bluuebunny/crossref_metadata_2025_split huggingface dataset:
856-P: Can Monetary-Based Reinforcement for Self-Monitoring Blood Glucose (SMBG) Impact Psychosocial Outcomes? A Randomized Controlled Trial
Authors: WONG JESSIE J. , ADDALA ANANTA , HOOD KOREY K. , WAGNER JULIE , CENGIZ EDA , TICHY EILEEN M. , WEYMAN KATE , NARANJO DIANA 
Published: June 2019

Background: Members of our group previously reported that monetary reinforcement of SMBG related behaviors shows robust increases in frequency of SMBG and modest decreases in A1c among youth with type 1 diabetes (T1D). In these secondary data analyses, we explored effects on psychosocial functioning.
Methods: Sixty youth ages 12-21 (Mage=15.58, SD=2.31) with T1D, A1c 7.5-13%, and &lt;4 BG checks per day were randomized to either a 24-week reinforce intervention or enhanced usual care (EUC). The intervention consisted of monetary incentives for completing blood glucose checks, texts with provider, glucose data uploads, and glucose pattern recognition forms. Validated psychosocial questionnaires were administered at baseline, 6, 12, 24, and 36 weeks. Measures included youth reported diabetes distress, family conflict, and negative affective responses to out-of-range glucose results.
Results: Generalized linear models showed no significant time x condition effects. In t-tests at discrete follow-ups, compared to the control group, the reinforce group had significantly lower youth-reported diabetes related family conflict at 12 weeks (22.39 vs. 25.11, p=.043) and significantly higher negative affective responses to out-of-range glucose results at 24 weeks (13.62 vs. 11.71, p=.047).
Conclusion: Monetary reinforcers targeting SMBG behaviors may produce transitory decreases in youth perceptions of family conflict and transitory iatrogenic increases in youth’s negative affective responses to out-of-range glucose results. The timing of changes in family conflict, negative affect, and previously reported changes in A1c suggest that psychosocial changes may reflect youth responses to A1c as well as to reinforcers per se. For broader effects, the intervention could include psychosocial components that seek to directly maintain decreased family conflict and mitigate negative affect related to increased awareness of glucose control.

Disclosure
J.J. Wong: None. A. Addala: None. K.K. Hood: Consultant; Self; Lilly Diabetes. Research Support; Self; Dexcom, Inc. Speaker's Bureau; Self; Johnson & Johnson Diabetes Institute. J. Wagner: None. E. Cengiz: Advisory Panel; Self; Abvance, ADOCIA, MannKind Corporation, Novo Nordisk Inc. Speaker's Bureau; Self; Novo Nordisk Inc. E.M. Tichy: None. K. Weyman: None. D. Naranjo: Advisory Panel; Spouse/Partner; Eli Lilly and Company. Speaker's Bureau; Spouse/Partner; Johnson & Johnson Diabetes Institute. Other Relationship; Self; Abbott.

Funding
National Institutes of Health
863-P: Insomnia Severity and Insulin Adherence
Authors: ZHENG YAGUANG , KORYTKOWSKI MARY T. , SEREIKA SUSAN M. , BURKE LORA E. , ATWOOD CHARLES W. , STROLLO PATRICK J. , JEON BOMIN , CHASENS EILEEN R. 
Published: June 2019

Background: Adherence to medications is vital for glycemic control in type 2 diabetes. It is unclear if insomnia is a barrier to medication adherence. The aim of this secondary analysis was to examine the association between insomnia and adherence to insulin therapy.
Method: Using a cross-sectional design, baseline data from subjects (N=139) prescribed insulin from the Diabetes Sleep Treatment Trial were analyzed. Measures included demographics, A1C, BMI, the Insomnia Severity Index, and the Pittsburgh Sleep Quality Index. Self-reported adherence to insulin therapy was determined by response to the question: How many of the past 7 days did you take your recommended insulin injections and scored as 7 days for adherent (77.7%; n=107) and 0 to 6 days for non-adherent (23.0%; n=32). Data were analyzed using univariate and backward multivariate logistic regression.
Results: The sample was diverse (55.4% white; 46.0% female; 41.7% married/partnered; 55.4% &gt;2 years post high school with a mean age of 56.3±10.9 years, BMI of 35.2±6.6 kg/m2; and A1C of 8.3±1.7%). Individuals with insulin adherence had a lower A1C than those with non-adherence (8.0±1.6% vs. 9.5±1.7%, p&lt;.001). Insomnia was negatively associated with insulin adherence in univariate and multivariate logistic regression.
Conclusion: These results suggest insomnia severity and race are associated with deceased insulin adherence. The mechanisms for these potential associations need to be further explored.

Disclosure
Y. Zheng: None. M.T. Korytkowski: None. S.M. Sereika: None. L.E. Burke: None. C.W. Atwood: None. P.J. Strollo: Consultant; Self; Emmi, Inspire Medical Systems, Philips Respironics. Research Support; Self; Jazz Pharmaceuticals, ResMed. B. Jeon: None. E.R. Chasens: Research Support; Self; National Institute of Diabetes and Digestive and Kidney Diseases, Philips Respironics, ResMed Inc.

Funding
National Institutes of Health (R01DK096028)
87-OR: Disappearing Antibodies: Frequency and Effect on T1D Progression
Authors: O'ROURKE COLIN , SO MICHELLE , GREENBAUM CARLA , BAHNSON HENRY T. , SPEAKE CATE 
Published: June 2019

While the majority of individuals with ≥2 autoantibodies (AAB) will progress to clinical T1D, there are reports that AAB disappear in some individuals. Clinical trials to delay or prevent disease progression often enroll those at stage 1 or 2, defined as individuals with ≥2 AAB confirmed on two separate occasions. Using data from TrialNet’s Pathway to Prevention study, we aimed to determine (a) how many individuals at stage 1 or 2 subsequently lost AAB, and (b) how this impacted the risk of T1D progression.
Individuals confirmed to be at stage 1 or stage 2 diabetes with a mean follow-up of 2.2 years (0.1 to 13) were included (n=3267). 3141 (96%) maintained their status over time while 126 (4%) did not (non-maintainers). This affected their risk of progression (Figure).
Conclusion: Reverting from stage 1 or stage 2 diabetes is rare; yet, if it occurs, the risk of progressing to stage 3 during the follow-up period is reduced. This suggests that there are unknown mechanisms that can lead to immune remission in some individuals.

Disclosure
C. O'Rourke: None. M. So: None. C. Greenbaum: Research Support; Self; Janssen Research & Development. H.T. Bahnson: None. C. Speake: None.

Funding
JDRF; National Institutes of Health
875-P: To Treat High Diabetes Distress or Not: Determining the Clinical Impact of Targeted Interventions with Type 1 Adults
Authors: PARRA JOSÉ , HESSLER DANIELLE M. , FISHER LAWRENCE , POLONSKY WILLIAM , STRYCKER LISA A. , BOWYER VICKY , DEDHIA MANSI , MASHARANI UMESH 
Published: June 2019

A recent study (T1-REDEEM) reported the relative effectiveness of two interventions to reduce high diabetes distress (DD) among adults with type 1 diabetes (T1). While these results show promise regarding the efficacy of DD-targeted interventions, there is little evidence to support their use when compared to non-treatment controls. We leveraged two recent studies to examine differences between the effect of targeted interventions on high DD T1 adults and a comparable sample of untreated participants, as well as to document the stability of untreated DD over time. T1 adults with elevated baseline DD (mean ≥ 2.0) and HbA1c (≥ 7.5), identified from a longitudinal, non-intervention, observational study (non-INT) (N = 51, age = 40.4 [SD = 16.8], 72.5% female, baseline DD = 2.5 [SD = 0.4], baseline HbA1c = 8.4 [SD = 1.3]), were compared to a matched sample of T1 adults who participated in T1-REDEEM (INT) (N=51, age = 48.8 [SD = 15.3], 74.5% female, baseline DD = 2.6 [SD = 0.4], baseline HbA1c = 8.7 [SD = 1.0]). Both groups completed the T1-DDS questionnaire at baseline and 9 months. Large reductions in DD (mean ∆ ± SD) were reported in the INT group (-0.6 ± 0.6), while minimal change was reported in the non-INT group (-0.2 ± 0.6), yielding a statistically and clinically meaningful difference (-0.4±0.6, p = 0.002; effect size d=.67) between groups. Additional analyses using the established MCID (0.19) for the T1-DDS showed that DD increased significantly (≥ 1 MCID) or persisted at high levels for 51% of non-INT participants, compared to 23.5% in the INT group. Targeted interventions lead to dramatic reductions in DD when compared to untreated individuals. Furthermore, high DD does not resolve over time when left unaddressed; in fact, DD remains high or worsens in more than half of non-INT participants. These data suggest that interventions targeting DD are clinically effective in T1 adults with high DD relative to non-treatment controls, and that high DD can become chronic if left untreated.

Disclosure
J. Parra: Employee; Self; Behavioral Diabetes Institute. D.M. Hessler: Consultant; Self; Eli Lilly and Company. L. Fisher: Consultant; Self; Abbott, Eli Lilly and Company. W. Polonsky: Consultant; Self; Abbott, Bigfoot Biomedical, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Johnson & Johnson Diabetes Institute, Merck & Co., Inc., Novo Nordisk Inc., Sanofi, Servier. L.A. Strycker: None. V. Bowyer: None. M. Dedhia: None. U. Masharani: Research Support; Self; Clementia Pharmaceuticals.

Funding
National Institutes of Health
887-P: Biological and Psychological Risk Factors for Eating Disorders in Type 1 Diabetes
Authors: LEE-AKERS DAWN , SIMON JUDY , AKERS ERIN 
Published: June 2019

Background: Women with type 1 diabetes (T1D) are 2.4 times more likely to develop an eating disorder than their nondiabetic peers. In addition, T1D has been reported as a risk factor associated with the development of an eating disorder.
Objective: To identify the biological disruptions and psychological pressures unique to a person with T1D that create a higher risk for developing an eating disorder.
Design and Methods: Conducted a three-year review of literature, articles and research studies on biological systems impacted by T1D, and on the psychological factors involved in eating disorders. Merged the research with case-study evidence obtained from Diabulimia Helpline clients and online support group members through discussions, posts and responses to questions.
Results: A number of physiological consequences of the destruction or removal of beta cells are known precursors to the onset of an eating disorder. Insulin is required for proper regulation of leptin, neuropeptide Y and dopamine, all of which are involved in the consumption and use of energy. While insulin analogs have made great strides, they do not perfectly mimic natural insulin or it’s interactions with other hormones and neurochemicals in the body. In addition, the more “out of range” a person’s blood glucose is, the more disrupted are these physiological mechanisms. The absence of amylin disrupts satiety mechanisms both directly in the brain and indirectly in the intestine through uncontrolled gastric emptying. In addition, certain character traits that are associated with eating disorders, such as avoiding thoughts and emotions or black and white thinking, can be exacerbated with a T1D diagnosis.
Conclusion: The development of T1D increases the number of risk factors a person has for developing an eating disorder, some of which are biological in nature and thus cannot be avoided. We can also see how biology becomes psychology when, for example, a reduction of leptin creates a risk of binging which in turn creates a risk for insulin omission.

Disclosure
D. Lee-Akers: None. J. Simon: None. E. Akers: None.
890-P: If We Build It, Will They Come? Engagement Data from a Young Adult Diabetes Transition Clinic
Authors: NAGRA HARPREET , JOARDER FARAHNAZ , ANDREAS LAURA , GUTTMANN-BAUMAN INES , KRAUS KIMBERLY , ROCHA LOLIS 
Published: June 2019

Objectives: Transition from pediatric to adult health care for young adults with type 1 diabetes has been notably concerning for patients and professionals alike. The Young Adult Diabetes Clinic (YADC) model—part of a larger transition program effort called Movin’ Up, Movin’ On, was developed to improve engagement with young adults in the transition process.
Method: The multidisciplinary clinic occurs on a half day, once a month. The clinic features a 45-minute orientation to adult diabetes care led by a behavioral health provider, followed by a 25-minute diabetes education visit and 25-minute medical appointment.
Results: Between November 2017 to December 2018, 129 young adults ages 17-25, approximately 60% male, were referred to the YADC (48 external and 52 internal referrals). Of the 129, 47 patients declined and 13 were non-responsive to the option to attend. Engagement efforts included word-of-mouth, reminding providers, and social media advertising. Common reasons for declining included conflict with work or school schedule, or clinic being too early in the morning. From the 47 who declined attendance, 28 established care independently at our clinic. Seven of the 47 patients remained in pediatrics, and 13 of these 47 patients’ provider status was unknown. Fifty-four patients scheduled and/or confirmed attendance. Approximately 44% were female, and mean hemoglobin A1C was 9.13% (76 mmol/mol). Approximately 27% were covered by state insurance while 73% had private insurance. Of the 54 scheduled, 12 patients no-showed, and 42 attended. Twenty-seven of the 54 patients both, attended YADC and established themselves as patients.
Conclusions: Preliminary data are promising, in that more than 50% of the patients who agreed to attend the clinic also established ongoing clinical services. The clinic model also supported only 10% of patients being lost to follow-up compared to higher rates previously reported in the literature. These results warrant ongoing support for the YADC model.

Disclosure
H. Nagra: None. F. Joarder: None. L. Andreas: None. I. Guttmann-Bauman: None. K. Kraus: None. L. Rocha: None.
904-P: Identification, Diagnosis, and Treatment of Prediabetes in Veterans at VA Central Iowa
Authors: THORSON GRETCHEN , PATTERSON JULIANNE M. , JORGENSEN KARMEN , VEIGULIS ZACHARY P. 
Published: June 2019

The prevalence of type 2 diabetes is high with approximately 24% of Veterans having the diagnosis and 70% being at high risk. In addition to traditional risk factors for diabetes, Veteran have a unique risk factor of Agent Orange exposure in Vietnam. Despite this increased risk, only 17 Veterans at VA Central Iowa had the prediabetes ICD-10 code R73.03. The Diabetes Prevention Program (DPP) indicates that lifestyle changes can reduce the progression to type 2 diabetes up to 58% in those under 60 and by 71% in those 60 or older. We piloted a process to identify, diagnose and treat prediabetes in one primary care team. After the 5-month pilot, prediabetes diagnosis rates increased by 5 times the pre-intervention rate (17 to 85). After all primary care providers and nurses received education on how to identify, diagnosis, and treat prediabetes, surveyed providers indicated they were more likely to diagnose and treat prediabetes according to evidence-based guidelines. After this 3-month staff education series, prediabetes diagnosis facility rates increased by 6 times the pre-intervention rate (67 to 421). The Prediabetes Identification Dashboard and Treatment Plan Tool was created after the pilot to identify Veterans at risk for diabetes. The tool can determine if referrals such as Nutrition, Diabetes Education, weight loss clinic, metformin, or a weight loss medication were used. In 2018, this tool identified 7,299 (28.4%) of Veterans at VA Central Iowa who were at risk for diabetes. Of the 7,299 Veterans, 2,932 (11.4%) were at high risk for prediabetes and diabetes since they’ve had one A1C between 5.7-6.4%. It’s essential for Primary Care staff to provide prediabetes education at the time of diagnosis. During the pilot, 97% of the Veterans wanted to receive education in Primary Care and declined referrals. This prediabetes pilot, education series, and prediabetes dashboard tool will be implemented at regional VA sites to improve prediabetes care and prevent progression to diabetes.

Disclosure
G. Thorson: None. J.M. Patterson: None. K. Jorgensen: None. Z.P. Veigulis: None.
907-P: Striking Improvements in HbA1c following Commencement of Flash Glucose Monitoring in Type 1 Diabetes
Authors: GIBB FRASER W. , STIMSON ROLAND H. , MCKNIGHT JOHN A. , TYNDALL VICTORIA , RITCHIE STUART A. , ZAMMITT NICOLA N. , DOVER ANNA R. 
Published: June 2019

Little evidence currently supports the efficacy of Flash Monitoring (FM) in type 1 diabetes. We present the largest prospective study of clinical outcomes following FM.
National Health Service (NHS) funding for FM was introduced in Feb 2018 in our center. We evaluated outcomes in 900 people with T1DM. Baseline HbA1c was the most recent value prior to commencing FM. Control HbA1c data were obtained from 518 people with no prior or current FM use. Pre- and post-FM hypoglycemia and Hospital Anxiety and Depression Scale (HADS) data were available in 57%. Hospital admission and test-strip prescription data were obtained for the 6 months following NHS-funding and the corresponding period the previous year.
Median age was 42 years (IQR 30 - 55). Mean baseline HbA1c was 65±15 mmol/mol. Pre-FM, 34.2% had HbA1c &lt;58 mmol/mol (7.5%) which rose to 50.9% at next follow-up (median 343 days from baseline HbA1c), P &lt; 0.001. Those with HbA1c &gt; 75 mmol/mol (9.0%) fell from 17.8% to 8.5%, P &lt; 0.001. Mean reduction in HbA1c was 5.6±10.9 mmol/mol (P &lt; 0.001) but was greater in those with baseline HbA1c above 75mmol/mol (-15.4±16.8 mmol/mol, P &lt; 0.001). In the control group, HbA1c did not change across the corresponding period (+0.2 mmol/mol, P = 0.66). In multivariate analysis, less frequent SMBG pre-FM (P = 0.03), higher HbA1c (P &lt;0.001) and higher socioeconomic status (P = 0.02) were all associated with greater likelihood of a ≥5 mmol/mol fall in HbA1c. Impaired awareness of hypoglycemia (IAH) improved, in those with a prior history of IAH, after FM use (P &lt; 0.001). HADS depression (2 [1 - 5] vs. 1 [0 - 3], P &lt; 0.0001) and anxiety scores (2 [1 - 5] vs. 1 [0 - 3], P = 0.03) were higher following FM use. DKA admissions fell significantly (2 vs. 8, P = 0.02) but no effect was observed on total admissions or emergency department attendance. Blood glucose test strip prescribing fell to 14.3% of pre-FM levels (P &lt; 0.01).
FM is associated with reduced DKA admissions and marked improvement in glycemic control across a wide range of people with T1DM.

Disclosure
F.W. Gibb: None. R.H. Stimson: None. J.A. McKnight: Other Relationship; Self; Boehringer Ingelheim International GmbH, Lilly Diabetes, MedImmune, Novo Nordisk Inc. V. Tyndall: None. S.A. Ritchie: Other Relationship; Self; MedImmune, Novo Nordisk Inc. N.N. Zammitt: None. A.R. Dover: Other Relationship; Self; Abbott.
908-P: Accuracy Comparison of the Freestyle Libre Pro Continuous Glucose Monitoring (CGM) and Point-of-Care (POC) Testing in Noncritically Ill Hospitalized Patients with Type 2 Diabetes Treated with Basal-Bolus Insulin Regimen
Authors: GALINDO RODOLFO J. , URRUTIA MARIA A. , DAVIS GEORGIA , KHOWAJA AMEER , ALBURY BONNIE S. , ANZOLA ISABEL , JOHNSON ASHLEY A. , VELLANKI PRIYATHAMA , CARDONA SAUMETH , FAYFMAN MAYA , MIGDAL ALEXANDRA , ZAMBRANO CESAR , PENG LIMIN , PASQUEL FRANCISCO J. , UMPIERREZ GUILLERMO E. 
Published: June 2019

Background: There are no published studies assessing the accuracy of the FreeStyle Libre CGM in the inpatient management of patients with type 2 diabetes (T2D).
Methods: Adult patients (n: 81) on basal-bolus insulin therapy with a target BG between 70-180 mg/dl were monitored with POC before meals and bedtime and by CGM. The primary outcome was the mean amplitude relative difference (MARD) between matched glucose pairs obtained from POC and CGM.
Results: Among 1453 pairs, the overall MARD was 14.4%. The overall percentage of glucose values within ±15% or 15mg/dl, ±20% or 20mg/dl, and ±30% or 30mg/dl of the POC reference value was 63%, 78%, and 92%, respectively. Clarke Error Grid analysis showed acceptable clinical accuracy with 98.0% of glucoses falling into Zones A (76.8%, n: 1,116) and B (22.0%, n: 320). Accuracy was lower for glucoses &lt; 80 mg/dL (Table 1), however; there were limited matched glucose pairs in hypoglycemic range.
Conclusions: FreeStyle Libre CGM showed an overall satisfactory performance in hospitalized patients, with lower accuracy observed for glucoses &lt; 80 mg/dL. Larger inpatient studies are needed to confirm its accuracy in non-critically ill hospitalized patients.

*Proportion of CGM values within ±15%/±15 mg/dL of POC glucose values, and the analogous %20/20, %30/30

Disclosure
R.J. Galindo: Advisory Panel; Self; Abbott, Novo Nordisk Inc., Sanofi US. Research Support; Self; Novo Nordisk Inc. M.A. Urrutia: None. G. Davis: None. A. Khowaja: None. B.S. Albury: None. I. Anzola: None. A.A. Johnson: None. P. Vellanki: Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Merck & Co., Inc. Research Support; Self; National Institutes of Health. S. Cardona: None. M. Fayfman: None. A. Migdal: None. C. Zambrano: None. L. Peng: None. F.J. Pasquel: Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Merck & Co., Inc. G.E. Umpierrez: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Pharmaceuticals, Inc. Research Support; Self; AstraZeneca, Merck & Co., Inc., Novo Nordisk Inc., Sanofi US.

Funding
Sanofi
921-P: Managing Trend Arrows with FGM: Effects on Glycemic Control in Type 1 Diabetic (T1DM) Subjects
Authors: RODIA COSIMO , BIANCHI CRISTINA , BERTOLOTTO ALESSANDRA , GIANNARELLI ROSA , CAMPI FABRIZIO , GENNAI SIMONA , PRATO STEFANO DEL , ARAGONA MICHELE 
Published: June 2019

Background: The use of flash glucose monitoring (FGM) has expanded widely among diabetic patients. Large randomized controlled trials demonstrated that use of FGM resulted in significant reductions in hypoglycemia, increased time in target range, reduced glycemic variability, and greater patient satisfaction compared with finger stick but no significant effects on glycemic control. Nonetheless, there is sparse guidance for what actions individuals should take based on the trend arrow data.
Aim of the Study: To verify the impact of published recommendation (Bianchi C., Aragona M. J Diabetes Complications. 2018 Oct 24) on glycemic control in type 1 diabetic subjects (T1DM). Patients and Methods: Since January 2018, 145 T1DM patients initiated FGM, after a period of education on the system and how to adjust insulin doses based on trend arrow (Trained Group - TG) and compared to a matched group of 204 patients who started FMG before recommendations were elaborated and therefore not being trained (Not Trained Group - NTG). The two groups showed no significant difference in terms of age, sex, duration of disease, type of treatment, BMI and insulin requirements.
Results: In TG HbA1c at baseline was 59±14 mmol/mol to decline 55±12 mmol/mol at month 6 (p&lt;0.00001). In NTG HbA1c at baseline was 58±14 mmol/mol with minimal though statistically significant reduction after 6 months (56±12 mmol/mol; p&lt;0.04). In both groups there was no change in BMI and Insulin Requirements.
Conclusions and Comments: In our clinical practice, FGM implementation was associated with a small but significant reduction in HbA1c, particularly in trained patients. Prospective and larger studies are needed to validate international guidelines for the education of diabetic patients adopting these new technologies.

Disclosure
C. Rodia: None. C. Bianchi: None. A. Bertolotto: Speaker's Bureau; Self; Abbott, Lilly Diabetes. R. Giannarelli: None. F. Campi: None. S. Gennai: None. S. Del Prato: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, GlaxoSmithKline plc., Merck Sharp & Dohme Corp., Novartis Pharmaceuticals Corporation, Novo Nordisk A/S, Sanofi, Servier, Takeda Pharmaceutical Company Limited. Board Member; Self; AstraZeneca. Research Support; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc. Speaker's Bureau; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Takeda Pharmaceutical Company Limited. M. Aragona: None.