Report of Prolonged Neonatal Hypoglycemia in Three Infants of Mothers With Variants in HNF1A.

Background/Objective: Genetic variants in hepatic nuclear factor 1α (HNF1A) cause maturity-onset diabetes of the young (MODY). We sought to examine whether HNF1A MODY variants also cause neonatal hypoglycemia. Case Report: We present 3 infants with variants in HNF1A shared with their mothers. The infants experienced neonatal hypoglycemia, 2 extending beyond 1 year and the third resolving by 28 days, and all were large for gestational age (birth weights of >99th percentile). In 2 cases, genetic testing for neonatal hypoglycemia revealed pathogenic variants in HNF1A; 1 mother was previously diagnosed with HNF1A MODY, and the other's genetic testing and ultimate MODY diagnosis were prompted by her child's hypoglycemia workup. In the third case, the infant's persistent hypoglycemia prompted genetic testing, revealing an HNF1A variant of uncertain significance, which was then identified in the mother. Discussion: Genetic variants causing HNF1A MODY have not been definitively linked to neonatal hypoglycemia or fetal overgrowth in utero. MODY caused by HNF1A is clinically similar to that caused by HNF4A, for which a causal relationship with neonatal hypoglycemia is more certain. Case reports have previously implicated variants in HNF1A in congenital hyperinsulinism; however, these cases have generally not been in families with MODY. The cases presented here suggest that HNF1A variants causing MODY may also cause neonatal hypoglycemia. Conclusion: Although confounding factors make the assessment of neonatal hypoglycemia challenging, these cases offer potential support for single genetic variants in HNF1A causing both MODY and neonatal hypoglycemia, with associated fetal overgrowth in utero.

Sleep in children with type 1 diabetes and their parents in the T1D Exchange.

OBJECTIVES: Sleep has physiological and behavioral impacts on diabetes outcomes, yet little is known about the impact of sleep disturbances in children with type 1 diabetes. The current study sought to characterize sleep in children with type 1 diabetes and in their parents and to examine the associations between child sleep, glycemic control and adherence, parent sleep and well-being, parental fear of hypoglycemia, and nocturnal caregiving behavior. METHODS: Surveys were emailed to parents of 2- to 12-year-old participants in the Type 1 Diabetes (T1D) Exchange clinic registry. Clinical data were obtained from the registry for the 515 respondents. RESULTS: In our sample, 67% of children met criteria for poor sleep quality. Child sleep quality was related to glycemic control (HbA1c of 7.9% [63 mmol/mol] in children with poor sleep quality vs 7.6% [60 mmol/mol] in children with non-poor sleep quality; P < 0.001) but not mean frequency of blood glucose monitoring (BGM) (7.6 times/day vs 7.4 in poor/non-poor quality; P = 0.56). Associations were similar for sleep duration. Children with poor sleep quality were more likely to experience severe hypoglycemia (4% in children with poor sleep quality vs 1% in children with non-poor sleep quality; P = 0.05) and more likely to experience DKA (7% vs 4%, respectively; P < 0.001). Poorer child sleep quality was associated with poorer parental sleep quality, parental well-being, and fear of hypoglycemia (P < 0.001 for all). Child sleep was not related to the use of diabetes-related technology (CGM, insulin pump). CONCLUSIONS: Sleep may be a modifiable factor to improve glycemic control and reduce parental distress.

Participatory surveillance of diabetes device safety: a social media-based complement to traditional FDA reporting.

BACKGROUND AND OBJECTIVE: Malfunctions or poor usability of devices measuring glucose or delivering insulin are reportable to the FDA. Manufacturers submit 99.9% of these reports. We test online social networks as a complementary source to traditional FDA reporting of device-related adverse events. METHODS: Participatory surveillance of members of a non-profit online social network, TuDiabetes.org, from October 2011 to September 2012. Subjects were volunteers from a group within TuDiabetes, actively engaged online in participatory surveillance. They used the free TuAnalyze app, a privacy-preserving method to report detailed clinical information, available through the network. Network members were polled about finger-stick blood glucose monitors, continuous glucose monitors, and insulin delivery devices, including insulin pumps and insulin pens. RESULTS: Of 549 participants, 75 reported device-related adverse events, nearly half (48.0%) requiring intervention from another person to manage the event. Only three (4.0%) of these were reported by participants to the FDA. All TuAnalyze reports contained outcome information compared with 22% of reports to the FDA. Hypoglycemia and hyperglycemia were experienced by 48.0% and 49.3% of participants, respectively. DISCUSSION: Members of an online community readily engaged in participatory surveillance. While polling distributed online populations does not yield generalizable, denominator-based rates, this approach can characterize risk within online communities using a bidirectional communication channel that enables reach-back and intervention. CONCLUSIONS: Engagement of distributed communities in social networks is a viable complementary approach to traditional public health surveillance for adverse events related to medical devices.

Routine behavioral and mental health screening in young children with type 1 diabetes mellitus.

BACKGROUND: The American Diabetes Association and International Society for Pediatric and Adolescent Diabetes recommend that providers of diabetes care receive training in the recognition of psychosocial problems related to diabetes. OBJECTIVE: To report the results of routine behavioral/mental health screening for children with type 1 diabetes mellitus (T1D) seen in a multidisciplinary pediatric diabetes program. SUBJECTS AND METHODS: This was a cross-sectional study of children with T1D ages 4-11 years, who underwent behavioral/mental health screening as part of their diabetes care. Screening utilized the Strengths and Difficulties Questionnaire (SDQ) Parent Proxy Version, and scores were reviewed by a social worker. SDQ scale and total difficulties scores were compared by gender, visit type, age, T1D duration, and HbA1c. Scores were also compared to age-appropriate normative data for children in United States of America (US). RESULTS: SDQ Parent Proxy Version total difficulties and scale scores did not differ by patient or visit characteristics. Compared with normative data for US children, a greater proportion of children with T1D ages 4-7 and 8-10 years had borderline/abnormal scores on the emotional symptoms scale (p = 0.01 and p = 0.03, respectively), suggesting risk for psychological disorders, such as anxiety and depression. CONCLUSIONS: Our findings suggest that children less than 11 years old with T1D may have greater emotional symptoms as compared to their age-matched healthy peers. Pediatric diabetes care providers, with access to mental health services, should consider incorporating routine behavioral/mental health screening for children less than 12 years old in their practice.

Participatory surveillance of hypoglycemia and harms in an online social network.

IMPORTANCE: Surveillance systems for elucidating the burden of hypoglycemia are limited. OBJECTIVE: To quantify experiences of hypoglycemia and related harms, members of an international online diabetes social network with insulin-dependent diabetes mellitus were polled through a software application ("app"). Aggregate results were returned to participants through network channels. DESIGN: The study period was from March 2011 through April 2012, during which time retrospective reports about experiences with hypoglycemia and related harms were collected from participants using the app. SETTING: The study was undertaken within the TuDiabetes.org international online diabetes social network. PARTICIPANTS: Eligibility criteria included TuDiabetes membership, age 13 years or older, a self-reported diagnosis of diabetes mellitus, ability to read and write English, and Internet access. Of 2827 app users, 687 (response rate, 24.3%) opted in to the volunteer sample. MAIN OUTCOME MEASURES: Primary outcomes included the following: frequency of "going low" (having a low glucose value in the past 2 weeks) and episodes of severe hypoglycemia (in the past 12 months), and, for respondents reporting recent and/or severe hypoglycemia, lifetime experience of vehicle crashes or severe medical injury, daily debilitating worry, and withdrawal from driving, exercise, sex, and going outside of the home to avoid hypoglycemia and consequences. Secondary outcomes included measures of research engagement. RESULTS: Of 613 respondents (24.3% of app users), 49.1% reported more than 4 episodes of "going low" in the past 2 weeks and 29.2% reported 1 or more severe low in the past year; 16.6% reported both more than 4 recent low episodes and 1 or more severe event in the past year. Harms were common, including daily debilitating worry (45.8%), vehicle crash or injury (15.0%), and withdrawal from exercise, driving, leaving home, and having sex (54.0%, 37.4%, 24.8%, and 22.7%, respectively). Of all respondents, 54.2% reported multiple harms, the risks for which were highest (73.7%) among respondents with a past-year severe event (odds ratio, 2.39; 95% CI, 1.60-3.58; P < .001 controlling for frequent recent low episodes and demographic and disease factors). Engagement was high, with 96.6% of the sample permitting recontact for research and 31.7% posting personal study data on their app profile page; 40.5% of 2825 unique page views of research-related materials published on the community site involved views of returned research results. CONCLUSIONS AND RELEVANCE: Participatory surveillance of hypoglycemia in an online diabetes social network enables characterization of patient-centered harms in a community sample and bidirectional communication with affected persons, augmenting traditional surveillance.

Most youth with type 1 diabetes in the T1D Exchange Clinic Registry do not meet American Diabetes Association or International Society for Pediatric and Adolescent Diabetes clinical guidelines.

OBJECTIVE: To assess the proportion of youth with type 1 diabetes under the care of pediatric endocrinologists in the United States meeting targets for HbA1c, blood pressure (BP), BMI, and lipids. RESEARCH DESIGN AND METHODS: Data were evaluated for 13,316 participants in the T1D Exchange clinic registry younger than 20 years old with type 1 diabetes for ≥1 year. RESULTS: American Diabetes Association HbA1c targets of <8.5% for those younger than 6 years, <8.0% for those 6 to younger than 13 years old, and <7.5% for those 13 to younger than 20 years old were met by 64, 43, and 21% of participants, respectively. The majority met targets for BP and lipids, and two-thirds met the BMI goal of <85th percentile. CONCLUSIONS: Most children with type 1 diabetes have HbA1c values above target levels. Achieving American Diabetes Association goals remains a significant challenge for the majority of youth in the T1D Exchange registry.

Helping high-risk youth move through high-risk periods: personally controlled health records for improving social and health care transitions.

BACKGROUND: New patient-centered information technologies are needed to address risks associated with health care transitions for adolescents and young adults with diabetes, including systems that support individual and structural impediments to self- and clinical-care. METHODS: We describe the personally controlled health record (PCHR) system platform and its key structural capabilities and assess its alignment with tenets of the chronic care model (CCM) and the social-behavioral and health care ecologies within which adolescents and young adults with diabetes mature. RESULTS: Configured as Web-based platforms, PCHRs can support a new class of patient-facing applications that serve as monitoring and support systems for adolescents navigating complex social, developmental, and health care transitions. The approach can enable supportive interventions tailored to individual patient needs to boost adherence, self-management, and monitoring. CONCLUSIONS: The PCHR platform is a paradigm shift for the organization of health information systems and is consistent with the CCM and conceptualizations of patient- and family-centered care for diabetes. Advancing the approach augers well for improvement around health care transitions for youth and also requires that we address (i) structural barriers impacting diabetes care for maturing youth; (ii) challenges around health and technology literacy; (iii) privacy and confidentiality issues, including sharing of health information within family and institutional systems; and (iv) needs for evaluation around uptake, impacts, and outcomes.

Characteristics at diagnosis of type 1 diabetes in children younger than 6 years.

OBJECTIVE: To characterize the prodrome, presentation, family history, and biochemical status at diagnosis of type 1 diabetes mellitus (T1D) in children under age 6 years. STUDY DESIGN: This was a retrospective chart review of patients hospitalized at diagnosis with T1D from 1990 to 1999 in a children's hospital. RESULTS: A total of 247 children were hospitalized, 44% of whom presented in diabetic ketoacidosis (DKA). When stratified by 2-year age intervals, only total carbon dioxide (tCO(2)) was significantly lower in the youngest children (P = .02), and the duration of candidiasis was significantly longer in those children presenting in DKA (P = .004). Parents were more likely to recognize symptomatic hyperglycemia in children older than 2 years (P < .0001). Most parents sought care for their child suspecting that the child had diabetes; the other children were diagnosed when presenting with another concern. Only gender and tCO(2) were significantly correlated with hemoglobin A1c (HbA1c); age-adjusted HbA1c was 0.64% higher in girls compared with boys (P = .045), and each 1-mmol/L decrement in tCO(2) increased the age- and gender-adjusted HbA1c by 0.086% (P < .001). CONCLUSIONS: A high proportion of children under age 6 years present critically ill at the diagnosis of T1D. When any of the classic symptoms of diabetes or a yeast infection is present, a serum glucose level should be measured.

Change in glycemic control predicts change in weight in adolescent boys with type 1 diabetes.

OBJECTIVE: To characterize the intraindividual relationships between changes in weight, glycosylated hemoglobin (HbA1c) levels, and reported total daily insulin dose between clinic visits in adolescent boys with type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: Intraindividual changes in HbA1c, anthropometric data, and reported total daily insulin dose between consecutive visits for 94 adolescent boys with T1D were analyzed. RESULTS: Average quarterly weight gain was 2.8 kg during periods of improving, 1.5 kg during periods of minimal change, and 0.8 kg during periods of worsening glycemic control (improving vs. minimal change p < 0.001; minimal change vs. worsening p = 0.11; improving vs. worsening p < 0.001). Analyzing the quarterly weight velocity according to change in reported total daily dose of insulin, we found significantly greater weight gain during intervals when the family reported a decreasing insulin dose compared to intervals when the family reported no change in insulin dose (p = 0.003). Conversely, weight change during periods of reported increasing insulin dose was similar to that when the family reported that the boy's insulin dose did not change. CONCLUSIONS: Quarterly weight velocity was correlated with degree of change in glycemic control between visits in adolescent boys with T1D. When weight loss or inadequate weight gain and worsening glycemic control occur, the possibility of insulin omission must be explored. Reviewing the adolescent's growth data and then the division of responsibilities for diabetes management within the family, clinicians must reconcile discrepancies between weight velocity and a reportedly adequate dose of insulin.