bluuebunny/crossref_metadata_2025_split huggingface dataset:
1265-P: Understanding the Childhood Obesity Trend in Brazil: The Target for Diabetes Prevention
Authors: OLIVEIRA ANA LUISA , FREITAS FILIPE , CLEMENTINO MICHELE , MELO LARA G. , SILVA DYALLE C. , GARCIA PRISCILA , CORREIA MATHEUS , MENDES MARCUS VINICIUS , SANTOS MARIANA , OLIVEIRA ATILA A. , DECHICHI THEO , OLIVEIRA ANTONIO CESAR , OLIVEIRA ANA MAYRA 
Published: June 2020

Diabetes mellitus (DM) in children is on the rise worldwide and it’s well established the relationship between it and obesity. The understanding of this risk factor for DM is critical to preventing the disease. The objective is to analyze epidemiological trends of weight in children, adding data from 2019. Temporal cross-sectional analysis of the years 2001, 2011 and 2019 was randomly done with children aged 5 to 9 years and proportionally selected from public and private schools in Feira de Santana, Bahia, Brazil. Overweight and obesity were defined using body mass index (BMI) ≥ the 85th and the 95th percentiles for age and gender, respectively. A total of 1.994 children were studied, being 699 (15.6±2.5 BMI; 366 [52%] girls; 7.1±1.3y), 714 (16.6±3.0 BMI; 348 [48.9%] girls; 7.6±1.4y), 581 (17.0±3.7 BMI; 303 [53.2%] girls; 6.9±2.2y) in 2001, 2011 and 2019 respectively. The excessive weight prevalence increased significantly from 2001, 2011 to 2019 (overweight [9.2%, 15.5% and 16.9%] and obesity [4.4%, 7.2%; 11.7%]) and normal weight decreased (86.4%, 68.6%, 61.9%) with p value &lt;0.005 for all analyzes. Classifying by type of school, private (group 1) and public (group 2), in both groups comparing 2001, 2011 and 2019, the rate of normal weight decreased (84.2%, 68.6%, 59.4% for group 1 and 88.0%, 81.7% and 67.6% for group 2), also with significance. The prevalence of overweight significantly increased between 2001 and 2011 for both private (9.9%, 19.9%) and public (8.7%, 13.3%) sectors, but maintained itself stable for both between 2011 and 2019 (group 1[19.9%, 18.6%], group 2 [13.3%, 12.8%]). As for obesity, it did significantly increase in both groups through the entire period, at a rate of 6.0%, 11.5% and 13.2% in group 1 and 3.4%, 5.0% and 8.4% in group 2, respectively for 2001, 2011 and 2019. This trend towards increased prevalence of obesity in children from both the private and public sectors confirms the urgency in taking preventive measures to control not only obesity but its comorbidities such as DM.

Disclosure
A. Oliveira: None. F. Freitas: None. M. Clementino: None. L.G. Melo: None. D.C. Silva: None. P. Garcia: None. M. Correia: None. M. Mendes: None. M. Santos: None. A.A. Oliveira: None. T. Dechichi: None. A. Oliveira: None. A. Oliveira: None.
1267-P: Physical Fitness (PF), Weight Status, and Metabolic Risk in Japanese Adolescents
Authors: MORIKAWA SAKIKO Y. , FUJIHARA KAZUYA , NEDACHI RINA , IKEDA IZUMI , TAKEDA YASUNAGA , TAKEUCHI MIZUKI , HATTA MARIKO , ISHIGURO HAJIME , YAMADA TAKAHO , SONE HIROHITO 
Published: June 2020

Although cardiorespiratory fitness (CRF) and muscular fitness (MF) are modifiable factors for metabolic risk, the role of weight status in these factors has not been clarified in the pediatric population. We examined associations between metabolic indices and CRF or MF according to weight categories and compared the prevalence of metabolic abnormalities among four groups stratified by combinations of PF and weight categories. Cross-sectionally analyzed were 1744 Japanese adolescents aged 13-14 years. The PF test included measurements of CRF (20-m shuttle run test), upper-limb strength (handgrip test), lower limb strength (standing long jump test), and muscular endurance (sit-ups). Participants were classified as non-overweight (non-OW) or overweight/obese (OW) according to BMI cutoffs by the International Obesity Task Force. Metabolic risk was defined as ≥1 SD of the clustered metabolic risk (estimated by summing standardized sex-specific Z scores of HbA1c, MAP, and non-HDL-C). After adjusting for BMI and other characteristics, linear regression analysis showed that non-HDL-C was inversely associated with CRF in the non-OW group (P &lt;0.001) and with muscular endurance in the OW group (P = 0.002). In the OW group, coefficient of correlation showed that the clustered metabolic risk was slightly lower in those with higher sit-up scores even after adjusting for BMI and CRF (P = 0.06). As to the combination of weight status and PF, upper-limb strength or muscular endurance but not CRF were additively associated with metabolic risk; in comparison with the non-OW group in the second-lowest to highest quintiles, even the OW group in the second-lowest to highest quintiles of muscular endurance were 1.8 (1.1-2.8) times more likely to have metabolic risk while those in the lowest quintile had a 3.1 (1.7-5.7) greater likelihood.
In summary, relationships of metabolic risk with components of PF differed according to weight status. In OW adolescents, MF might be more useful for stratifying metabolic risk than CRF.

Disclosure
S.Y. Morikawa: None. K. Fujihara: None. R. Nedachi: None. I. Ikeda: None. Y. Takeda: None. M. Takeuchi: None. M. Hatta: None. H. Ishiguro: None. T. Yamada: None. H. Sone: Research Support; Self; Kyowa Hakko Kirin Co., Ltd., Novartis AG, Ono Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co.
1269-P: A Prospective, Population-Based Study of Hypothalamic Gliosis, Obesity, and Weight Gain in Children
Authors: SEWAYBRICKER LETICIA E. , MELHORN SUSAN J. , SCHUR ELLEN 
Published: June 2020

Hypothalamic gliosis is a cellular response that, in rodents, is necessary for weight gain and diet-induced obesity. Whether this inflammatory process in the mediobasal hypothalamus (MBH) plays a role in common obesity or change in weight status during growth and development in children is uncertain. Using T2-weighted MRI scans from a longitudinal population-based sample of young children, we measured signal ratios to evaluate evidence of MBH gliosis in relation to obesity and adiposity change over time. We included 169 children from 6 sites recruited as part of the NIH Adolescent Brain Cognitive Development (ABCD) study. Baseline T2-weighted MRI scans were analyzed for evidence of MBH gliosis based on the T2 intensity of the mean bilateral MBH/Amygdala signal ratio. Putamen/Amygdala was used as the control ratio. Models were adjusted for site, age, and sex. At baseline, mean age was 9.9 ± 0.6 y, 50% were female, and 64% were pre-pubertal. Mean BMI z-score was 0.77 ± 1.02 [23% with overweight (OV) and 21% with obesity (OB)]. At 1y assessments (10.8 mo. on average), mean ΔBMI z-score was 0.02 ± 0.36. MBH/Amygdala ratio was positively associated with BMI z-score (r=0.32, P&lt;0.001) and waist/height ratio (r=0.26, P&lt;0.001), a marker of metabolic risk, whereas the control ratio was not (r=-0.02, P=0.52 and r=-0.05, P=0.76). Overall, MBH/Amygdala ratio was not associated with ΔBMI z-score (r=-0.02, P=0.49), but a significant interaction [F(5,158)=5.16; P&lt;0.001] indicated the relationship varied by group. Among children with OV, baseline MBH/Amygdala ratio positively correlated with ΔBMI z-score (r=0.43, P=0.01); this relationship was attenuated in children with OB (r=0.19, P=0.18) and absent among participants of normal weight (r=-0.07, P=0.36).
In conclusion, we found evidence that MBH gliosis is associated with excess adiposity in a large pediatric population. In children at risk for obesity, MBH gliosis may be an important predictor of increasing adiposity and metabolic risk.

Disclosure
L.E. Sewaybricker: None. S.J. Melhorn: None. E. Schur: None.

Funding
National Institutes of Health (R01DK117623, U01DA041022, U01DA041028, U01DA041048, U01DA041089, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, U24DA041147, U01DA041093, U01DA041025)
1272-P: Diabetes Distress and Depressive Symptoms in Adolescents and Young Adults with Type 2 Diabetes
Authors: ROBERTS ALISSA J. , BAO HAO , QU PINGPING , KIM GRACE , YI-FRAZIER JOYCE , PIHOKER CATHERINE , MALIK FAISAL 
Published: June 2020

Objectives: To assess rates of depression and diabetes distress (DD) in adolescents and young adults (AYAs) with type 2 diabetes (T2D) overall and by sociodemographic factors.
Methods: AYAs with T2D ages 13-21 years seen in a pediatric diabetes clinic between March 2018 and June 2019 completed the Patient Health Questionnaire-9 (PHQ-9) for depression screening and the Problem Areas in Diabetes - teen version (PAID-T) survey to assess for DD. Rates of depression and DD were calculated using standard PHQ-9 and PAID-T cut-offs. Chi-square tests were used to assess whether rates of depression and DD were associated with participant characteristics.
Results: The sample consisted of 64 AYAs with T2D (58% female, mean age 15.8 ± 2.0 years, mean HbA1c 8.3% ± 2.6%, mean BMI z-score 2.2 ± 0.6, 59% on insulin). Twenty-two percent of participants reported moderate to high depressive symptoms and 9% endorsed self-harm on the PHQ-9. There were no differences in rates of depression by sociodemographic factors. Twenty-three percent of participants reported elevated DD. Rates of DD were higher among those on insulin (p=0.01) and on public health insurance (p=0.01) (Table1).
Conclusions: Almost 1 in 4 AYAs with T2D endorse depression and DD. Our findings support the importance of mental health screening in AYAs with T2D, as well as the need for strategies to address psychological comorbidities in this population.

Disclosure
A.J. Roberts: None. H. Bao: None. P. Qu: None. G. Kim: None. J. Yi-Frazier: None. C. Pihoker: None. F. Malik: None.

Funding
Seattle Children’s Hospital
1273-P: Growth Differentiation Factor 15 (GDF15) Is Associated with Nonalcoholic Fatty Liver Disease (NAFLD) in Obese Youth
Authors: GALUPPO BRITTANY , AGAZZI CRISTIANA , PIERPONT BRIDGET , SAMUELS STEPHANIE , TARABRA ELENA , CAPRIO SONIA , SANTORO NICOLA 
Published: June 2020

Growth differentiation factor 15 (GDF15) has been associated with many important biological functions, such as food intake and weight regulation in response to metabolic stress. In animal models, it has also been noted that it may play a role in the progression of nonalcoholic fatty liver disease (NAFLD), the leading cause of chronic liver disease in children. Nevertheless, the exact role of GDF15 in liver disease has yet to be elucidated. We aimed to explore the association of GDF15 with NAFLD in obese youth, and whether GDF15 changes similarly with changes in hepatic fat content (HFF%) over time. Fasting plasma GDF15 levels were measured by ELISA in obese youth with (89) and without (95) NAFLD. Additionally, fasting GDF15 levels were measured in 22 obese youth who progressed (11) or regressed (11) in HFF% by more than 30% over a two-year period. Abdominal MRI was performed on all subjects to quantify HFF%. For the first time, we describe a novel association between GDF15 and NAFLD in obese youth. Figure 1A shows a statistically significant difference in fasting GDF15 levels (p&lt;0.0001) between three groups stratified by degree of HFF%. Figure 1B shows a statistically significant association between change in HFF% and change in GDF15 (p=0.01; r2=0.29). These data suggest that GDF15 levels change with change in intrahepatic fat content in obese youth and may serve as a biomarker for NAFLD in children.

Disclosure
B. Galuppo: None. C. Agazzi: None. B. Pierpont: None. S. Samuels: None. E. Tarabra: None. S. Caprio: None. N. Santoro: None.
128-OR: The Ipswich Neurodiab Study: A 5-Year Longitudinal Study Examining Natural History of Diabetes Polyneuropathy (DPN)
Authors: SHARMA SANJEEV , CROSS JEN , VAS PRASH R. , RAYMAN GERRY 
Published: June 2020

This longitudinal, case-control study compares the progression of Small and Large Fibre Neuropathy (SFN and LFN respectively) in T1DM and T2DM and examines determinants of progression.
T1DM, T2DM and healthy controls (HC) groups each with 50 subjects were evaluated annually (2014-19). Functional SFN was assessed using the LDIFLARE test in the foot and structural SFN in the cornea [corneal nerve fibre density using confocal microscopy (CCMCNFD)]. LFN was assessed using vibration perception threshold (VPT) and sural nerve conduction velocity (SNCV) and amplitude (SNAP). At year 5 DPN was diagnosed if the Neurology Disability score (NDS) was ≥3 (DPN+).
Mean (±SD) age and sex distribution at baseline for T1DM was (41.4±15.0 yr; 27 males), T2DM (54.38±9.1; 25m) and HC (40.7±15.1; 24m).
T1DM with DPN+ had a significantly greater decline of LDIFLARE size compared to DPN- [0.15 v 0.08 cm2/yr; p=0.001] and of CCMCNFD (0.16v 0.10 fibres/mm2/yr; p=0.005).
In contrast in T2DM there was no difference between DPN+ and DPN- groups in LDIFLARE size (0.22v 0.15cm2/yr; p=0.09) and CCMCNFD (0.23v 0.16 fibres/mm2/yr; p=0.06).
Decline in small fibre function and structure in T1DM DPN- was no different from HCs. (LDIFLARE - 0.07cm2/yr; CCMCNFD - 0.05 fibres/mm2/yr) in contrast to all other groups.
In T1DM, the decline of LDIFLARE size and CCMCNFD correlated only with HbA1c change (p=&lt;0.05). In T2DM they correlated with HbA1c, triglycerides and BP changes (p=&lt;0.05).
There was no significant change of LFN indices (VPT, SNCV and SNAP; p=&gt;0.05) over the 5yrs.
This - the first longitudinal comparative study of changes in small fibre nerve structure and function in T1DM and T2DM - demonstrates changes in SFN in both groups that are not paralleled by changes in LFN, supporting the concept that SFN precedes LFN in DPN, It further demonstrates important differences in determinants of progression between T1DM and T2DM; the former being related to glycaemic control and the latter to multiple metabolic factors.

Disclosure
S. Sharma: None. J. Cross: None. P.R. Vas: None. G. Rayman: None.
1280-P: Improving Type 1 Diabetes (T1D) Prediction by Incorporating Growth Features into Landmark Models
Authors: LI ZHIGUO , ANAND VIBHA , DUNNE JESSICA L. , FROHNERT BRIGITTE I. , HAGOPIAN WILLIAM , HYOTY HEIKKI , MAZIARZ MARLENA , ZIEGLER ANETTE-GABRIELE , TOPPARI JORMA ,   T1DI STUDY
Published: June 2020

We explored the association between growth features and T1D development using landmark analysis at different ages. Analysis included individuals from 2 birth cohort studies: DAISY and BABYDIAB (n=2,664; 129 progressed to T1D). Using height and weight measured over time, percentiles for age were calculated. Missing values were imputed using LMS parameters of CDC growth charts. Rates of change of percentiles were computed over the prior year. Twelve ages (1-12 years) were used for landmark analysis with Random Survival Forest to predict probability of T1D onset in the 1- to 19-year follow up windows. The baseline model used HLA risk group, sex, T1D family history and breastfeeding history. The full model added growth features: height and weight percentiles at age and change in percentiles. Performance was measured using C-index and feature importance was ranked. Incorporating growth features significantly improved prediction accuracy of T1D onset for 95% of combinations of landmark ages and prediction window sizes (Table 1, not all ages and windows shown). The order of features from most to least predictive is: HLA group, rates of height and weight changes, height and weight percentiles, family history, breastfeeding and sex. This analysis demonstrates that using growth features can significantly improve prediction of T1D.
Table 1: C-Index with and without inclusion of growth features for landmark age of 3 years.

Disclosure
Z. Li: None. V. Anand: None. J.L. Dunne: None. B.I. Frohnert: None. W. Hagopian: Consultant; Self; Novo Nordisk Inc. H. Hyoty: None. M. Maziarz: None. A. Ziegler: None. J. Toppari: None.

Funding
JDRF (1-IND-2019-717-I-X, 1-SRA-2019-722-I-X, 1-SRA-2019-720-I-X, 1-SRA-2019-721-I-X, 1-SRA-2019-719-I-X, 1-SRA-2019-723-I-X)
1283-P: Multicenter Assessment of the Pancreas in Type 1 Diabetes (MAP-T1D)
Authors: VIROSTKO JOHN , WILLIAMS JONATHAN M. , HILMES MELISSA A. , DU LIPING , KANG HAKMOOK , RUSSELL WILLIAM E. , TRIOLO TAYLOR M. , PHILIPSON LOUIS H. , SIMS EMILY K. , EVANS-MOLINA CARMELLA , THOMAS HELEN E. , KAY THOMAS , GREELEY SIRI ATMA W. , STECK ANDREA , POWERS ALVIN C. , MOORE DANIEL J. 
Published: June 2020

Individuals both at risk for and newly diagnosed with type 1 diabetes (T1D) have a reduced pancreas volume as assessed by MRI. Furthermore, multiparametric quantitative MRI techniques have detected focal alterations in the T1D pancreas. However, performing quantitative MRI techniques in multi-site trials is challenging due to differences in MRI hardware and software. To determine if quantitative MRI measurements in T1D can be performed at different institutions, 5 academic centers (see author affiliation) have established the Multicenter Assessment of the Pancreas in T1D (MAP-T1D) group to develop harmonized MRI acquisition and image processing protocols. We established and implemented an MRI protocol for pancreas imaging on both Siemens and Philips MRI platforms at 5 imaging centers, consisting of T1- and T2-weighted anatomical images, diffusion-weighted MRI, magnetization transfer MRI, and longitudinal relaxation (T1) mapping. Imaging phantoms assessing volume, diffusion, magnetization transfer ratio, and T1 were created and imaged at each institution to test the reproducibility of multiparametric MRI. Measurement of phantom volume yielded an average error of 1.5% from the true volume. The apparent diffusion coefficient, magnetization transfer ratio, and T1 phantoms had coefficients of variation of 6.0%, 10.0%, and 9.5%, respectively, between sites. To assess the reproducibility of human MRI scanning, we recruited 5 healthy subjects to travel to 4 sites for imaging using the standardized MRI protocol. Pancreas volume measured at multiple sites had an average coefficient of variation between scans of 8.3% with a maximum difference of 17% (n = 9 MRIs). This study demonstrates the feasibility of quantitative pancreas MRI across multiple sites. Standardization of pancreas MRI acquisition and processing will accelerate integration of pancreas volume and other quantitative MRI measurements in future multi-center clinical trials of T1D.

Disclosure
J. Virostko: None. J.M. Williams: None. M.A. Hilmes: None. L. Du: None. H. Kang: None. W.E. Russell: None. T.M. Triolo: None. L.H. Philipson: None. E.K. Sims: None. C. Evans-Molina: Consultant; Self; Bristol-Myers Squibb. H.E. Thomas: None. T. Kay: None. S.W. Greeley: None. A. Steck: None. A.C. Powers: None. D.J. Moore: None.

Funding
JDRF (3-SRA-2019-759-M-B, 3-SRA-2015-102-M-B)
1286-P: Identification of Atypical Pediatric Diabetes Using Electronic Medical Records (EMR)
Authors: ASTUDILLO MARCELA , TOSUR MUSTAFA , SILLER ALEJANDRO F. , BALASUBRAMANYAM ASHOK , REDONDO MARIA J. 
Published: June 2020

We aimed to identify cases of rare or atypical pediatric diabetes who may be candidates for studies to understand their etiology and pathogenesis. We tested two strategies in a large pediatric hospital in Southwestern USA. STRATEGY 1: We designed a questionnaire that would allow a health-care provider to rule out typical diabetes types by manual EMR review. This questionnaire was first applied to the EMR of 50 youth (0-21 years old [y/o]) consecutively seen in the diabetes outpatient clinic, then modified to address problems identified, and tested in a second iteration, and on 50 additional cases (n=100). STRATEGY 2: In collaboration with local EMR analysts, we built three queries to generate periodic, automated reports of possible pediatric atypical diabetes cases: unknown type, type 2 diabetes (T2D) diagnosed &lt;10 y/o, and autoantibody-negative type 1 diabetes (T1D). Diabetes type (i.e., unknown, T1D or T2D) was determined by the treating pediatric endocrinologist, through a customized flowchart embedded in the EMR. STRATEGY 1: We found 6 cases (6%) of atypical diabetes (mean age at diagnosis 11 y/o [SD 2.64], 16.6% male, 33% non-Hispanic White [NHW] and 66.6% Hispanic [Hisp]). STRATEGY 2: Unknown diabetes type: 67 cases (15, out of 6676 total diabetes cases), with mean age at diagnosis 12.6 y/o (SD 3.3), 32.8% male, 23.8% NHW, 47.6% Hisp, 25.4% African-American (AA), 3.2% other. Out of 1142 children with T2D, 64 (6.6%) cases were diagnosed &lt;10 y/o, with mean age at diagnosis 8.6 y/o (SD 1.6), 20.3% male, 4.7% NHW, 65.6% Hisp, 28.1% AA, 1.6% other. Out of 680 cases of new onset T1D, 38 (5.6%) were negative for islet autoantibodies (IAA, GAD, IA-2), with mean age at diagnosis 11.3 y/o (SD3.8); 57.9% male, 50% NHW, 19.4% Hisp, 22.3% AA, 8.3% other. In sum, we designed and tested two strategies that use EMR to identify possible atypical pediatric diabetes cases for further studies that may shed light on the heterogeneity of pediatric diabetes, possibly opening new opportunities for diagnosis, treatment and prevention.

Disclosure
M. Astudillo: None. M. Tosur: None. A.F. Siller: None. A. Balasubramanyam: None. M.J. Redondo: None.
1294-P: Clinically Significant Hypoglycemia Is Rare in Youth with T1D during Partial Clinical Remission
Authors: ADDALA ANANTA , GU ANGELA , ZAHARIEVA DESSI , PRAHALAD PRIYA , BUCKINGHAM BRUCE A. , SCHEINKER DAVID , MAAHS DAVID M. 
Published: June 2020

Lower CGM glucose is typical after the diagnosis of T1D and the initiation of insulin treatment. Although ADA guidelines now state that glycemic targets can be lower during partial clinical remission (PCR), little guidance is offered on the optimal targets. We describe CGM glucose &lt;70 mg/dL for youth wearing CGM by PCR status. We reviewed 201 visits from 67 records; 55 visits in PCR as defined by insulin dose adjusted A1C value &lt;9 [(HbA1c at visit)*(4*units/kg/day)]. CGM data were collected 7 days before and after each visit. In multivariate regression, controlling for age, sex, and T1D duration, proportion of time spent &lt;70 mg/dL was calculated in a 24-hour period and at nighttime (midnight to 6am). Our cohort is 40% female, aged 9.4±4.7 years, with 92±11% wear time, and T1D duration of 126±105 days. Time spent between 54-70 mg/dL was statistically higher at nighttime for those in PCR and the time spent &lt;54 mg/dL was minimal for both (3.4±9.3 mins/24h, Table). There were no episodes of severe hypoglycemia. Clinically significant hypoglycemia (&lt;54 mg/dl) is rare. Furthermore, youth in PCR have time &lt;70 mg/dL similar to youth without T1D. A threshold alarm of 65 mg/dl may reduce hypoglycemia related alarms by 50% without increasing risk of severe hypoglycemia and warrants further study. These data support a trial of lower alarm thresholds for youth in PCR who wear CGM to avoid overtreatment of clinically insignificant lows.

Disclosure
A. Addala: None. A. Gu: None. D. Zaharieva: Speaker’s Bureau; Self; Ascensia Diabetes Care, Insulet Corporation, Medtronic. P. Prahalad: None. B.A. Buckingham: Advisory Panel; Self; ConvaTec Inc., Medtronic. Research Support; Self; Beta Bionics, Inc., Dexcom, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care. D. Scheinker: None. D.M. Maahs: Advisory Panel; Self; Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S. Consultant; Self; Abbott, Sanofi. Research Support; Self; Bigfoot Biomedical, Dexcom, Inc., Roche Diabetes Care, Tandem Diabetes Care.