The association of self-reported sleep and circadian measures with glycemic control and diabetes complications among young adults with type 2 diabetes.

We aim to examine the association of sleep duration, sleep quality, late chronotype, and circadian misalignment with glycemic control and risk of complications in young adults with youth-onset type 2 diabetes followed in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study. Self-reported sleep duration, quality, timing, and circadian misalignment were assessed via a modified Pittsburgh Sleep Quality Index (PSQI) questionnaire, and chronotype was assessed via the Morningness-Eveningness Questionnaire (MEQ). We examined diabetes complications including loss of glycemic control (defined as hemoglobin A1c ≥8%), hypertension, dyslipidemia, albuminuria, and diabetic peripheral neuropathy. Multivariable logistic regression models were constructed to assess associations between sleep and circadian measures with outcomes of interest, such as loss of glycemic control and diabetes complications. A total of 421 participants (34.2% male), mean age 23.6 ± 2.5 yr, mean body mass index (BMI) of 36.1 ± 8.3 kg/m2, and mean diabetes duration of 10.0 ± 1.5 yr were evaluated. Self-reported short sleep duration, daytime sleepiness, and sleep quality were not associated with loss of glycemic control or diabetes complications. Late self-reported bedtime (after midnight) on work/school nights, rather than self-expressed chronotype or circadian misalignment, was independently associated with loss of glycemic control. An association was seen between late bedtimes and albuminuria but was attenuated after adjusting for depression. In conclusion, late bedtime on work/school days, rather than short sleep duration, daytime sleepiness, or poor sleep quality, was independently associated with loss of glycemic control in this longitudinal cohort of young adults with youth-onset type 2 diabetes.NEW & NOTEWORTHY The prevalence of type 2 diabetes in youth is increasing at an alarming rate. Identifying potentially modifiable factors modulating glycemic control is critically important to reduce micro and macrovascular complications. In a large cohort of youth-onset type 2 diabetes, self-reported late bedtime on work/school days was independently associated with loss of glycemic control in this longitudinal cohort of young adults with youth-onset type 2 diabetes.

Characteristics of Type 2 Diabetes in Female and Male Youth.

The incidence of type 2 diabetes in children is rising and carries a worse prognosis than in adults. The influence of sex on pediatric type 2 diabetes outcomes has not been well investigated. We studied 715 youth with type 2 diabetes diagnosed at a median age of 13.7 years and compared sex differences in demographic, clinical, and laboratory characteristics within the first year of diagnosis. Females diagnosed with type 2 diabetes were younger and at a higher stage of pubertal development than males, yet presented with lower A1Cs, a lower prevalence of diabetic ketoacidosis, and higher HDL cholesterol levels.

CGM Metrics Identify Dysglycemic States in Participants From the TrialNet Pathway to Prevention Study.

OBJECTIVE: Continuous glucose monitoring (CGM) parameters may identify individuals at risk for progression to overt type 1 diabetes. We aimed to determine whether CGM metrics provide additional insights into progression to clinical stage 3 type 1 diabetes. RESEARCH DESIGN AND METHODS: One hundred five relatives of individuals in type 1 diabetes probands (median age 16.8 years; 89% non-Hispanic White; 43.8% female) from the TrialNet Pathway to Prevention study underwent 7-day CGM assessments and oral glucose tolerance tests (OGTTs) at 6-month intervals. The baseline data are reported here. Three groups were evaluated: individuals with 1) stage 2 type 1 diabetes (n = 42) with two or more diabetes-related autoantibodies and abnormal OGTT; 2) stage 1 type 1 diabetes (n = 53) with two or more diabetes-related autoantibodies and normal OGTT; and 3) negative test for all diabetes-related autoantibodies and normal OGTT (n = 10). RESULTS: Multiple CGM metrics were associated with progression to stage 3 type 1 diabetes. Specifically, spending ≥5% time with glucose levels ≥140 mg/dL (P = 0.01), ≥8% time with glucose levels ≥140 mg/dL (P = 0.02), ≥5% time with glucose levels ≥160 mg/dL (P = 0.0001), and ≥8% time with glucose levels ≥160 mg/dL (P = 0.02) were all associated with progression to stage 3 disease. Stage 2 participants and those who progressed to stage 3 also exhibited higher mean daytime glucose values; spent more time with glucose values over 120, 140, and 160 mg/dL; and had greater variability. CONCLUSIONS: CGM could aid in the identification of individuals, including those with a normal OGTT, who are likely to rapidly progress to stage 3 type 1 diabetes.

Detection of Hypoglycemia and Hyperglycemia Using Noninvasive Wearable Sensors: ECG and Accelerometry.

BACKGROUND: Monitoring glucose excursions is important in diabetes management. This can be achieved using continuous glucose monitors (CGMs). However, CGMs are expensive and invasive. Thus, alternative low-cost noninvasive wearable sensors capable of predicting glycemic excursions could be a game changer to manage diabetes. METHODS: In this article, we explore two noninvasive sensor modalities, electrocardiograms (ECGs) and accelerometers, collected on five healthy participants over two weeks, to predict both hypoglycemic and hyperglycemic excursions. We extract 29 features encompassing heart rate variability features from the ECG, and time- and frequency-domain features from the accelerometer. We evaluated two machine-learning approaches to predict glycemic excursions: a classification model and a regression model. RESULTS: The best model for both hypoglycemia and hyperglycemia detection was the regression model based on ECG and accelerometer data, yielding 76% sensitivity and specificity for hypoglycemia and 79% sensitivity and specificity for hyperglycemia. This had an improvement of 5% in sensitivity and specificity for both hypoglycemia and hyperglycemia when compared with using ECG data alone. CONCLUSIONS: Electrocardiogram is a promising alternative not only to detect hypoglycemia but also to predict hyperglycemia. Supplementing ECG data with contextual information from accelerometer data can improve glucose prediction.

Safety and Glycemic Outcomes With a Tubeless Automated Insulin Delivery System in Very Young Children With Type 1 Diabetes: A Single-Arm Multicenter Clinical Trial.

OBJECTIVE: Very young children with type 1 diabetes often struggle to achieve glycemic targets, putting them at risk for long-term complications and creating an immense management burden for caregivers. We conducted the first evaluation of the Omnipod 5 Automated Insulin Delivery System in this population. RESEARCH DESIGN AND METHODS: A total of 80 children aged 2.0-5.9 years used the investigational system in a single-arm study for 13 weeks following 14 days of baseline data collection with their usual therapy. RESULTS: There were no episodes of severe hypoglycemia or diabetic ketoacidosis. By study end, HbA1c decreased by 0.55% (6.0 mmol/mol) (P < 0.0001). Time with sensor glucose levels in target range 70-180 mg/dL increased by 10.9%, or 2.6 h/day (P < 0.0001), while time with levels <70 mg/dL declined by median 0.27% (P = 0.0204). CONCLUSIONS: Use of the automated insulin delivery system was safe, and participants experienced improved glycemic measures and reduced hypoglycemia during the study phase compared with baseline.

Here for You: A Review of Social Support Research in Young Adults With Diabetes.

Living with and managing diabetes is challenging during young adulthood, and social support may help relieve or minimize the burdens young adults with diabetes experience. This article reviews the types and sources of support young adults with diabetes receive and their associations with behavioral, psychosocial, and glycemic outcomes. Intervention research integrating social support and future directions for care are discussed.

Type 2 diabetes in prepubertal children.

OBJECTIVE: Puberty-induced insulin resistance is considered critical in the pathogenesis of type 2 diabetes (T2D) in youth. The development of T2D before puberty suggests distinct risk factors and pathophysiology but, because of its rarity, this has not been well studied. We aimed to describe the clinical characteristics of children with T2D diagnosed before the onset of puberty. RESEARCH DESIGN AND METHODS: We retrospectively studied all children with autoantibody-negative T2D and available pubertal development assessment seen at our center between July 2016 and July 2019, and compared characteristics of those at Tanner stage I (prepubertal, n = 35) versus those at Tanner II-V of pubertal development (n = 341). RESULTS: At T2D diagnosis, prepubertal children compared with those at Tanner II-V had higher body mass index z-score (p = 0.003) and higher C-peptide (p = 0.003) (while glucose levels were not significantly different), with differences retaining significance after adjustment for glucose, race/ethnicity and sex. Dyslipidemia occurred in 100% of prepubertal children versus 89.7% of those diagnosed later (p = 0.036). Of the prepubertal children diagnosed under age 10 (n = 13), 69.2% were female, 100% racial/ethnic minority, 100% had obesity with history of dyslipidemia and none with diabetic ketoacidosis. CONCLUSIONS: T2D, although rarely, can develop before puberty. Children with T2D diagnosed in the prepubertal period have more severe obesity, greater insulin resistance, and more frequent dyslipidemia than older youth. These findings suggest that children with prepubertal T2D are at increased risk for associated morbidity compared with older youth and underscore the significance of interventions to prevent and treat obesity in early childhood.

Improved Low-Glucose Predictive Alerts Based on Sustained Hypoglycemia: Model Development and Validation Study.

BACKGROUND: Predictive alerts for impending hypoglycemic events enable persons with type 1 diabetes to take preventive actions and avoid serious consequences. OBJECTIVE: This study aimed to develop a prediction model for hypoglycemic events with a low false alert rate, high sensitivity and specificity, and good generalizability to new patients and time periods. METHODS: Performance improvement by focusing on sustained hypoglycemic events, defined as glucose values less than 70 mg/dL for at least 15 minutes, was explored. Two different modeling approaches were considered: (1) a classification-based method to directly predict sustained hypoglycemic events, and (2) a regression-based prediction of glucose at multiple time points in the prediction horizon and subsequent inference of sustained hypoglycemia. To address the generalizability and robustness of the model, two different validation mechanisms were considered: (1) patient-based validation (model performance was evaluated on new patients), and (2) time-based validation (model performance was evaluated on new time periods). RESULTS: This study utilized data from 110 patients over 30-90 days comprising 1.6 million continuous glucose monitoring values under normal living conditions. The model accurately predicted sustained events with >97% sensitivity and specificity for both 30- and 60-minute prediction horizons. The false alert rate was kept to <25%. The results were consistent across patient- and time-based validation strategies. CONCLUSIONS: Providing alerts focused on sustained events instead of all hypoglycemic events reduces the false alert rate and improves sensitivity and specificity. It also results in models that have better generalizability to new patients and time periods.

Feature-Based Machine Learning Model for Real-Time Hypoglycemia Prediction.

BACKGROUND: Hypoglycemia is a serious health concern in youth with type 1 diabetes (T1D). Real-time data from continuous glucose monitoring (CGM) can be used to predict hypoglycemic risk, allowing patients to take timely intervention measures. METHODS: A machine learning model is developed for probabilistic prediction of hypoglycemia (<70 mg/dL) in 30- and 60-minute time horizons based on CGM datasets obtained from 112 patients over a range of 90 days consisting of over 1.6 million CGM values under normal living conditions. A comprehensive set of features relevant for hypoglycemia are developed and a parsimonious subset with most influence on predicting hypoglycemic risk is identified. Model performance is evaluated both with and without contextual information on insulin and carbohydrate intake. RESULTS: The model predicted hypoglycemia with >91% sensitivity for 30- and 60-minute prediction horizons while maintaining specificity >90%. Inclusion of insulin and carbohydrate data yielded performance improvement for 60-minute but not for 30-minute predictions. Model performance was highest for nocturnal hypoglycemia (~95% sensitivity). Shortterm (less than one hour) and medium-term (one to four hours) features for good prediction performance are identified. CONCLUSIONS: Innovative feature identification facilitated high performance for hypoglycemia risk prediction in pediatric youth with T1D. Timely alerts of impending hypoglycemia may enable proactive measures to avoid severe hypoglycemia and achieve optimal glycemic control. The model will be deployed on a patient-facing smartphone application in an upcoming pilot study.

Challenges in the diagnosis of diabetes type in pediatrics.

The incidence of diabetes, both type 1 and type 2, is increasing. Health outcomes in pediatric diabetes are currently poor, with trends indicating that they are worsening. Minority racial/ethnic groups are disproportionately affected by suboptimal glucose control and have a higher risk of acute and chronic complications of diabetes. Correct clinical management starts with timely and accurate classification of diabetes, but in children this is becoming increasingly challenging due to high prevalence of obesity and shifting demographic composition. The growing obesity epidemic complicates classification by obesity's effects on diabetes. Since the prevalence and clinical characteristics of diabetes vary among racial/ethnic groups, migration between countries leads to changes in the distribution of diabetes types in a certain geographical area, challenging the clinician's ability to classify diabetes. These challenges must be addressed to correctly classify diabetes and establish an appropriate treatment strategy early in the course of disease for all. This may be the first step in improving diabetes outcomes across racial/ethnic groups. This review will discuss the pitfalls in the current diabetes classification scheme that is leading to increasing overlap between diabetes types and heterogeneity within each type. It will also present proposed alternative classification schemes and approaches to understanding diabetes type that may improve the timely and accurate classification of pediatric diabetes type.

Adherence to multiple medications in the TODAY (Treatment Options for type 2 Diabetes in Adolescents and Youth) cohort: effect of additional medications on adherence to primary diabetes medication.

Background Non-adherence to diabetes medication leads to poor outcomes and increased healthcare costs. Multiple factors affecting adherence in adults with type 2 diabetes (T2D) have been identified, but pediatric data is sparse. We aimed to determine whether initiation of additional oral medications or insulin affects adherence to primary study medication (PSM) in the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) study. Methods Six hundred and ninety-nine youth (aged 10-17 years) with recent-onset T2D were randomized in the TODAY study. Participants were categorized as adherent (≥80% taken by pill count) or non-adherent (<80%), and adherence was compared between those on additional medications or not. Subgroup analyses to assess influence of race/ethnicity, gender, medication type, or depression were performed. Results At 36 months, 46.3% of participants were taking additional oral medications and 31.9% were on insulin. There was no difference in study medication adherence with additional oral medications (55.1%, 67.1%, and 56.7% at month 36 in those prescribed 0, 1, or 2+ additional medications; p = 0.16). Girls on oral contraceptives (OC) had higher adherence (65.2% vs. 55.8% at month 36; p = 0.0054). Participants on insulin had lower adherence (39.7% vs. 59.3% at 36 months; p < 0.0001). There was decreased adherence in participants with baseline depression (p = 0.008). Conclusions Additional oral medications did not influence adherence to diabetes medications in TODAY. Addition of insulin led to reduced adherence. In subgroup analyses, OC use was associated with higher adherence in girls, while baseline depression was associated with lower adherence overall. Further studies examining potentially modifiable risk factors of adherence in pediatric T2D are needed.

Menstrual Dysfunction in Girls From the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) Study.

Context: Little is known about reproductive function in girls with youth-onset type 2 diabetes. Objectives: To characterize girls with irregular menses and effects of glycemic treatments on menses and sex steroids in the Treatment Options for Type 2 Diabetes in Youth (TODAY) study. Design: Differences in demographic, metabolic, and hormonal characteristics between regular- vs irregular-menses groups were tested; treatment group (metformin with or without rosiglitazone, metformin plus lifestyle) effect on menses and sex steroids over time in the study was assessed. This is a secondary analysis of TODAY data. Setting: Multicenter study in an academic setting. Patients: TODAY girls not receiving hormonal contraception and those at least 1-year postmenarche were included. Irregular menses was defined as three or fewer periods in the prior 6 months. Results: Of eligible participants with serum measurement of sex steroids (n = 190; mean age, 14 years), 21% had irregular menses. Those with irregular vs regular menses had higher body mass index (BMI) (P = 0.001), aspartate aminotransferase (AST) (P = 0.001), free androgen index (P = 0.0003), and total testosterone (P = 0.01) and lower sex hormone-binding globulin (SHBG) (P = 0.004) and estradiol (P = 0.01). Differences remained after adjustment for BMI. There was no treatment group effect on menses or sex steroids at 12 or 24 months, and no association of sex steroids was seen with measures of insulin sensitivity or secretion. Conclusions: Menstrual dysfunction is common in girls with recently diagnosed type 2 diabetes and associated with alterations in sex steroids, SHBG, and AST but not with alteration in insulin sensitivity or ß-cell function and did not improve with 2 years of antihyperglycemic treatment.

Insulin Sensitivity and Diabetic Kidney Disease in Children and Adolescents With Type 2 Diabetes: An Observational Analysis of Data From the TODAY Clinical Trial.

BACKGROUND: Diabetic kidney disease is a major cause of premature mortality in type 2 diabetes mellitus (T2DM). Worsening insulin sensitivity independent of glycemic control may contribute to the development of diabetic kidney disease. We investigated the longitudinal association of insulin sensitivity with hyperfiltration and increased albumin excretion in adolescents with T2DM. STUDY DESIGN: Observational prospective cohort study. SETTING & PARTICIPANTS: 532 TODAY (Treatment Options for Type 2 Diabetes in Adolescents and Youth) participants aged 12 to 17 years with T2DM duration less than 2 years at baseline. The TODAY Study was a multicenter randomized clinical trial that examined the efficacy of 3 treatment regimens (metformin monotherapy, metformin plus rosiglitazone, or metformin plus an intensive lifestyle intervention program) to achieve durable glycemic control. PREDICTORS: Natural log-transformed estimated insulin sensitivity (reciprocal of fasting insulin), hemoglobin A1c concentration, age, race-ethnicity, treatment group, body mass index, loss of glycemic control, and hypertension. OUTCOMES: Hyperfiltration was defined as 99th percentile or higher of estimated glomerular filtration rate (≥140mL/min/1.73m2) when referenced to healthy adolescents (NHANES 1999-2002) and albumin-creatinine ratio ≥ 30µg/mg at 3 consecutive annual visits. RESULTS: Hyperfiltration was observed in 7.0% of participants at baseline and in 13.3% by 5 years, with a cumulative incidence of 5.0% over 5 years. The prevalence of increased albumin excretion was 6% at baseline and 18% by 5 years, with a cumulative incidence of 13.4%. There was an 8% increase in risk for hyperfiltration per 10% lower estimated insulin sensitivity in unadjusted and adjusted models (P=0.01). Increased albumin excretion was associated with hemoglobin A1c concentration, but not estimated insulin sensitivity. LIMITATIONS: Longer follow-up is needed to capture the transition from hyperfiltration to rapid glomerular filtration rate decline in youth-onset T2DM. CONCLUSIONS: Lower estimated insulin sensitivity was associated with risk for hyperfiltration over time, whereas increased albumin excretion was associated with hyperglycemia in youth-onset T2DM.

Correlates of Medication Adherence in the TODAY Cohort of Youth With Type 2 Diabetes.

OBJECTIVE: To identify factors that predict medication adherence and to examine relationships among adherence, glycemic control, and indices of insulin action in TODAY (Treatment Options for Type 2 Diabetes in Adolescents and Youth). RESEARCH DESIGN AND METHODS: A total of 699 youth 10-17 years old with recent-onset type 2 diabetes and ≥80% adherence to metformin therapy for ≥8 weeks during a run-in period were randomized to receive one of three treatments. Participants took two study pills twice daily. Adherence was calculated by pill count from blister packs returned at visits. High adherence was defined as taking ≥80% of medication; low adherence was defined as taking <80% of medication. Depressive symptoms, insulin sensitivity (1/fasting insulin), insulinogenic index, and oral disposition index (oDI) were measured. Survival analysis examined the relationship between medication adherence and loss of glycemic control. Generalized linear mixed models analyzed trends in adherence over time. RESULTS: In this low socioeconomic cohort, high and low adherence did not differ by sex, age, family income, parental education, or treatment group. Adherence declined over time (72% high adherence at 2 months, 56% adherence at 48 months, P < 0.0001). A greater percentage of participants with low adherence had clinically significant depressive symptoms at baseline (18% vs. 12%, P = 0.0415). No adherence threshold predicted the loss of glycemic control. Longitudinally, participants with high adherence had significantly greater insulin sensitivity and oDI than those with low adherence. CONCLUSIONS: In the cohort, the presence of baseline clinically significant depressive symptoms was associated with subsequent lower adherence. Medication adherence was positively associated with insulin sensitivity and oDI, but, because of disease progression, adherence did not predict long-term treatment success.

Nonaqueous, Mini-Dose Glucagon for Treatment of Mild Hypoglycemia in Adults With Type 1 Diabetes: A Dose-Seeking Study.

OBJECTIVE: To evaluate mini-dose glucagon in adults with type 1 diabetes using a stable, liquid, ready-to-use preparation. RESEARCH DESIGN AND METHODS: Twelve adults with type 1 diabetes receiving treatment with insulin pumps received subcutaneous doses of 75, 150, and 300 µg of nonaqueous glucagon. Plasma glucose, glucagon, and insulin concentrations were measured. At 180 min, subjects received insulin followed in ~60 min by a second identical dose of glucagon. RESULTS: Mean (±SE) fasting glucose concentrations (mg/dL) were 110 ± 7, 110 ± 10, and 109 ± 9 for the 75-, 150-, and 300-µg doses, respectively, increasing maximally at 60 min by 33, 64, and 95 mg/dL (all P < 0.001). The post-insulin administration glucose concentrations were 70 ± 2, 74 ± 5, and 70 ± 2 mg/dL, respectively, with maximal increases of 19, 24, and 43 mg/dL post-glucagon administration (P < 0.02) at 45-60 min. CONCLUSIONS: Subcutaneous, nonaqueous, ready-to-use G-Pen Mini glucagon may provide an alternative to oral carbohydrates for the management of anticipated, impending, or mild hypoglycemia in adults with type 1 diabetes.

Metabolic syndrome is common and persistent in youth-onset type 2 diabetes: Results from the TODAY clinical trial.

OBJECTIVE: To examine the prevalence of metabolic syndrome (MetS) in youth-onset type 2 diabetes in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study. METHODS: Prevalence of MetS (ATP III definition) was compared at baseline (n = 679) and at 6 (n = 625) and 24 months (n = 545) using chi-square tests. Laboratory data were examined between MetS classifications at each time point using ANOVA. RESULTS: Baseline prevalence of MetS was 75.8% and did not differ by treatment group or change over time. MetS was more common in females (83.1%) than males (62.3%; P < 0.0001) at baseline; this difference persisted over 24 months. Prevalence of MetS was similar between ethnic groups at baseline but greater in Hispanics (82.7%) vs. non-Hispanic Whites (67.5%; P = 0.0017) and non-Hispanic Blacks (72.7%; P = 0.0164) at 24 months. Although MetS was common in participants with hemoglobin A1c < 7.0% (74.4% at baseline; no significant change over 24 months), it was more common in those who did not maintain glycemic control at 6 months (80.3%; P = 0.0081). Elevated C-reactive protein, ALT, IL-6, and PAI-1 levels were more frequent with MetS. CONCLUSIONS: Persistent high prevalence of MetS in youth-onset diabetes, even with excellent glycemic control, is of concern given the associated increased cardiovascular risk.

Parental Characteristics Associated With Outcomes in Youth With Type 2 Diabetes: Results From the TODAY Clinical Trial.

OBJECTIVE: This study examined parental factors associated with outcomes of youth in the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) clinical trial. RESEARCH DESIGN AND METHODS: Of 699 youth with type 2 diabetes in the TODAY cohort, 623 (89.1%) had a parent participate and provide data at baseline, including weight, HbA1c, blood pressure, symptoms of depression, binge eating (BE), and medical history. Youth were followed 2-6.5 years. Data were analyzed using regression models and survival curve methods. RESULTS: Parental diabetes (43.6% of parents) was associated with higher baseline HbA1c (P < 0.0001) and failure of youths to maintain glycemic control on study treatment (53.6% vs. 38.2% failure rate among those without a diabetic parent, P = 0.0002). Parental hypertension (40.6% of parents) was associated with hypertension in youth during TODAY (40.4% vs. 27.4% of youth with and without parental hypertension had hypertension, P = 0.0008) and with higher youth baseline BMI z scores (P = 0.0038). Parents had a mean baseline BMI of 33.6 kg/m(2). Parental obesity (BMI >30 kg/m(2)) was associated with higher baseline BMI z scores in the youth (P < 0.0001). Depressive symptoms in parents (20.6% of parents) were related to youth depressive symptoms at baseline only (P = 0.0430); subclinical BE in parents was related to the presence of subclinical BE (P = 0.0354) and depressive symptoms (P = 0.0326) in youth throughout the study period. CONCLUSIONS: Parental diabetes and hypertension were associated with lack of glycemic control, hypertension, and higher BMI z scores in youth. Further research is needed to better understand and address parental biological and behavioral factors to improve youth health outcomes.

Alterations in left ventricular, left atrial, and right ventricular structure and function to cardiovascular risk factors in adolescents with type 2 diabetes participating in the TODAY clinical trial.

Data on cardiovascular disease (CVD) risk in adolescents with type 2 diabetes (T2D) are limited. Echocardiography was performed in the last year of the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) clinical trial (median 4½ yr from diagnosis of T2D, average age 18 yr), including MMode and 2D measurements of left ventricular (LV) and left atrial (LA) dimensions, LV tissue Doppler imaging (TDI), and tricuspid annular plane systolic excursion (TAPSE). Relationships between cardiac structure and function with demographic characteristics and baseline and change-from-baseline in CVD risk factors were examined in 455 participants. Mean LV mass (LVM) was high/normal and 16.2% had adverse LV geometry (8.1% concentric geometry, 4.5% LV hypertrophy, and 3.6% both). Determinants of higher LVM were male gender, black race, baseline and increasing body mass index (BMI), baseline and increasing systolic blood pressure (SBP), use of blood pressure (BP) medications, maintenance of glycemic control, and smoking; heart rate (HR) was inversely related. LV shortening fraction was high/normal and related to increasing BMI and higher baseline SBP. LV relative wall thickness was related to race-ethnicity, change in BMI, baseline glycated hemoglobin (HbA1c), and baseline and change in SBP. Mean LA internal dimension was high/normal and gender, baseline and increasing BMI, increasing SBP, and HR (inverse) were related. LV TDI was positively related to obesity (higher with adverse geometry). TAPSE was normal and related to higher baseline BMI and lower HR. There was no effect of T2D treatment on cardiac target organ injury. Adolescents with T2D have adverse measures of cardiac structure and function positively related to BMI and BP.

The Relationship between Self-Management and Glycemic Control in a Cohort of Children with Type 1 and Type 2 Diabetes.

AIM: Self-management of diabetes improves glycemic control. The development of a quick, objective questionnaire in the clinic setting may provide data to the clinician caring for the patient in overall evaluation. OBJECTIVE: We developed a 23 question tool (clinic preparedness score) and administered it to type 1 and 2 (T1DM & T2DM) diabetes patients. Clinicians of patients were surveyed to determine their perception of adherence by patients. A total of 350 T1DM patients and families and 137 T2DM families were administered the questionnaire. Additionally, HbA1C was correlated to the various parameters that are related to improved glycemic control such as having a meter, carrying glucose tablets for hypoglycemia, and downloading/ writing blood sugars in log book in T1DM and T2DM. RESULTS: T1DM subjects had a lower HbA1C with better clinic preparedness (8.2 ± 1.3 vs. 9.4 ± 1.9%) However, this did not hold true for T2DM (p NS). If T1DM subjects adjusted their insulin dose and reported that their parent was involved they had better HbA1C than those that did not change insulin dose and if parent was uninvolved in the care. Clinicians of patients were able to accurately predict that appropriate dose adjustments resulted in good glycemic control. CONCLUSIONS: Pediatric T2DM adherence measures do not mirror similar characteristics of T1DM in childhood. The variability in glucose monitoring, medication and insulin administration may affect T2DM differently than T1DM.

Depressive symptoms and quality of life in adolescents with type 2 diabetes: baseline data from the TODAY study.

OBJECTIVE: The study objective was to examine the prevalence of depressive symptoms and relationships to quality of life and demographics in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study's large, ethnically diverse youth with type 2 diabetes. RESEARCH DESIGN AND METHODS: A total of 704 youth with type 2 diabetes <2 years' duration, aged 10-17 years, and BMI ≥85th percentile completed depressive symptoms and quality of life measures. RESULTS: Some 14.8% reported clinically significant depressive symptoms, and older girls had significantly higher rates than older boys. CONCLUSIONS: Rates of significant depressive symptoms were similar to those of healthy adolescents and lower than those of teens with type 1 diabetes. Elevated depressive symptoms, particularly in older girls, suggest clinicians assess vulnerability.