bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sleep Quality and Heart Rate Variability in Adolescents with Type 1 or Type 2 Diabetes
Authors: FAULKNER MELISSA S. , HELVIG ASHLEY 
Published: June 2018

Regardless of the type of diabetes, there is twice the risk of experiencing cardiovascular (CV) disease complications in comparison to not having the disease. Although these complications and associated symptoms are rarely noted in adolescents with diabetes, early identification of biobehavioral markers for CV risks are essential for targeted approaches for prevention of later disease sequelae. Decreased sleep quality and heart rate variability (HRV) have both independently been associated with diabetes or the presence of obesity and risk for developing diabetes, as well as with CV disease. Studies exploring both sleep quality and HRV in adolescents with diabetes are not available. Thus, we conducted a secondary analysis of data from an existing study to examine differences in sleep quality and HRV in adolescents with type 1 (T1D) vs. type 2 diabetes (T2D); and to determine if there were associations between HRV and sleep quality. Adolescents with T1D (n = 101; 56 males) or T2D (n= 37; 16 males) completed 24-hour HRV Holter monitoring and measurement using Burdick Vision Premier™ ECG Analysis and Editing software system (Waukesha, WI), hemoglobin A1c (HbA1c) using the Abbott IMx® assay method, and a self-report global measure of the impact of diabetes on their sleep quality using a 5-point Likert scale. Duration of diabetes was greater (P \ .001) and measures of HRV were higher in T1D (P \ .01); BMI and BMI z-scores (P \ .001) and systolic and diastolic BP (P ≤ .05) were higher in T2D. No differences in recent or average HbA1c, Tanner staging or sleep quality were found. Both spectral and time domain measures of HRV were associated with sleep quality in T2D (r = - .51 to -.38, P \ .02); only time domain measures were associated with sleep quality in T1D (r = -. 21 to -.19, P ≤ .05). Poorer sleep quality was evident in those with lower HRV; these linkages were stronger in those with T2D. Further study is warranted to elucidate risks and improve sleep quality and CV outcomes in youth with diabetes.

Disclosure
M.S. Faulkner: None. A. Helvig: None.
Glycemic Variability from CGM Correlates with Indices of Glucose Metabolism in Healthy Obesity but Not in Type 2 Diabetes
Authors: ELSHAFIE AHMED , LAM WAI , PARIKH LISA , RANGEL ELIZABETH SANCHEZ , SCHMIDT CHRISTIAN P. , HWANG JANICE , YECKEL CATHERINE W. , SHERWIN ROBERT , BELFORT-DEAGUIAR RENATA 
Published: June 2018

We evaluated the relationship between measurements of beta cell function and insulin resistance assessed from OGTT and 2-step glucose clamp data with indices of glucose variability (GV) obtained with a continuous glucose monitor (CGM) in obese subjects with and without type 2 diabetes (T2D). 17 healthy obese (OB) (FPG 91 ± 4.9mg/dl and A1c 5.2 ± 0.4%) and 8 age- and weight-matched participants with T2D treated with diet and/or metformin (FPG 131.5 ± 42.8 mg/dl and A1c 6.8 ± 0.8%) wore CGM (Dexcom®) for up to 5 days. EasyGV® software was used to calculate indices of GV: standard deviation (SD), mean amplitude of glycemic excursions (MAGE), J-Index, continuous overlapping net glycemic action (CONGA), and Glycemic Risk Assessment in Diabetes Equation (GRADE). Indices of glucose metabolism were determined with a 2 hour OGTT and a two-step hyperglycemic-euglycemic clamp. Insulin levels during the hyperglycemic-step of clamp (116 ± 126 vs. 40 ± 23 mU/mL) were equal in both groups, while glucose infusion rate (GIR) (7.7 ± 3.1 vs. 3.9 ± 2.4 mg/kg/minutes) during euglycemia was as expected significantly lower in the T2D subjects compared to OB subjects. GV indices (SD, CONGA, J-Index, GRADE) were statistically lower in OB vs. T2D (P&lt;0.05). Insulin Sensitivity Index (ISI0-120) and the insulin secretion-sensitivity index-2 (ISSI-2) were also lower in obese than in T2D subjects (P&lt;0.001). CGM indices (mean, CONGA, J-index, and GRADE) correlated with incremental AUC of insulin during the OGTT, but not for glucose; as well as insulin levels during the hyperglycemic-step (r=0.740, P&lt;0.01), and GIR during the euglycemic step of the clamp (r= -0.733, P&lt;0.01). CGM measures of GV (CONGA, J-Index, and GRADE) were lower in obese compared to T2D subjects. These results suggest that GV indices are surrogate measurements of beta cell function and insulin action in obese subjects, and may help determine progression to T2D.

Disclosure
A. Elshafie: None. W. Lam: None. L. Parikh: None. E. Sanchez Rangel: None. C.P. Schmidt: None. J. Hwang: None. C.W. Yeckel: None. R. Sherwin: Other Relationship; Self; QuintilesIMS, MannKind Corporation. Research Support; Self; Regeneron Pharmaceuticals, Inc.. Other Relationship; Self; ICON plc. R. Belfort-DeAguiar: Research Support; Self; GlaxoSmithKline plc..
Diabetic Complications Associated with Poor Sleep Quality in Type 2 Diabetes
Authors: CHOI DUGHYUN , KIM BO-YEON , JUNG CHAN-HEE , KIM CHUL-HEE , KANG SUNG-KOO , MOK JI-OH 
Published: June 2018

Purpose: Metabolic disorders are known to cause poor sleep quality. However, there is not much research about the association of diabetic complications and poor sleep quality. Our aim was to find out which diabetic complications are associated with poor sleep quality in type 2 diabetes (T2D).
Methods: In this cross-section study, sleep quality of 151 T2D patients were assessed by using the Pittsburgh Sleep Quality Index (PSQI) questionnaire. PSQI score was interpreted as good sleep quality for ≤ 5 and poor sleep quality for &gt; 5. Microvascular complications were assessed with the presence of diabetic retinopathy, diabetic polyneuropathy (DPN) and microalbuminuria. Macrovascular complications were assessed with ankle-brachial index, pulse wave velocity, and carotid intima-media thickness.
Results: Fasting c-peptide, insulin, triglyceride (TG) and waist-hip ratio (WHR) were higher in the poor sleep quality group. Among the complications, the proportion of DPN was higher in the poor sleep quality group (31.7% vs. 15.2%, p=0.020). Other diabetic complications did not show a significant difference between both groups (Table). After adjustment for sex, age, usage of insulin, TG, WHR and DPN, fasting c-peptide was the only significant marker for poor sleep quality in T2D (OR = 2.207, p = 0.048).
Conclusion: DPN was higher in the poor sleep quality group. Other diabetic complications showed no significant difference in both groups.

Disclosure
D. Choi: None. B. Kim: None. C. Jung: None. C. Kim: None. S. Kang: None. J. Mok: None.
Cognitive Function Is Impaired in Recently Diagnosed Type 2 Diabetes, but Not in Type 1 Diabetes
Authors: VAN GEMERT THERESA , WÖLWER WOLFGANG , WEBER KATHARINA S. , HOYER ANNIKA , STRASSBURGER KLAUS , BOHNAU NORA T. , BRÜGGEN MARIE , OVELGOENNE KATHARINA , GÖSSMANN EVA-MARIA , BURKART VOLKER , SZENDROEDI JULIA , RODEN MICHAEL , MÜSSIG KARSTEN 
Published: June 2018

Diabetes associates with higher risk of dementia. We hypothesized that cognitive function is already impaired during the early course of diabetes. Thus, we performed a cross-sectional analysis within the German Diabetes Study including patients within the first year after diagnosis of type 1 (n=82) or type 2 (n=119) diabetes, patients with type 1 (n=45) or type 2 (n=65) diabetes five years after study inclusion and metabolically healthy humans (n=42). Participants underwent comprehensive metabolic phenotyping and testing of different domains of cognitive function. Cognition test outcomes were compared using linear regression models with age, sex, and crystallized intelligence as independent variables. Furthermore, within the groups, associations between cognitive function and age, sex, body mass index (BMI), insulin sensitivity, high-sensitivity C-reactive protein, hemoglobin A1c, and crystallized intelligence were studied using linear regression analysis. In participants with recently diagnosed diabetes, verbal memory was poorer in patients with type 2 diabetes (P=0.029), but not in type 1 diabetes (P=0.154) when compared to healthy individuals. Five years after diagnosis, type 2 diabetes patients also showed decreased verbal memory than those with type 1 diabetes (P=0.013). In addition to crystallized intelligence, a higher BMI among individuals with recently diagnosed type 2 and male sex among individuals with recently diagnosed type 1 diabetes were associated with impaired verbal memory (all P&lt;0.05).
In conclusion, verbal memory is impaired in individuals with recently diagnosed type 2 diabetes and likely associated with higher body mass.

Disclosure
T. van Gemert: None. W. Wölwer: None. K.S. Weber: None. A. Hoyer: None. K. Strassburger: None. N.T. Bohnau: None. M. Brüggen: None. K. Ovelgoenne: None. E. Gössmann: None. V. Burkart: None. J. Szendroedi: None. M. Roden: Speaker's Bureau; Self; Boehringer Ingelheim GmbH. Research Support; Self; Boehringer Ingelheim GmbH. Consultant; Self; Poxel SA. Research Support; Self; Danone Nutricia Early Life Nutrition, GlaxoSmithKline plc., Nutricia Advanced Medical Nutrition, Sanofi. K. Müssig: None.
Impact of rtCGM Usage on a Combined Patient Reported Outcome—A Post-Hoc Analysis of the HypoDE Study
Authors: EHRMANN DOMINIC , HEINEMANN LUTZ , FRECKMANN GUIDO , WALDENMAIER DELIA , HERMANNS NORBERT 
Published: June 2018

The HypoDE study, a randomized multi-center trial, showed that rtCGM use reduces the number of low glucose events (&lt;55 mg/dl for at least 20 min) per 28 days significantly from 10.4 to 3.4 events compared to SMBG (13.5 to 13.2 events) in MDI-treated type 1 diabetic patients with hypoglycemia problems. We analyzed the impact of rtCGM use on patient-reported-outcomes (PRO). A combined PRO consisting of a specific measure of satisfaction with glucose monitoring (GMSS), a diabetes-specific assessment (DDS) and a generic measure (EQ-5D) was used. In a factor analysis, all three scales loaded on one factor. All questionnaire scores were z-transformed as well as the number of low glucose events. The figure shows the effect sizes of the combined PRO and the single scores as well as of the low glucose events. There was a significant positive impact of rtCGM use on the combined PRO. However, only GMSS but not DDS or EQ-5D showed a significant impact. The more device-specific the PRO, the higher was the effect size. Interestingly, the impact of rtCGM use on biochemical hypoglycemia had a remarkably larger effect size than the combined PRO. Since most other rtCGM studies are powered to detect a benefit in glycemic endpoints and not in PRO, the lower impact of rtCGM on PRO is a barrier to prove the efficacy of rtCGM on PRO like quality of life, diabetes distress or satisfaction with treatment.

Disclosure
D. Ehrmann: Speaker's Bureau; Self; Berlin-Chemie AG. L. Heinemann: Stock/Shareholder; Self; Profil Institute for Metabolic Research, ProSciento. Consultant; Self; Roche Diabetes Care Health and Digital Solutions. G. Freckmann: Speaker's Bureau; Self; Ascensia Diabetes Care. Research Support; Self; Ascensia Diabetes Care. Speaker's Bureau; Self; Roche Diabetes Care Health and Digital Solutions. Advisory Panel; Self; Roche Diabetes Care Health and Digital Solutions. Research Support; Self; Roche Diabetes Care Health and Digital Solutions. Advisory Panel; Self; Abbott, Novo Nordisk Inc.. Consultant; Self; Sensile Medical AG. Speaker's Bureau; Self; Ypsomed AG. D. Waldenmaier: None. N. Hermanns: Speaker's Bureau; Self; Berlin-Chemie AG. Advisory Panel; Self; Abbott. Research Support; Self; Abbott. Speaker's Bureau; Self; Abbott. Research Support; Self; Berlin-Chemie AG. Advisory Panel; Self; Eli Lilly and Company. Speaker's Bureau; Self; Eli Lilly and Company. Advisory Panel; Self; Roche Diabetes Care Health and Digital Solutions. Research Support; Self; Ypsomed AG, Dexcom, Inc.. Speaker's Bureau; Self; Novo Nordisk Inc..
Impact of Diabetes-Related Distress on Predicted Cardiovascular Complications in Patients with Type 2 Diabetes
Authors: YOUNG CLIPPER , DUGAN JOY A. , RAY ANDREW J. , SHUBROOK JAY H. 
Published: June 2018

Objective: To evaluate the impact of diabetes-related distress along with other cardiovascular risk factors on the predicted 10-year cardiovascular complication risks in patients with type 2 diabetes
Methods: This cross-sectional study involved Problem Areas in Diabetes (PAID) questionnaire and UK Prospective Diabetes Study (UKPDS) Risk Engine 2.0, surveying a population with lower socioeconomic status and type 2 diabetes. Statistical analyses incorporated multiple linear regression models, comprising of the predicted cardiovascular risks, PAID scores, tobacco use, gender, age, LDL levels, clinically documented depression status, BMI, and systolic blood pressure.
Results: Results are organized by statistical models (driven by risk factors for cardiovascular conditions) and the predicted, individual 10-year cardiovascular complication risks vs. PAID scores.
Conclusion: This study found an association between psychosocial status and cardiovascular disease risk management in lower socioeconomic patients with type 2 diabetes. Within all the multiple linear regression models, the levels of diabetes-related distress have been shown to impact the predicted fatal coronary heart disease risks, thus allowing this distress to predict such cardiovascular risk after including certain risk factors.
Coefficientp-value95% CIDepression Status, Tobacco Use, LDL Levels, Gender, AgePredicted Coronary Heart Disease Risks vs. PAID Scores0.0770.039(0.0039 – 0.15)Predicted Fatal Coronary Heart Disease Risks vs. PAID Scores0.0700.014(0.014 – 0.13)Predicted Stroke Risks vs. PAID Scores0.0160.38(-0.020 – 0.053)Predicted Fatal Stroke Risks vs. PAID Scores0.00170.62(-0.0050 – 0.0084)Systolic Blood Pressure, Tobacco Use, LDL Levels, Gender, AgePredicted Coronary Heart Disease Risks vs. PAID Scores0.0680.069(-0.0054 – 0.14)Predicted Fatal Coronary Heart Disease Risks vs. PAID Scores0.0630.029(0.0066 – 0.12)Predicted Stroke Risks vs. PAID Scores0.0150.388(-0.019 – 0.049)Predicted Fatal Stroke Risks vs. PAID Scores0.00190.495(-0.0036 – 0.0075)BMI, Tobacco Use, LDL Levels, Gender, AgePredicted Coronary Heart Disease Risks vs. PAID Scores0.0660.072(-0.0061 – 0.14)Predicted Fatal Coronary Heart Disease Risks vs. PAID Scores0.0610.032(0.0053 – 0.12)Predicted Stroke Risks vs. PAID Scores0.0110.52(-0.024 – 0.047)Predicted Fatal Stroke Risks vs. PAID Scores0.000880.79(-0.0056 – 0.0073)

Disclosure
C. Young: None. J.A. Dugan: None. A.J. Ray: None. J.H. Shubrook: Advisory Panel; Self; Eli Lilly and Company, Novo Nordisk Inc., Intarcia Therapeutics, Inc..
Increasing Daily Step Count Results in an Improvement in BMI and Aortic Blood Pressure in Patients with Type 2 Diabetes Mellitus
Authors: SEOW CHERNGJYE , XIA LIAN , TAN JANET S. , TANG XIN , SUN BING , DALAN RINKOO 
Published: June 2018

Background: We investigated whether increasing daily steps by 3000 improves glycemic indices (HbA1c and glycemic variability), cardiometabolic risk factors (BMI, blood pressure (BP) and lipids) and aortic stiffness in middle-aged Chinese men with type 2 diabetes mellitus (T2DM).
Methods: In this 12 weeks, pre and post intervention, prospective study, 20 chinese men (40-70 years old; baseline HbA1c 7-10%) with T2DM were recruited. They were on stable therapeutic regime and had no preexisting macrovascular complications. Measurements included glycemic profile (HbA1c, CGMS (Medtronics iPro)), BMI, BP, fasting lipids, aortic BP and stiffness (SphygmoCor Xcel) and daily steps (pedometer). The intervention was to increase the daily step count by 3000/day. We compared group 1 who achieved an increase of &gt;3000 steps/day (N=7) with group 2 who failed to achieve target (N=11). All comparisons were performed using Student’s independent t test.
Results: We found that compared to Group 2, Group 1 had a significant improvement in BMI (-1.14 vs. +0.11), aortic systolic (-1.38 vs. +6.58mmHg) and diastolic (-4.63 vs. +4.08mmHg) BP(p&lt;0.05). Interaction analysis showed that in patients who had an improvement in BMI, there was a significant improvement in HbA1c (β=0.57, p=0.041). Changes in indices of glycemic variability were not significantly different between the two groups.
Conclusion: Increasing step counts by more than 3000 steps/day resulted in improvement in BMI and aortic BP with an interactive improvement in HbA1c in the long term. Further studies with a larger sample size and a longer follow-up are needed to confirm our findings.

Disclosure
C. Seow: None. L. Xia: None. J.S. Tan: None. X. Tang: None. B. Sun: None. R. Dalan: None.
From Research to Action—Impactful Intervention Arenas
Authors: DAVID NAPIER A. , LUND NIELS , BAGGER MALENE , JENSEN BJARNE B. 
Published: June 2018

More than half the world’s population lives in cities and two thirds of 425 million people with diabetes live in cities. That makes cities a focal point for tackling diabetes. As part of Cities Changing Diabetes (CCD) five diverse cities (Copenhagen, Houston, Mexico City, Shanghai, Tianjin) have implemented actions based on 740 individual interviews with people with type 2 diabetes or at increased risk of developing it. Based on participants’ perspectives on socio-cultural barriers to live a healthy life action plans were created relevant to the local diabetes challenge and city context and tailor-made interventions were designed. CCD is a partnership between Novo Nordisk A/S, University College London, and Steno Diabetes Center Copenhagen aiming to map the diabetes challenge, understand risk and vulnerability to type 2 diabetes, and design interventions tailor-made to the respective city context. In the cities the program is driven by local partnerships in a collaborative working approach bringing together city governments, academics, businesses, city planners, patient organizations, faith-based organizations, and other non-governmental organizations. The research insights led to four arenas for impactful interventions: Health promoting policies by incorporating awareness and understanding of type 2 diabetes into local policies to address the diabetes challenge and improve overall health. Urban planning by integrating health-promoting aspects such as walkability and bikeability in urban planning to increase the ability to live a healthy life. Community involvement by strengthening communities around citizens vulnerable to diabetes to build resilience, improve diabetes care and quality of life. Health system strengthening by building capacity into the local healthcare system to help vulnerable citizens to access it.
In conclusion, insights from the research have directly guided development of city-specific tailor-made interventions within four arenas.

Disclosure
A. Napier: Consultant; Self; Novo Nordisk A/S. N. Lund: Employee; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk A/S. M. Bagger: Employee; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk A/S. Stock/Shareholder; Spouse/Partner; Novo Nordisk A/S. B.B. Jensen: None.
Clinical Experience with the MiniMed 670G System in Children, Adolescents, and Young Adults with Type 1 Diabetes
Authors: HENSON CARLO J. , BARNES TIMOTHY L. , NICKEL AMANDA J. , JENNIFER ABUZZAHAB M. , KYLLO JENNIFER , GANDRUD LAURA M. 
Published: June 2018

Objective: To compare measured HbA1c, estimated HbA1c, and percent time in range before and after the initiation of the Minimed 670G system in children and young adults with type 1 diabetes (T1D).
Methods: Data consisted of 67 T1D patients, aged 5-23 years, who started the MiniMed 670G system and were followed for at least 12 weeks. Data were analyzed at baseline and 2, 4, 8, and 12 weeks following Auto Mode start. Paired t tests and linear mixed regression models were used to evaluate the effect of time on percent of time in Auto Mode, percent of time in range (70-180 mg/L) and changes in most recently measured HbA1c and sensor estimated HbA1c.
Results: Fifteen percent of patients (n=10) were aged 5-9 years, 27% (n=18) were 10-13 years, 30% (n=20) were 14-17 years and 28% (n=19) were ≥ 18 years; average duration of T1D was 5.47 ± 4.26 years. Nearly 96% of patients were Caucasian; 54% were male. Estimated HbA1c levels decreased from 8.10% ± 1.26% at baseline to 7.51% ± 0.88% at 12 weeks (P&lt;0.0001). Measured HbA1c decreased from 7.98% ± 1.03% to 7.73% ± 1.03% (P=0.0008) (Figure 1). Percent time in range increased from 50% at baseline to 61% at 12 weeks (P&lt;0.0001), without significant change in time below range. Time in Auto Mode declined from 75.1% at start to 68.4% at 12 weeks (P=0.0015).
Conclusion: Initiation of the 670G system in a clinical setting led to improved glycemic control in children, adolescents, and young adults.

Disclosure
C.J. Henson: None. T.L. Barnes: None. A.J. Nickel: None. M. Abuzzahab: Research Support; Self; Ascendis, Genentech, Inc., Novo Nordisk Inc.. Speaker's Bureau; Self; Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc., Pfizer Inc.. Research Support; Self; Versartis, Inc., Medtronic. Advisory Panel; Self; Sandoz. J. Kyllo: None. L.M. Gandrud: Consultant; Self; UnitedHealth Group.
A Content Analysis of Text Messages in a Type 1 Diabetes Peer Mentoring Program—The Importance of Shared Interests
Authors: WALKER ASHBY F. , JOHNSON CATHRYN , ANEZ-ZABALA CLAUDIA , DORVIL SARAH R. , HALLER MICHAEL J. , GURKA MATTHEW J. , BRUGGEMAN BRITTANY S. , GUIFFRE DANIELLE , ATKINSON MARK A. , SCHATZ ILYSSA , SCHATZ DESMOND 
Published: June 2018

A paucity of research exists regarding the feasibility of utilizing personalized, live-texting as outreach to improve health outcomes for low-income teenagers with type 1 diabetes (T1D). A peer mentoring program pairing college students with T1D with publicly insured teens ages 11-17 with T1D (gender matched) was piloted with the aim of improving outcomes for both groups (n=88; 44 control and 44 treatment). The program involved social events, clinic visits, automated daily texts for blood glucose monitoring (BGM), and weekly text exchanges. For consistency, mentors were trained in protocols for texts using a technique of reciprocal sharing and limited to one text exchange with their mentee a week at a time of day agreed on by parents. Mentors, mentees and parents were aware that all texts were monitored by study staff through IRB-approved processes. A content analysis of all texts for a 12-week period was conducted (47,475 words) using six coders with schemata that included presence/absence variables (e.g., did the mentor prompt for BGM), numeric variables (word counts), and categorical variables (major themes discussed). Texts included poignant examples of uninhibited sharing about daily life and excellent coaching by mentors. However, pairs that talked about a shared common interest outside of T1D used far more words about diabetes-specific and non-specific topics (both were athletes, both enjoyed drawing, shared an ethnic identity, etc.). Mean word use for pairs with a common interest was 2,902 compared to 1,537 with no common interest (p=.01; t-test). For mentors, as word use increased in texts there was a greater improvement in HbA1c (r = -.54, p=.03; Pearson’s correlation). This pilot study shows the feasibility of using texting in peer mentoring programs and reiterates the importance of finding common ground beyond T1D to facilitate rapport building. Additional efforts are needed to better explicate the role of shared interests in outcomes for peer mentoring programs.

Disclosure
A.F. Walker: None. C. Johnson: None. C. Anez-Zabala: None. S.R. Dorvil: None. M.J. Haller: None. M.J. Gurka: None. B.S. Bruggeman: None. D. Guiffre: None. M.A. Atkinson: Other Relationship; Self; Patent Issued. I. Schatz: None. D. Schatz: None.