Search

Background Pediatric diabetes clinics around the world rapidly adapted care in response to COVID-19. We explored provider perceptions of care delivery adaptations and challenges for providers and patients across nine international pediatric diabetes clinics. Methods Providers in a quality improvement collaborative completed a questionnaire about clinic adaptations, including roles, care delivery methods, and provider and patient concerns and challenges. We employed a rapid analysis (RA) to identify main themes. Results Providers described adaptations within multiple domains of care delivery, including provider roles and workload, clinical encounter and team meeting format, care delivery platforms, self-management technology education, and patient-provider data sharing. Providers reported concerns about potential negative impacts on patients from COVID-19 and the clinical adaptations it required, including fears related to telemedicine efficacy, blood glucose and insulin pump/pen data sharing, and delayed care-seeking. Particular concern was expressed about already vulnerable patients. Simultaneously, providers reported 'silver linings' of adaptations that they perceived as having potential to inform care and self-management recommendations going forward, including time-saving clinic processes, telemedicine, lifestyle changes compelled by COVID-19, and improvements to family and clinic staff literacy around data sharing. Conclusions Providers across diverse clinical settings reported care delivery adaptations in response to COVID-19 --particularly telemedicine processes-- created challenges and opportunities to improve care quality and patient health. To develop quality care during COVID-19, providers emphasized the importance of generating evidence about which in-person or telemedicine processes were most beneficial for specific care scenarios, and incorporating the unique care needs of the most vulnerable patients. This article is protected by copyright. All rights reserved.

Objectives: To examine, among youth and young adults (YYAs) with type 1 diabetes (T1D), the independent association of household food insecurity (HFI) with: 1) glycemic control and 2) episodes of diabetic ketoacidosis (DKA) and severe hypoglycemia. Methods: This cross-sectional study included SEARCH for Diabetes in Youth participants with T1D examined between 2016-2019. HFI was assessed using the U.S. Household Food Security Survey Module. HbA1c was measured from blood drawn at a research visit; episodes of DKA and severe hypoglycemia were collected by survey. Linear and logistic regression models adjusted for age, sex, race, income, health insurance, diabetes duration, and SEARCH site. Results: Of 1834 participants (mean age 20.8±5.0 years, 69.9% non-Hispanic white, diabetes duration 11.1±3.2 years), HbA1c was collected for 1029 individuals (mean HbA1c 9.2%±2.0%). The prevalence of HFI was 16.4%. In this sample, 18.7% and 9.9% reported an episode of DKA or severe hypoglycemia in the past 12 months, respectively. Compared to participants who were food secure, HFI was associated with a 0.43% [CI: 0.02%-0.68%] higher HbA1c. In two separate adjusted models, those with HFI had 1.86 [CI: 1.03, 2.34] times the odds of an episode of DKA and 1.64 [CI: 1.03, 2.34] times the odds of an episode of severe hypoglycemia as those without HFI. Conclusions: HFI is independently associated with poor glycemic control and increased odds of diabetes-related complications in YYAs with T1D. Interventions to reduce HFI and studies to longitudinally examine its impact on glycemic control and complications are warranted. Disclosure F. Malik: None. A.D. Liese: None. A.M. Ellyson: None. L.A. Reid: None. K.A. Sauder: None. E.A. Frongillo: None. C. Pihoker: None. D. Dabelea: None. J.M. Lawrence: None. E.T. Jensen: None. S. Saydah: None. S.M. Marcovina: None. D. Bowlby: None. J.A. Mendoza: None. Funding Centers for Disease Control and Prevention (00097, DP-05-069, DP-10-001); National Institute of Diabetes and Digestive and Kidney Diseases (1UC4DK108173)

BACKGROUND Prevalence of MODY is 1.2% in pediatric diabetes population. SEARCH study reported most of these patients were misdiagnosed as T1DM or T2DM up to 36% and 51% respectively (1). GCK (MODY 2) and HNF1A/HNF4A (MODY3) are the most common forms of MODY. Despite improvement in testing strategy (panel testing instead of step-wise approach) and cost, MODY testing remains underutilized. These conditions do not require insulin therapy, and MODY 2 patients may even be discharged from clinic after diagnosis. We present 4 cases and valuable lessons learned. MODY 2 Case 1. 4 yo M referred for hyperglycemia in the 300s during surgery. A1c 6.4%. FBG at home 150s, asymptomatic. MGM and MGM’s siblings have diabetes. Diabetes autoantibodies (DAA) negative. C-peptide 5.4 (NL 0.78 - 5.19 ng/ml). MODY panel (GeneDx) showed heterozygous mutation in GCK gene (c.70 C>T). Patient remains off insulin, family reassured and advised to undergo genetic testing. MODY 2 Case 2. 8 yo M diagnosed at local ED with “T1DM” after presenting with polyuria, polydipsia, and random BG 237. A1c 6.7%, C-peptide 1.9, started on basal-bolus insulin. MODY panel (sent a year later when patient was found to have low insulin requirement, negative DAA) showed pathogenic variant in GCK gene. Weaned from insulin, A1c unchanged (6.3–7%). Mother found to have same mutation. MODY 3 Case 1. 16 yo F referred by PCP who started her on insulin a year prior after an incidental finding of hyperglycemia. A1c was 7.5% at diagnosis. Mom, MGM have diabetes, unknown type (MGM thin by report). DAA neg, C-Peptide 1.74. MODY Panel showed HNF1A heterozygous gene mutation for RI31Q. She was switched to Glyburide, blood glucose 90s. MODY 3 Case 2. 10 yo M referred from the ED for “T1DM” (weight loss, fatigue, A1c 7.6%) started on basal-bolus insulin, but lost to follow up for a year. Brother has MODY 3. DAA neg, C-Peptide 3.1. Targeted gene sequencing showed HNF1A gene mutation. He was switched to Glyburide, A1c improved to 6.7%. However, patient became noncompliant as teenager, A1c now 9.3%. CONCLUSION MODY remains underdiagnosed. A high index of suspicion should be maintained in nonobese, DAA-negative patients diagnosed with DM before 25yo. Although DAA and genetic testing can be costly, diagnosis can dramatically alter diabetes management as illustrated in all 4 cases, and overall cost of management may be lower in the end. Patients with MODY 2 do not develop vascular complications associated with diabetes, nor require pharmacotherapy. MODY 3 patients may be safely switched to sulfonylurea monotherapy, though degree of diabetes control depends on compliance with medication. Testing gives relatives previously misdiagnosed the opportunity to improve their own quality of life. More education for health care providers is warranted for prompt diagnosis and appropriate management of this condition. Reference:1. Pihoker, et al. JCEM 2013; 98:4055–62

The Case: An 8 days old male, born at 40 wks, 2.8 kg (SGA) presented to local ED with lethargy, decreased PO intake and urine output, respiratory distress. No fever, URI sx, vomiting/diarrhea. His dad had URI symptoms and fever a week prior. He was found to have T=95.5F, glucose Discussion/Conclusion: There is a dearth of information on SARS-CoV-2 infection in newborns. The few studies available show favorable outcomes in this population, with typical mild-moderate respiratory symptoms and fever, while some newborns are asymptomatic. Our patient required oxygen tx and developed HH requiring Diazoxide therapy. To our knowledge, this is the first reported case of HH in the newborn with SARS-CoV-2 infection. Hyerperinsulinism is the most common cause of hypoglycemia in infants. These newborns are at risk of developing significant neurologic morbidity, which can be dose dependent. Prompt diagnosis and aggressive management are important to reduce such risk. Perinatal stress is likely the underlying mechanism leading to HH in newborns with SARS-CoV-2 infection. Patient is also SGA. Both perinatal stress and SGA can lead to inappropriately elevated insulin levels and resultant hypoglycemia. HH in both of these conditions is effectively managed by Diazoxide. Our case illustrates that although most newborns do well with SARS-CoV-2 infection, a high index of suspicion for HH should be maintained in such newborns, particularly in those with at least one other risk factor for HH such as SGA. More studies are needed to elucidate underlying pathology and tease out actual incidence of hypoglycemia in neonates with SARS-CoV-2 infection.

Background The incidence of type 1 diabetes mellitus (T1DM) in children is increasing, resulting in higher burden of cardiovascular diseases due to diabetes mellitus–related vascular dysfunction. Methods and Results We examined cardiovascular risk factors ( CVRF s) and arterial parameters in 1809 youth with T1DM. Demographics, anthropometrics, blood pressure, and laboratory data were collected at T1DM onset and 5 years later. Pulse wave velocity and augmentation index were collected with tonometry. ANOVA or chi‐square tests were used to test for differences in measures of arterial parameters by CVRF . Area under the curve of CVRF s was entered in general linear models to explore determinants of accelerate vascular aging. Participants at the time of arterial measurement were 17.6±4.5 years old, 50% female, 76% non‐Hispanic white, and duration of T1DM was 7.8±1.9 years. Glycemic control was poor (glycated hemoglobin, 9.1±1.8%). All arterial parameters were higher in participants with glycated hemoglobin ≥9% and pulse wave velocity was higher with lower insulin sensitivity or longer duration of diabetes mellitus. Differences in arterial parameters were found by sex, age, and presence of obesity, hypertension, or dyslipidemia. In multivariable models, higher glycated hemoglobin, lower insulin sensitivity, body mass index, blood pressure, and lipid areas under the curve were associated with accelerated vascular aging. Conclusions In young people with T1DM, persistent poor glycemic control and higher levels of traditional CVRF s are independently associated with arterial aging. Improving glycemic control and interventions to lower CVRF s may prevent future cardiovascular events in young individuals with T1DM.

THE CASE 4 mo M born at term 7lbs 7.5oz, 19.5 inches via C-section, referred for micropenis found during evaluation for circumcision. No history of hypoglycemia. Of note, dad is s/p hypospadias repair and is short at 5th %ile. PE showed short stature, length at 3rd %ile (-1.91 SDS), wt 53rd %ile, HC 76th %ile. Stretched penile length 1.5 cm (-2.5 SDS = 1.9cm), testes 1.5 cm each, normal. Periorbital hemangioma noted. Otherwise normal exam. Chromosome microarray showed a 6.1 Mb duplication of the terminal region of 6p, pathogenic; and a 222 kb deletion of terminal 17p (felt to have no clinical significance). Patient referred to Genetics. Parental testing showed balanced translocation in dad's chromosome 46,XY,t(6;17)(p25.1;p13.1)]. GH, TSH, FT4, LH, FSH, AMH levels normal. Total Testosterone 68 ng/dL. CAH-6 panel within expected limits. Testosterone therapy 50mg/mo x 3mos initiated to improve penile length. DISCUSSION Workup of underlying cause of male undervirilization is challenging. More often than not, a definitive diagnosis remains elusive. The current case underlines the invaluable contribution of chromosomal microarray in this endeavor. Duplication of distal fragment of chromosome 6p is extremely rare, with

INTRODUCTION We present 2 contrasting cases of Neonatal Diabetes (NDM) switched from insulin to sulfonylurea in infancy vs adolescence. Importance of having high index of suspicion, making prompt diagnosis, choosing the right therapy is highlighted. METHODOLOGY Case1 13 mo/Female born premature 34 weeks presented with hyperglycemia after birth requiring insulin. Mother herself reported "Type1 Diabetes" (T1DM) diagnosed at 3 weeks. Patient was started on Glyburide 0.1mg/kgBID at 2 weeks, titrated with insulin wean. Blood sugars improved, stable at Glyburide dose 0.2mg/kg/day. HbA1c 6.4%, no hypoglycemia. Genetic testing showed KCNJ11 mutation (c.602G>A). Mother's testing showed same mutation, switched to glyburide, doing well. Case2 13 yo/Male transferred care for "T1DM" on insulin pump, diagnosed at 6 days old. Mother herself reported "T1DM" diagnosed at 2 weeks, on insulin pump. Maternal cousin diagnosed at 1 week, reported to have ABCC8 mutation. Patient's A1c >14%, feeling burnt out. DNA sequencing showed ABCC8 gene mutation (c.4136G>A;p.arg1379His). Glyburide 0.1 mg/kgBID started, titrated weekly with insulin wean. He is currently insulin-free, blood sugars range 72-118 at glyburide dose 0.7 mg/kg/day. Mother's genetic testing pending. DISCUSSION/CONCLUSION Most diabetes in infancy are monogenic. Technology for NDM diagnosis has been available for at least a decade. Oral sulfonylureas may be used in patients with KCNJ11 or ABCC8 mutation. Prompt diagnosis can make dramatic impact on quality of life, as illustrated by Case 1 (likely to be insulin-free for life) vs Case 2 who was burnt out. More education for diabetes providers is paramount regarding NDM and its proper management.

Key Clinical Message Endocrinologists should have a high index of suspicion for a Hb variant when the HbA1c is not consistent with other indices of glycemic control.

We aimed to develop an efficient surveillance approach for childhood diabetes. We analyzed EHR data from two independent US academic health care systems. Presumptive diabetes cases were identified as those having >1 of the five diabetes indicators in the past 3.5 years. EHRs of the presumptive cases were manually reviewed. We developed a stepwise surveillance approach using billing codes-based pre-specified algorithms and targeted manual EHRs review. The sensitivity and positive predictive value in both systems were approximately >90%. This stepwise surveillance approach resulted in a >70% reduction in the number of cases requiring manual validation compared to traditional surveillance methods.

Objective To develop an efficient surveillance approach for childhood diabetes by type across 2 large US health care systems, using phenotyping algorithms derived from electronic health record (EHR) data. Materials and Methods Presumptive diabetes cases Results We developed a stepwise surveillance approach using billing code–based prespecified algorithms and targeted manual EHR review, which efficiently and accurately ascertained and classified diabetes cases by type, in both health care systems. The sensitivity and positive predictive values in both systems were approximately ≥90% for ascertaining diabetes cases overall and classifying cases with type 1 or type 2 diabetes. About 80% of the cases with “other” type were also correctly classified. This stepwise surveillance approach resulted in a >70% reduction in the number of cases requiring manual validation compared to traditional surveillance methods. Conclusion EHR data may be used to establish an efficient approach for large-scale surveillance for childhood diabetes by type, although some manual effort is still needed.

Objective Dyslipidemia contributes to the increased risk of cardiovascular disease in persons with type 1 diabetes (T1D). Weight control is commonly recommended as a treatment for dyslipidemia. However, the extent to which decreases in weight affect the lipid profile in youth with T1D is not known. Therefore, we tested the hypothesis that decreases in body mass index z-score (BMIz) were associated with concomitant changes in the lipid profile in youth with T1D. Study Design We studied 1142 youth with incident T1D, who had at least two fasting lipid measurements over 2 yr (initial visit mean: age = 10.8 ± 3.9 yr, BMIz = 0.55 ± 0.97, T1D duration = 10.7 ± 7.6 months; 47.5% female, 77.9% non-Hispanic white) in the SEARCH for Diabetes in Youth Study. Longitudinal mixed models were used to examine the relationships between changes in BMIz and changes in total, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), non-HDL cholesterol, and log triglycerides (TG) adjusted for initial age, sex, race/ethnicity, clinical site, season of study visit, T1D duration, and glycated hemoglobin A1c (HbA1c). Results We found that over 2 yr all lipid levels, except LDL-C, increased significantly (p < 0.05). Decreases in BMIz were associated with favorable changes in HDL-C and TG only and the magnitude of these changes depended on the initial BMIz value (interaction p < 0.05), so that greater improvements were seen in those with higher BMIz. Conclusions Our data suggest that weight loss may be an effective, but limited, therapeutic approach for dyslipidemia in youth with T1D.

Ongoing surveillance of childhood diabetes in the U.S. is needed to understand the trends in incidence and prevalence, and to anticipate health care delivery needs. The SEARCH for Diabetes in Youth Study (SEARCH) (1) documented an increase in the prevalence of type 1 and type 2 diabetes from 2001 to 2009 (2, 3). From 2010 to 2050, the number of youth with type 1 and type 2 diabetes is projected to increase by another 23% and 49%, respectively, even assuming no change in incidence since 2002 (4). Surveillance of childhood diabetes is challenging. First, we are unable to employ existing national surveillance systems such as the National Health and Nutrition Examination Survey (NHANES) because childhood diabetes is uncommon; NHANES (1999-2002) yielded only18 self-reported cases of diabetes among youth aged 12 to 19 years (5). Second, ascertainment of childhood diabetes cases is often costly in terms of time and financial resources. Currently the SEARCH study conducts validation of potential cases by manual review of medical records which is expensive, although the resulting case ascertainment is estimated to be very complete (i.e., >90% for both prevalent and incident cases) based on capture-recapture analyses (6). Third, a useful childhood diabetes surveillance system should be able to discriminate between types of diabetes in different age, and racial/ethnic groups as the distribution of childhood diabetes varies by type, age and race/ethnicity (7, 8); and both etiology and treatment differ by diabetes type (7, 9-11). The increasing utilization of computerized medical information systems may provide timely data for diabetes surveillance with substantially reduced cost relative to traditional approaches (12-14). Approaches to identify diabetes cases and classify type have been explored using administrative data (15-22), and electronic health record (EHR) data (23-26). Among all childhood diabetes algorithms in the literature, only two explored type-specific algorithms (21, 23). None of these studies evaluated algorithm performance according to age and race/ethnicity. In the U.S., it is not known whether administrative and EHR data from a large academic care delivery system can be used to accurately differentiate between childhood type 1 and type 2 diabetes (i.e., through use of type-sensitive algorithms) or whether such data can only identify cases without regard to type (i.e., through use of type-insensitive algorithms). It is also not known whether the performance of automated algorithms differs by age and race/ethnicity. Our objective was to identify algorithms with high performance, as demonstrated by high sensitivity, specificity, and positive predictive value (PPV), with a goal to efficiently identify diabetes cases and classify type in youth, overall and by age and race/ethnicity in a large academic care delivery system caring for patients with all payment sources, utilizing administrative and EHR data from the University of North Carolina Health Care System (UNCHCS).