Faculty Bibliography

Severe hypertriglyceridemia (HTG) (>885 mg/dL) can be caused by familial partial lipodystrophy type 3 (FPLD3), an autosomal dominant disorder caused by loss of function of the peroxisome proliferator-activated receptor gamma (PPARG), characterized by abnormal distribution of fat and metabolic derangements. This case reports a 16-year-old female (body mass index, 23.5 kg/m2) hospitalized twice for pancreatitis (triglycerides [TG] level >2,200 mg/dL). Her treatment management included bowel rest, insulin infusion, and plasmapheresis. A low-fat diet with 10 g of fat daily and 160 mg of fenofibrate daily decreased fasting TG to 411 mg/dL (range, 0-149 mg/dL). The patient had a normal leptin level. Panel testing of genes that impact TG metabolism revealed a known pathogenic variant in the PPARG gene (c.452A>G p.Tyr151Cys). A second variant detected in this gene, c.1003G>C (p.Val335Leu), is considered benign. Her glycosylated hemoglobin of 6.6% and 2-hour oral glucose tolerance test confirmed type 2 diabetes mellitus (T2DM). This study reports the earliest detection of T2DM in an adolescent with a pathogenic variant of PPARG. PPARG-related FPLD3 should be considered in lean children that present with severe HTG and insulin resistance, and subsequent treatment with proliferator-activated receptor gamma agonists, specifically thiazolidinediones, should be considered.

Background/Objective: The T1D Exchange Quality Improvement Collaborative (T1Dx-QI) is a learning health system of over 40 US type 1 diabetes clinics. Participating clinics benefit from benchmarking insights, share best-practice ideas for quality improvement (QI), and use data for population health research. This study aims to benchmark the HbA1c metric targets across pediatric clinics in the T1Dx-QI network.
Method(s): T1Dx-QI pediatric clinics report monthly on key metrics, including median HbA1c, percent with HbA1c <7%, time in range, depression screening, and other quality metrics. T1Dx-QI uses this data to support, monitor, and sustain improvement efforts. The T1Dx-QI has set numerous collaborative goals, including to (a) Decrease the median HbA1c to <8% and (b) Increase the % of patients with HbA1c <7%and other QI metric goals. Median values for each site were calculated using Lahey P run charts between July 2020 and June 2021.
Result(s): Across 17 T1Dx-QI clinics, median HbA1c values between July 2020 and June 2021 ranged from 7.4% to 9.2% (Figure 1A). In the same time frame, the clinic-specific average monthly percentage of patients with HbA1c <7% ranged from 35.5% to 11.9% (Figure 1B). These results are shared internally in a non-anonymized version among participating T1Dx-QI clinics. The benchmarked data facilitates collaborative learning and advancement.
Conclusion(s): The T1Dx-QI uses benchmarking of key clinical outcomes metrics as a tool to support quality improvement, sharing of best practices, and promote learning across clinics

BACKGROUND:Hyperosmolar diabetic ketoacidosis (H-DKA), a distinct clinical entity, is the overlap of diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic state (HHS). AIM/OBJECTIVE:We describe the clinical presentation, metabolic aberrations, and associated morbidity/mortality of these cases with H-DKA. We highlight the problem areas of medical care which require particular attention when caring for pediatric diabetes patients presenting with H-DKA. METHODS:In our study we reviewed the literature back to 1963 and retrieved twenty-four cases meeting the criteria of H-DKA: glucose >600 mg/dL, pH < 7.3, bicarbonate <15 mEq/L, and serum osmolality >320 mOsm/kg, while adding three cases from our institution. RESULTS:Average age of presentation of H-DKA was 10.2 years ± 4.5 years in females and 13.3 years ± 4 years in males, HbA1c was 13%. Biochemical parameters were consistent with severe dehydration: serum osmolality = 394.8±55 mOsm/kg, BUN = 48±22 mg/dL, creatinine = 2.81±1.03 mg/dL. Acute kidney injury, present in 12 cases, was the most frequent end-organ complication. CONCLUSION/CONCLUSIONS:Multi-organ involvement with AKI, rhabdomyolysis, pancreatitis, neurological and cardiac issues such as arrhythmias, are common in H-DKA. Aggressive fluid management, insulin therapy and supportive care can prevent acute and long term adverse outcomes in children and adolescents.

Introduction: Children and adolescents with pre-existing type 1 diabetes (T1D) diagnosed with COVID-19 are at risk of adverse outcomes such as hospitalizations and diabetic ketoacidosis (DKA). There is limited data on the association between the presence of one or more comorbidities and the risk of adverse outcomes for patients with preexisting T1D and COVID19.
Objective(s): This study's aim is to determine if pediatric and adolescent patients with T1D and other pre-existing comorbidities were more likely to experience adverse outcomes than T1D patients with COVID-19 who did not have any other comorbidities.
Method(s): Data from 592 patients with previously established T1D aged <24 years with COVID-19 were analyzed from the T1Dx COVID-19 Surveillance Registry. Data were collected from 52 endocrinology clinics across the US using an online survey tool. Each clinic completed the survey using electronic medical record (EMR) data between April 2020 and May 2021. Descriptive statistics were used to describe the study population, and multivariate logistic regression models were used to analyze the relationship between age, insurance type, use of diabetes technology, presence of comorbidities, adverse outcomes, and hospitalization.
Result(s): The most frequent comorbidities were obesity (14%), asthma (11%), celiac disease (9%), and hypothyroidism (7%). T1D patients with at least one other comorbidity had a higher DKA presentation (16% vs 12%, p = 0.03) and a higher all-cause hospitalization rate (24% vs 15%, p = 0.02) compared to T1D patients without additional comorbidities. T1D Patients with comorbidities and COVID-19 were almost twice as likely to be hospitalized than those with no comorbidities (Odds Ratio 1.94, 95% CI: 1.23-3.03). The most frequent comorbidities were obesity (14%), asthma (11%), celiac disease (9%), and hypothyroidism (7%). T1D patients with at least one other comorbidity had a higher DKA presentation (16% vs 12%, p = 0.03) and a higher all-cause hospitalization rate (24% vs 15%, p = 0.02) compared to T1D patients without additional comorbidities. T1D Patients with comorbidities and COVID-19 were almost twice as likely to be hospitalized than those with no comorbidities (Odds Ratio 1.94, 95% CI: 1.23-3.03).
Conclusion(s): Our data reveal higher rates of hospitalizations and adverse outcomes among children and adolescents with T1D with at least one more comorbidities and COVID-19 in comparison with T1D patients without additional comorbidities. (Table Presented)

Introduction: The COVID-19 pandemic has had far-reaching consequences for individuals with type 1 diabetes (T1D) and has laid bare inequities in health care.
Objective(s): We sought to examine the United States (US) trends in diabetic ketoacidosis (DKA) across the lifespan during the COVID-19 pandemic and factors associated with these trends, compared to DKA rates the year prior to the pandemic.
Method(s): The T1D Exchange Quality Improvement Collaborative (T1DX-QI) collected aggregate data on the incidence of DKA among children and adults with established and new-onset T1D from 7 large medical centers in the US (total T1D population >15,000). We compared DKA rates during COVID-19 Wave 1 (March-May 2020) and COVID-19 Wave 2 (August-October 2020) to the same periods in 2019. Descriptive statistics were used to summarize data. Chi-square tests were used to compare differences in patient characteristics.
Result(s): DKA rates were higher in patients with established T1D during COVID-19 Wave 1 compared to the same period in 2019 (6.15% vs 4.71%, p=<0.001). DKA rates were also higher in patients with established T1D during COVID-19 Wave 2 compared to 2019 (5.55% vs 4.90%, p=0.02). There were no differences in rates of DKA by age or DKA severity. DKA rates were lower among individuals on insulin pumps during both COVID-19 waves compared to 2019 (Wave 1: 6.43% vs 10.25%, p=0.008; Wave 2: 8.14% vs 11.21%, p=0.03). Consistent with known T1D inequities, DKA rates were exacerbated for NH Black patients in 2020, with 18% of NH Blacks with T1D experiencing DKA compared to 6% of NH Whites.
Conclusion(s): DKA rates rose among patients with T1D during US COVID-19 Waves 1 and 2, with the highest rates among NH Blacks. These findings highlight the urgent need for improved strategies to decrease the risk of DKA in individuals with T1D under pandemic conditions, especially among populations most affected by health inequities

Introduction: The use of smart insulin pens has the potential to improve glucose stability, medication adherence, glycemic management, time in range, dose accuracy, quality of visits, and virtual care opportunities for patients living with diabetes.
Objective(s): The purpose of this study was to identify facilitators to smart insulin pen use by assessing provider and care team perceptions.
Method(s): The study was conducted using a mixed-methods approach. Participating endocrinology clinics within the T1D Exchange Quality Improvement Collaborative (T1Dx-QI) were recruited for this study. Four pediatric centers participated in focus group sessions while 17 clinics completed an online survey. Focus groups were transcribed, coded, and analyzed for common themes using NVivo qualitative analysis software. The online survey responses were summarized using R software.
Result(s): Smart insulin pens (SIPs) were seen as a tool to engage patients in their diabetes self-management and increase accountability for insulin administration. Improvements were noted in patient engagement. SIPs were viewed as an acceptable alternative to pump therapy. Major facilitators for smart insulin pen use are shown in Figure 1. Majority of participants reported improvement in medication adherence and glycemic management in patients using SIPs. Testimonials from providers include "Especially for the kids who didn't want to go on a pump, that they can still have a lot [benefits of dose calculator] without using a pump." "I've had a couple of teenagers really take ownership of their diabetes in sending in those reports." "It can really help to structure the clinic visits and make them more productive."
Conclusion(s): All respondents saw SIPs as a beneficial tool with provider-reported benefits to the patient, caregivers, provider, and clinic. Reports from smart insulin pens were seen as useful tools for both patients and providers. (Table Presented)

Introduction: An increase in newly diagnosed type 1 diabetes (T1D) has been posited during the COVID-19 pandemic, but data have been conflicting.
Objective(s): We aimed to determine trends in newly diagnosed T1D and severity of presentation at diagnosis for pediatric and adolescent patients during COVID-19 year (2020) as compared to the previous year (2019) in a multi-center data analysis across the United States.
Method(s): This retrospective multi-center study included data from seven large U.S. clinical centers recruited from the T1D Exchange Quality Improvement Collaborative (T1DX-QI). Data on diagnosis, diabetic ketoacidosis (DKA), and clinical characteristics were collected from January 1 to December 31, 2020, compared to the prior year. Chi-square tests were used to compare differences in patient characteristics during the pandemic compared to the pre-pandemic comparison group.
Result(s): Across seven member sites, there were 1399 newly diagnosed patients with T1D in 2020, compared to 1277 in 2019 (p=0.007). Of the newly diagnosed patients, a greater number, presented in DKA in 2020 compared to 2019 (599/1399 (42.8%) v. 493/1277 (38.6%), p<0.001), and a higher proportion of these patients presented with severe DKA (p=0.01) as characterized by a pH<7.1 or bicarbonate of <5mmol/L. The mean age at diagnosis was not different, but there were fewer females (p=0.004), and fewer NH White youth diagnosed in 2020 (p<0.001). Newly diagnosed T1D patients in 2020 were less likely to have private insurance (p=0.001). Monthly data trends demonstrated a higher number of new diagnoses of T1D over the spring and summer months (April to September) of 2020 compared to 2019 (p=0.007).
Conclusion(s): We found an increase in newly diagnosed T1D and a greater proportion of newly diagnosed T1D patients presenting in DKA at diagnosis during the COVID-19 pandemic compared to the prior year. Future longitudinal studies are needed to confirm these findings with population level data and determine the long-term impact of COVID-19 on diabetes trends

In the pediatric population, insulin pump therapy, or CSII, is often considered the gold standard for intensive diabetes management. Insulin pump technology offers families and caregivers many beneficial features including a calculator for insulin dosing and the ability to review diabetes management data to provide data-driven diabetes management. However, for those who find CSII challenging or choose to use multiple daily injections (MDI) there is an option that offers similar features called the Smart Insulin Pen (SIP). Even though SIP technology provides a safe and data-driven diabetes self-management tool for the pediatric population using MDI, there is limited pediatric specific literature. This article will describe current options, data-driven diabetes management, benefits, challenges and clinical use of SIP technology in the pediatric population.

BACKGROUND:Diabetes is a risk factor for poor COVID-19 outcomes, but pediatric patients with type 1 diabetes are poorly represented in current studies. METHODS:T1D Exchange coordinated a US type 1 diabetes COVID-19 registry. Forty-six diabetes centers submitted pediatric cases for patients with laboratory confirmed COVID-19. Associations between clinical factors and hospitalization were tested with Fisher's Exact Test. Logistic regression was used to calculate odds ratios for hospitalization. RESULTS:Data from 266 patients with previously established type 1 diabetes aged <19 years with COVID-19 were reported. Diabetic ketoacidosis (DKA) was the most common adverse outcome (n = 44, 72% of hospitalized patients). There were four hospitalizations for severe hypoglycemia, three hospitalizations requiring respiratory support (one of whom was intubated and mechanically ventilated), one case of multisystem inflammatory syndrome in children, and 10 patients who were hospitalized for reasons unrelated to COVID-19 or diabetes. Hospitalized patients (n = 61) were more likely than nonhospitalized patients (n = 205) to have minority race/ethnicity (67% vs 39%, P < 0.001), public insurance (64% vs 41%, P < 0.001), higher A1c (11% [97 mmol/mol] vs 8.2% [66 mmol/mol], P < 0.001), and lower insulin pump and lower continuous glucose monitoring use (26% vs 54%, P < 0.001; 39% vs 75%, P < 0.001). Age and gender were not associated with risk of hospitalization. Higher A1c was significantly associated with hospitalization, with an odds ratio of 1.56 (1.34-1.84) after adjusting for age, gender, insurance, and race/ethnicity. CONCLUSIONS:Higher A1c remained the only predictor for hospitalization with COVID-19. Diabetic ketoacidosis is the primary concern among this group.

OBJECTIVES/OBJECTIVE:There have been few large-scale studies utilizing exome sequencing for genetically undiagnosed maturity onset diabetes of the young (MODY), a monogenic form of diabetes that is under-recognized. We describe a cohort of 160 individuals with suspected monogenic diabetes who were genetically assessed for mutations in genes known to cause MODY. METHODS:. The average age of onset of hyperglycemia or diabetes diagnosis was 19 years (median 14 years) with an average HbA1C of 7.1%. RESULTS:. For those probands with available family members, 100% of the variants segregated with diabetes in the family. Cascade genetic testing in families identified 75 additional family members with a familial MODY mutation. CONCLUSIONS:Our study is one of the largest and most ethnically diverse studies using exome sequencing to assess MODY genes. Tiered testing is an effective strategy to genetically diagnose atypical diabetes, and familial cascade genetic testing identified on average one additional family member with monogenic diabetes for each mutation identified in a proband.