bluuebunny/crossref_metadata_2025_split huggingface dataset:
1352-P: Ancestry Affects Biomarkers of Pediatric Type 1 Diabetes
Authors: KELLER NANCY , FULLER KEELY E. , SHUM BETTY J. , NOBLE JANELLE 
Published: June 2019

Presentation of type 1 diabetes (T1D) appears to differ among patients with different ancestries. In this study, medical record data were taken from type 1 diabetes patients, diagnosed from 2010 to 2017 at a single site, UCSF Benioff Children’s Hospital Oakland (BCHO). Patients were grouped into ancestry classes based on medical records. European (EUR; n = 81), Hispanic (HIS; n = 84), and African (AFR; n = 48) groups were compared for C-peptide levels at diagnosis and for levels of four autoantibodies (aAb); insulin (IAA), protein phosphatase-like IA-2 (IA-2A), glutamic acid decarboxylase (GADA), and zinc transporter (ZnT8A). All aAb measurements were performed at a single reference laboratory in Denver. The proportion of patients with no evidence of any aAb was similar in EUR and AFR groups (5% and 4%, respectively) but higher in HIS (14%). For up to three aAb, the number of aAb was correlated with the number of patients in the EUR (r = 0.96; p = 0.039) and AFR (r = 0.96; p = 0.038) groups but not in the HIS group (r = 0.58; p = 0.24). The pattern of autoantibody positivity differed among groups; most prevalent were IA-2A in EUR (75%), GADA in AFR (75%), and both IA-2A and GADA (both at 68%) in HIS. Differences in aAb patterns did not reach statistical significance but were consistent with published reports. As expected, C-peptide levels were below the normal range in the EUR group, regardless of aAb positivity. In contrast, in the HIS group, mean C-peptide levels were in the normal range for patients with up to three positive aAb; only HIS patients with all four aAb positive had C-peptide levels below the normal range. The AFR group was similar to the EUR group, with below normal C-peptide levels, except that the subset of AFR patients with a single positive aAb had C-peptide in the normal range. Observed differences in C-peptide mean and median values were significant between HIS and EUR groups (mean p = 0.013; median p = 0.046). Differences in biomarkers between HIS and EUR T1D patients may have implications for both differential diagnosis and management of T1D.

Disclosure
N. Keller: None. K.E. Fuller: None. B.J. Shum: None. J. Noble: Employee; Spouse/Partner; Roche Diagnostic USA.
1360-P: Increase in Diabetic Ketoacidosis at Diagnosis of T1D in Colorado Children, 2010-2017
Authors: ALONSO GUY T. , COAKLEY ALEXANDER , PYLE LAURA , MANSEAU KATHERINE , THOMAS SARAH , REWERS MARIAN , REWERS ARLETA 
Published: June 2019

Diabetic ketoacidosis at diagnosis of T1D in children is associated with high cost, higher long-term A1c, and complications. Due to delayed access to medical care, DKA in Colorado increased from 30% in 1998 to 46% in 2012. The rate in most developed countries is &lt;30%. To examine a potential effect of the Affordable Care Act’s overhaul of the U.S. healthcare on the prevalence of DKA at diagnosis, we reviewed records of Colorado residents &lt;18 years old who were diagnosed with T1D in 2010-17 and subsequently followed at the Barbara Davis Center for Diabetes. They account for &gt;80% of children with T1D in Colorado. From 2010-2017, 2137 subjects met inclusion criteria. The rate of DKA rose from 40% to 60%, doubling among privately insured, but increased less among children with public insurance (Figure). In a univariate, unadjusted regression analysis, race/ethnicity other than non-Hispanic white (p&lt;.01), public insurance (p&lt;.0001), and rural residence (p=.02) were associated with higher risk for DKA. Gender and primary language other than English were not significantly associated with DKA. There was a bimodal distribution by age. By 2017, 60% of children presented with DKA. The increase was pronounced in patients with private insurance. This setback paradoxically occurred during a time of increasing health insurance coverage. More study needs to be done to understand what factors are driving these changes.

Disclosure
G.T. Alonso: None. A. Coakley: None. L. Pyle: None. K. Manseau: None. S. Thomas: None. M. Rewers: None. A. Rewers: None.
1363-P: Cyber School: A Marker of High-Risk Youth with Diabetes?
Authors: MARCH CHRISTINE , SIMINERIO LINDA M. , MILLER ELIZABETH , LIBMAN INGRID 
Published: June 2019

For many youth with diabetes, school provides a structured and supervised environment for diabetes management. Cyber school is a recent alternative in many states with variable supervision. To our knowledge, no information is available on characteristics of youth with diabetes enrolled in cyber school. We identified 142 youth followed in a large academic diabetes center between 2014-2018. Medical records were reviewed for demographic, anthropometric, clinical, and laboratory data from their first visit after cyber enrollment. The vast majority, 130 (92%), had T1D and were white, 127 (90%). Mean age was 14.0±3.4 years with a duration of diabetes of 5.1±4.3 years. Most, 74 (53%), entered cyber in grades 9-12. Reasons for enrollment were documented for 91 (64%), with medical concerns being the most common, 28 (31%). Forty percent were overweight or obese. Most were managed with multiple daily injections, 104 (73%), compared with insulin pumps, 32 (23%), or other regimens. Very few, 8 (6%), utilized continuous glucose monitors. Mean hemoglobin A1c (HbA1c) for those diagnosed two or more years was 9.4±2.1%, and only 17, (18%), of those youth met the glycemic target of a HbA1c ≤ 7.5%. Dyslipidemia (LDL-cholesterol &gt;100 mg/dL) was highly prevalent at 37%; of those, mean LDL was 131±22 mg/dL. Depression was present in 38/84 (45%) screened youth over age 12 years. Missed clinic visits were common; 76 (54%) missed two or more visits in the 12 months before or after enrollment. Mean HbA1c was significantly higher in those missing two or more visits compared with 0-1 visits (9.4±0.3 vs. 8.0±0.3, p-value&lt;0.01), adjusting for age and duration of diabetes. Mean HbA1c increased with additional visits missed. To our knowledge, this is the first description of youth with diabetes in cyber school. They were characterized by poor glycemic control, limited use of devices, a high prevalence of comorbidities, and poor follow-up. This represents a unique group of high-risk patients who may benefit from additional interventions to ensure adequate follow-up.

Disclosure
C. March: None. L.M. Siminerio: None. E. Miller: None. I. Libman: Consultant; Self; Novo Nordisk Inc.
1369-P: Continuous Glucose Monitoring Interventions in Toddlers with Type 1 Diabetes (T1D)
Authors: LANNING MONICA S. , DIMEGLIO LINDA , LANGE SAMANTHA , DRISCOLL KIMBERLY A. , HANNON TAMARA S. , LAGGES ANN M. , WOERNER STEPHANIE , BUCKINGHAM BRUCE A. , HOOD KOREY K. 
Published: June 2019

Introduction: Achieving optimal glycemic control is difficult in children with T1D even with insulin pumps and continuous glucose monitoring (CGM). Additional support focused on improving technology use may improve diabetes management.
Methods: Children aged 2-6 years were enrolled in a 6-month adaptive study design (SMART) utilizing Dexcom G5 CGM. Monthly data were collected to assess time in range (70-180mg/dL) and adherence. If time in range was &lt;60% or adherence was &lt;6 of 7 days worn, participants’ families randomized to one of four interventions focusing on diabetes distress, developmental demands, fear of hypoglycemia, or remote monitoring. Parents completed surveys on diabetes distress, glucose monitoring satisfaction, hypoglycemia fear and confidence at enrollment and study end. HbA1c was collected at study initiation and study end.
Results: Of 77 participants, 52.6% were male, mean age 4.94 ± 1.42y (2.03-7.00), diabetes duration 2.12 ± 1.13y (0.58-4.26). Each participant received an average of 3 intervention sessions. HbA1c decreased and psychological outcomes improved at statistically and clinically significant levels (Table).
Conclusion: Providing interventions that address common diabetes management problem areas may help parents of young children with T1D improve glucose control and quality of life. More work is needed to identify which interventions were associated with the greatest benefit.

Disclosure
M.S. Lanning: None. L. DiMeglio: Research Support; Self; Amgen Inc., Caladrius Biosciences, Inc., Janssen Research & Development, Medtronic, Sanofi. Other Relationship; Self; Dexcom, Inc. S. Lange: Other Relationship; Self; Medtronic MiniMed, Inc. K.A. Driscoll: None. T.S. Hannon: Advisory Panel; Self; Eli Lilly and Company. A.M. Lagges: None. S. Woerner: None. B.A. Buckingham: Advisory Panel; Self; ConvaTec Inc., Novo Nordisk Inc., Profusa, Inc. Consultant; Self; Medtronic MiniMed, Inc. Research Support; Self; Beta Bionics, ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. Other Relationship; Self; Insulet Corporation, Tandem Diabetes Care. K.K. Hood: Consultant; Self; Lilly Diabetes. Research Support; Self; Dexcom, Inc. Speaker's Bureau; Self; Johnson & Johnson Diabetes Institute.

Funding
National Institutes of Health
1375-P: Acquisition of Self-Care in Youth with Type 1 Diabetes (T1D) Varies by Age and Task
Authors: LA BANCA REBECCA O. , VOLKENING LISA K. , LAFFEL LORI M. 
Published: June 2019

Aim: In childhood, there is gradual transition of T1D tasks from parents to youth. To assess acquisition of self-care by age, we examined parent report of responsibility across task domains in youth ages 5-18 years.
Methods: Parents of youth with T1D completed the Diabetes Family Responsibility Questionnaire using 3 response options (mainly parent, shared, mainly youth) across 5 T1D domains: Nutrition, Monitoring, Insulin, Communication, and Health Surveillance. Analyses included 3 age groups: 5-10 (Elementary School [ES]), 11-14 (Early Adolescence [EA]), and 15-18 (Late Adolescence [LA]).
Results: Youth (N=148, 50% male) were 12.9±3.2 [X±SD] years, with T1D duration 6.2±3.6 years; 60% pump treated, BG checks 5.6±2.9 X/day, A1c 8.4±1.3%. Parents were 84% mothers, 92% white, 83% married, and 63% college educated. Parent report of youth self-care varied by age and task (Figure). Youth self-care increased as age and T1D duration increased (p&lt;.001). Self-care in Nutrition began in ES, followed by Monitoring and Insulin in EA, and Communication in LA. Health Surveillance (e.g., sick day care) remained mainly under parent care for majority in ES, EA, and LA. In all youth, more parent involvement was related to lower A1c (p&lt;.03).
Conclusion: Recognizing and supporting youth during acquisition of self-care, especially for Nutrition, BG Monitoring, and Insulin, may help to prevent glycemic deterioration later in childhood/adolescence.

Disclosure
R.O. La Banca: None. L.K. Volkening: None. L.M. Laffel: Advisory Panel; Self; Lilly Diabetes, Novo Nordisk A/S, Roche Diabetes Care, Sanofi. Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Janssen Pharmaceuticals, Inc., UpToDate.

Funding
National Institutes of Health (P30DK036836)
1376-P: Glucose-Independent Racial Disparity in HbA1c Is Present at Onset of Type 1 Diabetes (T1D)
Authors: ALAQEEL AQEEL , CHALEW STUART 
Published: June 2019

Introduction: HbA1c is an important guide for management, diagnosis and prediction of complications in diabetes. We have shown that young black patients with established T1D have higher HbA1c than white patients even after adjustment for mean blood glucose, RBC indices, age, and gender. We hypothesized that glucose-independent racial disparity in HbA1c is also present at diagnosis of T1D.
Methods: Data was collected by chart review for self-identified white and black patients who presented between Jan 2012 and Nov 2018 to the Hospital ER with untreated new onset T1D. Analyte data is from initial blood sample. Data was collected for date of birth, sex, self-identified race, weight, height, glucose, HbA1c, pH, bicarbonate, insulin, C-peptide, pancreatic autoantibodies, RBC indices. Simple correlation and comparison of means between groups was performed. This followed by multiple variable regression modeling to test the statistical effect of race, gender, age, glucose, RDW-CV and other variables on HbA1c.
Results. We included 191 children with newly diagnosed T1D (69 blacks and 122 whites; 116 M, 75 F). HbA1c was correlated with glucose, insulin, c-peptide, age, RDW-CV, Hb, HCO3. blacks had higher HbA1c 11.9 ±1.9 vs. whites 11.04±2 (P=0.004), higher glucoses 530.6±230.4 vs. 441.9±211.3 mg/dL (P=0.0075), lower C-peptides 0.57± 0.42 vs. 0.76±0.61 ng/mL (P=0.019) and lower pH 7.28±0.15 vs. 7.33±0.12, (P=0.02). There was no statistical difference in age, BMI-z, HCO3 or insulin between the groups. After adjusting for age, sex, glucose, C-peptide and RDW-CV, HbA1c is still higher in blacks, P=0.037. Age, gender, glucose, C-peptide and RDW-CV were also significant covariates in the model.
Conclusions. 1- HbA1c at presentation is influenced by Race, glucose, age, sex, RDW-CV, and c-peptide 2- Even after adjustment for glucose blacks have higher HbA1c than whites 3- Glucose-independent HbA1c racial difference should be taken into account for purposes of diagnosis and management of T1D.

Disclosure
A. Alaqeel: None. S. Chalew: None.
1377-P: Driving Behaviors in Adolescents with Type 1 Diabetes
Authors: ROBERTS ALISSA J. , MOSS ASHLEY , YI-FRAZIER JOYCE 
Published: June 2019

Adolescents and adults with type 1 diabetes (T1D) are advised to take precautions when driving to prevent impairment due to hyper/hypoglycemia. Literature shows many adults with T1D do not use proper precautions to avoid glycemic excursions when driving, yet no known studies have examined this in adolescents with T1D. Adolescents may be at elevated risk due to risk-taking behavior associated with this age. The goal of this study is to describe driving related behaviors in adolescents with T1D. Data was collected from 53 adolescents seen in the diabetes clinic between 6/2017 and 12/2018. Driving behaviors were assessed via electronic intake form prior to the clinic visit and reviewed before providers saw patients. Of these 53 participants, 47% were female, average age was 19.4 years (SD 1.5), 53% were on CGM, and 60% were on an insulin pump. Forty-two percent reported checking their blood sugar rarely or never within 30 minutes before driving. If they had a glucose &lt;70 mg/dL prior to driving, 47% reported waiting until a recheck glucose (after treatment) is &gt; 70 mg/dL before driving. Only 40% reported pulling over their vehicle, treating, and waiting until their glucose was &gt;70 mg/dL if experiencing hypoglycemia while driving or being alerted they were becoming hypoglycemic via their CGM. Seventy percent reported always having a source of rapid acting glucose available when driving. In the past month, 43% had a low blood glucose while driving. Further, 11% reported driving within a few hours of consuming alcohol, 9% reported driving while feeling the effects of alcohol or other drugs, 13% reported driving within a few hours of using marijuana, and 47% reported texting while driving. Results demonstrate many adolescents with T1D are not using safe driving practices, particularly around preventing and treating hypoglycemia, which can cause significant cognitive-motor impairment. Furthermore, many adolescents reported unsafe behaviors around substance use prior to driving and texting while driving.

Disclosure
A.J. Roberts: None. A. Moss: None. J. Yi-Frazier: None.
1378-P: Gluten-Free Diet in Children with Recent-Onset Type 1 Diabetes without Coeliac Disease: A 12-Month Intervention Trial
Authors: NEUMAN VÍT , PRUHOVA STEPANKA , KULICH MICHAL , KOLOUŠKOVÁ STANISLAVA , VOSAHLO JAN , ROMANOVA MARTINA , PETRUZELKOVA LENKA , OBERMANNOVA BARBORA , CINEK ONDREJ , SUMNIK ZDENEK 
Published: June 2019

Objectives: Data on the role of gluten in type 1 diabetes (T1D) are scarce. We aimed to test whether gluten-free diet (GFD) can decelerate the decline in beta-cell capacity in newly diagnosed non-celiac T1D children.
Methods: Forty-six children (aged 10.2±3.3 years) were recruited into this non-randomized self-selected intervention trial: 26 started with GFD whereas 20 remained on standard diet. Main outcomes were the decline in C-peptide area under the curve (AUC) in mixed-meal tolerance tests and the differences in insulin dose, insulin dose adjusted A1c (IDAA1c) and HbA1c at 12 months. Data were analyzed as intention-to-treat by linear regression models adjusted for baseline parameters. The adherence to GFD was tested by immunoreactive gluten in stool.
Results: Mean decrease in C-peptide AUC was 293 vs.484 pmol/L (p=0.3) at 6 months, and 567 vs. 919 pmol/L (p=0.1) at 12 months in GFD and control group, respectively. The GFD group had a lower insulin dose by 0.22 U/kg/day (p=0.007), lower IDAA1c by 1.5 (p=0.003) and lower mean HbA1c by 7.5 mmol/mol (p=0.01) at 12 months (Figure 1). There was no difference in daily carbohydrate intake between the groups (p=0.4). Immunoreactive gluten was found in the stool of only 3 patients.
Conclusions: GFD kept over the first year after T1D diagnosis was associated with lower insulin demand and lower HbA1c, although the groups did not differ in the C-peptide dynamics.

Disclosure
V. Neuman: None. S. Pruhova: None. M. Kulich: None. S. Koloušková: None. J. Vosahlo: None. M. Romanova: None. L. Petruzelkova: None. B. Obermannova: None. O. Cinek: None. Z. Sumnik: None.

Funding
Ministry of Health of the Czech Republic (16-27994A)
1379-P: Type 1 Diabetes Mellitus and Periodontal Disease—Relationship with Pubertal Stage and Glycaemic Control
Authors: CHAKRABORTY PAMPITA , GHOSH SUJOY 
Published: June 2019

Background and Aims: Periodontal disease (PD) has been considered as the sixth complication of diabetes (DM). It has also been suggested that PD may worsen glycemic control. The present study has been designed to establish correlation between periodontal health status with pubertal stage and metabolic control in type 1 diabetes (T1D).
Methodology: Oral hygiene index (OHI), gingival index (GI), probing pocket depth (PPD) and clinical attachment loss (CAL) were recorded in subjects with T1D (110) and healthy siblings (22). Duration, age, HbA1c and presence of microvascular complications was documented.
Result: GI (p=0.044) and PPD (p=0.013) was worse in the cases vs. the controls. Greater PPD (p=0.026) in cases vs. the controls in stage II-IV puberty was seen and both worsening GI (p=0.038) and greater PPD (p=0.027) in the cases vs. controls in stage V despite better OHI (p=0.040). Pubertal staging revealed no difference in any of the studied dental parameters in stage 1. A binary logistic regression model with age, HbA1c and duration of DM as independent continuous variables, detected HbA1c as a significant predictor of PD. HbA1c along with stage of puberty rather than duration of DM and chronological age were found as important predictor of PD. PD was significantly associated with markers of nephropathy and neuropathy. Both the PPD and GI were found to have significant positive correlation with vibration perception threshold and microalbuminuria in the cases. A positive correlation was observed between HbA1c levels and albumin creatinine ratio (ACR) levels, p=0.010.
Conclusion: T1D was more likely to develop PD compared to healthy siblings. Onset and progression of puberty and poorer glycaemic control, rather than duration of DM was associated with greater risk of PD. PD was more likely to be associated with markers of microvascular disease.

Disclosure
P. Chakraborty: None. S. Ghosh: None.

Funding
Department of Science & Technology, Government of India, West Bengal; Research Society for the Study of Diabetes in India
1383-P: Longitudinal Changes in Transition Readiness (TR) in Teens with Type 1 Diabetes (T1D) Are Unrelated to Glycemic Control
Authors: GOETHALS EVELINE R. , VOLKENING LISA K. , COMMISSARIAT PERSIS V. , BUTLER DEBORAH A. , MCGILL DAYNA E. , LAFFEL LORI M. 
Published: June 2019

Aim: During adolescence, teens with T1D increase self-care, anticipating future independence. To assess TR skills (i.e., affective, behavioral, and cognitive preparation to transfer from pediatric to adult care), teens with T1D and parents completed the validated Readiness for Independent Self-Care Questionnaire (RIS-Q).
Methods: Teens, ages 13-17, with T1D and parents completed RIS-Q every 6 months over 18 months. Teen and parent reports of teen treatment adherence and self-efficacy were assessed as predictors of TR and A1c with longitudinal mixed models.
Results: At entry, teens (N=178, 52% male, 88% white) had mean±SD age 14.9±1.3 years, T1D duration 7.4±3.7 years, 4.9±2.0 BG checks/day, and A1c 8.5±1.0%; 67% were pump users. Teen and parent reported TR increased over time while teen A1c was unchanged (Figure). In multivariate models, teen age, teen reported adherence, and self-efficacy predicted TR (all p&lt;.001). Teen TR did not predict A1c while teen reported adherence, self-efficacy, and BG checks/day predicted A1c (all p&lt;.008). Longitudinal models using parent reports had similar results.
Conclusion: Teen TR increased with age and over time but was unrelated to A1c, suggesting a disconnect between teen perceptions of self-care readiness and self-care behaviors. While TR may be important, it is insufficient, highlighting need to improve self-care behaviors and A1c in teens with T1D.

Disclosure
E.R. Goethals: None. L.K. Volkening: None. P.V. Commissariat: None. D.A. Butler: None. D.E. McGill: None. L.M. Laffel: Advisory Panel; Self; Lilly Diabetes, Novo Nordisk A/S, Roche Diabetes Care, Sanofi. Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Janssen Pharmaceuticals, Inc., UpToDate.

Funding
National Institutes of Health (R01DK095273, P30DK036836, T32DK007260, K12DK094721); JDRF (2-SRA-2014-253-M-B)