after 3 or 6 months of liraglutide use, and iii) maintenance of the optimal glucose control (HbA1c &lt;7%) that a patient had before switching to liraglutide, after 3 or 6 months of treatment. Patients who failed to fulfil any of those criteria, were characterized as non-responders. 81 (70%) patients were classified as responders and 35 (30%) as non-responders. 97 (84%) patients were homozygous for the wild type T allele (TT) and 19 (16%) patients carried one polymorphic G allele (TG). Heterozygotes tended to have better response to liraglutide treatment; still, the difference was not significant (OR: 1.25, 95% CI: 0.4, 3.8, P=0.69). The probability of being a responder was 45% greater, when the baseline HbA1c was increased by 1% (adjusted for gender and baseline weight OR: 1.45, 95% CI: 1.05, 2.1, P=0.048). Additionally, an increase in baseline weight by 10 kg was associated with 26% reduced probability of being a responder (adjusted for gender and baseline HbA1c OR: 0.97, 95% CI: 0.94, 0.99, P=0.011). Our findings do not suggest a role of CTRB1/2 rs7202877 in affecting glycemic response to liraglutide. Lower baseline body weight and higher baseline glycemia might be related to better glycemic control following treatment with liraglutide.

Disclosure
A. Kyriakidou: None. A.V. Kyriazou: Research Support; Self; Novo Nordisk A/S. T. Koufakis: None. Y. Vasilopoulos: None. I. Avramidis: None. S. Baltagiannis: None. E. Manthou: None. D.G. Goulis: None. P. Zebekakis: None. K. Kotsa: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Sanofi-Aventis, Takeda Pharmaceutical Company Limited. Speaker’s Bureau; Self; Menarini Group. Other Relationship; Self; Novo Nordisk Inc.

Funding
Novo Nordisk (91220)
936-P: Plasma Proteomic Profiling Delineates Treatment Efficacy of a GLP-1/GIP Coagonist in Female and Male Mice
Authors: HOFMANN SUSANNA M. , WEWER ALBRECHTSEN NICOLAI J. , TSCHÖP MATTHIAS H. , FEUCHTINGER ANNETTE , BRIELMEIER MARKUS , FINAN BRIAN , DIMARCHI RICHARD , KLEINERT MAXIMILIAN , SACHS STEPHAN , MÜLLER TIMO D. , STEMMER KERSTIN , MANN MATTHIAS 
Published: June 2020

Objective: Polypharmacotherapy shows superior efficacy compared to monotherapy in correcting obesity and its co-morbidities in preclinical studies and clinical trials. Female organisms have been traditionally neglected in this research potentially contributing to an increased rate of adverse advents in women. To address this disparity we herein determined the efficacy of our monomeric peptide with a balanced agonism at the receptors for glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) to correct obesity, glucose metabolism, nonalcoholic fatty liver disease (NAFLD) and dyslipidemia in both sexes of a mouse model for diet-induced obesity (DIO) by combining physiological treatment endpoints with plasma proteomic profiling (PPP), a new unbiased diagnostic tool for the efficacy and optimization of pharmacological interventions.
Methods: We performed metabolic phenotyping along with PPP in body weight matched male and female DIO mice treated for 21 days with either PBS, the single GIP and GLP-1 monoagonists, or our GLP-1/GIP coagonist.
Results: GLP-1R/GIPR coagonism improved obesity, glucose intolerance, NAFLD and dyslipidemia with superior efficacy in both male and female mice compared to monoagonist treatments. PPP revealed in both sexes broader changes of plasma proteins after GLP-1/GIP coagonist compared to monoagonist treatments, including established and novel biomarkers for systemic inflammation, NAFLD and atherosclerosis. Subtle sex-specific differences have been observed in metabolic phenotyping and PPP.
Conclusions: We herein report enhanced efficacy of our GLP-1/GIP coagonist in both sexes relative to monoagonists for the treatment of metabolic disease. Wider sex-specific reductions of circulating proteins after GLP-1/GIP coagonist treatment may reflect additional metabolic benefits that are currently achieved exclusively after bariatric surgery.

Disclosure
S.M. Hofmann: Advisory Panel; Spouse/Partner; Novo Nordisk A/S. N.J. Wewer Albrechtsen: Research Support; Self; Mercodia, Novo Nordisk A/S, Novo Nordisk Foundation. Speaker’s Bureau; Self; Merck Sharp & Dohme Corp. M.H. Tschöp: Advisory Panel; Self; ERX Pharmaceuticals, Novo Nordisk Foundation. A. Feuchtinger: None. M. Brielmeier: None. B. Finan: Employee; Self; Novo Nordisk A/S. R. DiMarchi: Employee; Self; Novo Nordisk Inc. M. Kleinert: None. S. Sachs: None. T.D. Müller: Research Support; Self; Novo Nordisk Inc., Sanofi-Aventis. K. Stemmer: None. M. Mann: None.