Comorbidities increase COVID-19 hospitalization in young people with type 1 diabetes.

OBJECTIVES: We evaluated COVID-19 outcomes in children and young adults with type 1 diabetes (T1D) to determine if those with comorbidities are more likely to experience severe COVID-19 compared to those without. RESEARCH DESIGN AND METHODS: This cross-sectional study included questionnaire data on patients <25 years of age with established T1D and laboratory-confirmed COVID-19 from 52 sites across the US between April 2020 and October 2021. We examined patient factors and COVID-19 outcomes between those with and without comorbidities. Multivariate logistic regression analysis examined the odds of hospitalization among groups, adjusting for age, HbA1c, race and ethnicity, insurance type and duration of diabetes. RESULTS: Six hundred fifty-one individuals with T1D and COVID-19 were analyzed with mean age 15.8 (SD 4.1) years. At least one comorbidity was present in 31%, and more than one in 10%. Obesity and asthma were the most frequently reported comorbidities, present in 19% and 17%, respectively. Hospitalization occurred in 17% of patients and 52% of hospitalized patients required ICU level care. Patients with at least one comorbidity were almost twice as likely to be hospitalized with COVID-19 than patients with no comorbidities (Odds ratio 2.0, 95% CI: 1.3-3.1). This relationship persisted after adjusting for age, HbA1c, race and ethnicity (minority vs nonminority), insurance type (public vs. private), and duration of diabetes. CONCLUSIONS: Our findings show that comorbidities increase the risk for hospitalization with COVID-19 in children and young adults highlighting the need for tailored COVID-19 prevention and treatment strategies in T1D.

Variation in nutrition education practices in SWEET pediatric diabetes centers-an international comparison.

BACKGROUND: Nutrition education is central to pediatric type 1 diabetes management. Dietary management guidelines for type 1 diabetes are evidence based, but implementation may be challenging and inconsistent. We describe variation in the practice of nutrition education across pediatric diabetes centers globally and explore associations with A1c and BMI. METHODS: In 2018, 77 pediatric diabetes clinics in the SWEET network received a survey about nutrition education. Using data submitted to the registry, regression analysis corrected for age, diabetes duration, BMI, and sex was used to compare survey parameters with A1c and BMI. RESULTS: Fifty-three centers who collectively cared for 22,085 patients aged 0 to 18 with type 1 diabetes responded. Median A1c was 7.68% [IQR 7.37-8.03], age 13.13 y [12.60-13.54], insulin pump use 39.1%, and continuous glucose monitor use 37.3%. 34% reported screening for disordered eating, but only 15.1% used validated screening tools. Recommending insulin boluses for snacks in patients taking insulin via injection varied, with 23% of the clinics giving this recommendation to half or fewer patients. In regression analysis, instructing patients to take insulin for snacks was the only survey parameter associated with the percent of clinic percent of patients attaining A1c <7.5% (<58 mmol/mol, P = 0.018) and < 7.0% (<53 mmol/mol, P = 0.026). CONCLUSIONS: There is considerable variation in nutrition education for pediatric patients with type 1 diabetes across this international registry. Consistently recommending independent of treatment modality (insulin pump or injections) that patients take insulin for snacks and more uniformity in screening for disordered eating are improvement opportunities.

Erratum. Establishment of the T1D Exchange Quality Improvement Collaborative (T1DX-QI). Clinical Diabetes 2020;38:141-151 (DOI: 10.2337/cd19-0032).

[This corrects the article on p. 141 in vol. 38, PMID: 32327886.].

Establishment of the T1D Exchange Quality Improvement Collaborative (T1DX-QI).

The T1D Exchange established a learning platform by evaluating the current state of care and engaging 10 diabetes clinics in collaborative quality improvement (QI) activities. Participating clinics are sharing data and best practices to improve care delivery for people with type 1 diabetes. This article describes the design and initial implementation of this platform, known as the T1D Exchange Quality Improvement Collaborative. This effort has laid a foundation for learning from variation in type 1 diabetes care delivery via QI methodology and has demonstrated success in improving processes through iterative testing cycles and transparent sharing of data.

Weight gain after treatment of Graves' disease in children.

OBJECTIVE: The frequency of and risk factors for weight gain in children treated for Graves' disease have not been described. We evaluated change in BMI-Z score and predictors of weight gain in this population. DESIGN: Retrospective review of data from January 2000 to July 2011. PATIENTS: Two hundred and twenty two children and adolescents with Graves' disease (ages 2-18 years) evaluated following radioactive iodine administration (RAI); (n = 101), thyroidectomy (n = 9) and initiation of medical therapy (n = 112). MEASUREMENTS: Changes in body mass index Z score over 12 months (ΔBMI-Z0-12 ). RESULTS: All treatment groups in each gender and race increased BMI-Z (median ΔBMI-Z0-12 was positive). T3 levels following RAI (P = .04) and weight lost at the time of administration (P = .02) in the RAI group and free T4 levels in the medical therapy group (P = .03) were positively correlated with ΔBMI-Z0-12 . Race was a significant predictor only in the medical therapy group (P = .01). Age negatively correlated with ΔBMI-Z0-12 in both the RAI (P < .001) and medical therapy groups (P = .003). Gender, maximum TSH in the 12 months after RAI and initial dose of LT4 replacement did not correlate with ΔBMI-Z0-12 . The prevalence of overweight and obesity in our cohort was similar to US children. CONCLUSIONS: Weight gain during treatment for Graves' disease is common in children, and many children become overweight or obese during treatment. Risk factors include greater degree of hyperthyroidism at presentation and time of RAI and younger age. Weight lost upon presentation may also predict greater weight gain. Control of subsequent hypothyroidism does not appear to affect weight gain.

Racial Disparities in Diabetes Technology Adoption and Their Association with HbA1c and Diabetic Ketoacidosis.

Aim: Poorer glycemic control and higher diabetic ketoacidosis (DKA) rates are seen in racial/ethnic minorities with type 1 diabetes (T1D). Use of diabetes technologies such as continuous glucose monitors (CGM), continuous subcutaneous insulin infusion (CSII) and automated insulin delivery (AID) systems has been shown to improve glycemic control and reduce DKA risk. We examined race/ethnicity differences in diabetes technology use and their relationship with HbA1c and DKA. Methods: Data from patients aged ≥12 years with T1D for ≥1 year, receiving care from a single diabetes center, were examined. Patients were classified as Non-Hispanic White (n=3945), Non-Hispanic Black (Black, n=161), Hispanic (n=719), and Multiracial/Other (n=714). General linear models and logistic regression were used. Results: Black (OR=0.22, 0.15-0.32) and Hispanic (OR=0.37, 0.30-0.45) patients were less likely to use diabetes technology. This disparity was greater in the pediatric population (p-interaction=0.06). Technology use associated with lower HbA1c in each race/ethnic group. Among technology users, AID use associated with lower HbA1c compared to CGM and/or CSII (HbA1c of 8.4% vs 9.2%, respectively), with the greatest difference observed for Black adult AID users. CSII use associated with a lower odds of DKA in the past year (OR=0.73, 0.54-0.99), a relationship that did not vary by race (p-interaction =0.69); this inverse association with DKA was not observed for CGM or AID. Conclusion: Disparities in diabetes technology use, DKA, and glycemic control were apparent among Black and Hispanic patients with T1D. Differences in technology use ameliorated but did not fully account for disparities in HbA1c or DKA.

Glycemic Control in Relation to Technology Use in a Single-Center Cohort of Children with Type 1 Diabetes.

Background: Technology for patients with type 1 diabetes (T1D), including continuous glucose monitoring (CGM), insulin pumps, and hybrid closed-loop (HCL) systems, is improving, being used more commonly in the pediatric population, and impacts glycemic control. Materials and Methods: We evaluated the use of these technologies and their impact on glycemic control among patients with T1D who were seen at the Barbara Davis Center (n = 4003) between January 2018 and December 2020, <22 years old, with diabetes duration >3 months. Data were analyzed by age group and technology-use group defined as multiple daily injection with blood glucose meter (MDI/BGM), pump with BGM (pump/BGM), MDI with CGM (MDI/CGM), and pump with CGM (pump/CGM). Glycemic control was compared using analysis of covariance (ANCOVA) and controlling for diabetes duration, race, and insurance. Results: Among 4003 patients, 20% used MDI/BGM (mean hemoglobin A1c [HbA1c] = 10.0%); 14.4% used pump/BGM (mean HbA1c = 10.0%); 15.4% used MDI/CGM (mean HbA1c = 8.6%); and 49.8% used pump/CGM (mean HbA1c = 8.1%). Compared with MDI/BGM patients, MDI/CGM and pump/CGM users had a lower HbA1c and were more likely to reach an HbA1c <7.0% (all P < 0.0001). Among pump/CGM users, 35% used HCL technology (mean HbA1c = 7.6%) and had a lower HbA1c and were more likely to reach an HbA1c <7% than non-HCL users (P < 0.001). Conclusions: CGM use was associated with a lower HbA1c in both MDI and pump users. Pump use was only associated with a lower HbA1c if used with CGM. HCL was associated with the lowest HbA1c. Spanish language and minority race/ethnicity were associated with lower rates of pump and CGM use, highlighting the need to reduce disparities.

Diabetes Technology Use in Remote Pediatric Patients with Type 1 Diabetes Using Clinic-to-Clinic Telemedicine.

Background: Clinic-to-clinic telemedicine can increase visit frequency in pediatric patients with type 1 diabetes (T1D) living far from a diabetes specialty clinic, but the impact on adoption of diabetes technology is unclear. Materials and Methods: Pediatric patients with T1D in Colorado and surrounding states who received diabetes care using clinic-to-clinic telemedicine were enrolled. Medical records and surveys were reviewed to ascertain technology use, and data were compared to patients from the main clinic population. Results: Patients (N = 128, baseline mean age 12.4 ± 4.2 years, median T1D duration 3.3 years [IQR 1.4-7.7], mean A1c 8.9% ± 1.8%, 60% male, 75% non-Hispanic white, 77% private insurance) who utilized telemedicine were included. Technology use among telemedicine patients was not associated with gender, T1D duration, insurance, distance from the main clinic or rural designation but was associated with ethnicity and A1c. Compared to the main clinic cohort (N = 3636), continuous glucose monitor (CGM) use and pump/CGM combination use was lower among patients participating in clinic-to-clinic telemedicine (CGM: 29.7% vs. 56.0%, P < 0.001; CGM/pump combination: 27.3% vs. 40.3%, P = 0.004). Technology use was associated with lower A1c regardless of cohort. Conclusions: Compared to patients attending in-person clinic, pediatric T1D patients who use clinic-to-clinic telemedicine due to their distance from the main clinic, have lower CGM and combination CGM/pump use. For both telemedicine and main clinic patients, CGM and CGM/pump combination was associated with lower A1c. Additional research is needed to explore reasons for this discrepancy and find methods to improve CGM use in this population.

Increased DKA at presentation among newly diagnosed type 1 diabetes patients with or without COVID-19: Data from a multi-site surveillance registry.

Highlights Our multicenter study reports a higher proportion of diabetic ketoacidosis presentation of over 60% in newly diagnosed patients with type 1 diabetes with or without confirmed coronavirus disease 2019 (COVID-19) at diagnosis. This finding is suggestive of delays in seeking care during the COVID-19 pandemic.

Adoption of Telemedicine for Type 1 Diabetes Care During the COVID-19 Pandemic.

Background: We describe the utilization of telemedicine visits (video or telephone) across the type 1 diabetes (T1D) Exchange Quality Improvement Collaborative (T1DX-QI) during the COVID-19 pandemic. Metrics, site-level survey results, and examples of interventions conducted to support telemedicine in T1D are shown. Materials and Methods: Thirteen clinics (11 pediatric, 2 adult) provided monthly telemedicine metrics between December 2019 and August 2020 and 21 clinics completed a survey about their telemedicine practices. Results: The proportion of telemedicine visits in T1DX-QI before the pandemic was <1%, rising to an average of 95.2% in April 2020 (range 52.3%-99.5%). Three sites initially used mostly telephone visits before converting to video visits. By August 2020, the proportion of telemedicine visits decreased to an average of 45% across T1DX-QI (range 10%-86.6%). The majority of clinics (62%) performed both video and telephone visits; Zoom was the most popular video platform used. Over 95% of clinics reported using CareLink™, Clarity®, Glooko™, and/or t:connect® to view device data, with only one center reporting automated data upload into the electronic medical record. The majority of centers had multidisciplinary teams participating in the video visits. All sites reported reimbursement for video visits, and 95% of sites reported coverage for telephone visits early on in the pandemic. Conclusions: There was rapid adoption of telemedicine in T1DX-QI during the COVID-19 pandemic. Future insurance reimbursement for telemedicine visits and the ideal ratio of telemedicine to in-person visits in T1D care remain to be determined.

Diabetic ketoacidosis drives COVID-19 related hospitalizations in children with type 1 diabetes.

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.

Inequities in Diabetic Ketoacidosis Among Patients With Type 1 Diabetes and COVID-19: Data From 52 US Clinical Centers.

OBJECTIVE: We examined whether diabetic ketoacidosis (DKA), a serious complication of type 1 diabetes (T1D) was more prevalent among Non-Hispanic (NH) Black and Hispanic patients with T1D and laboratory-confirmed coronavirus disease 2019 (COVID-19) compared with NH Whites. METHOD: This is a cross-sectional study of patients with T1D and laboratory-confirmed COVID-19 from 52 clinical sites in the United States, data were collected from April to August 2020. We examined the distribution of patient factors and DKA events across NH White, NH Black, and Hispanic race/ethnicity groups. Multivariable logistic regression analysis was performed to examine the odds of DKA among NH Black and Hispanic patients with T1D as compared with NH White patients, adjusting for potential confounders, such as age, sex, insurance, and last glycated hemoglobin A1c (HbA1c) level. RESULTS: We included 180 patients with T1D and laboratory-confirmed COVID-19 in the analysis. Forty-four percent (n = 79) were NH White, 31% (n = 55) NH Black, 26% (n = 46) Hispanic. NH Blacks and Hispanics had higher median HbA1c than Whites (%-points [IQR]: 11.7 [4.7], P < 0.001, and 9.7 [3.1] vs 8.3 [2.4], P = 0.01, respectively). We found that more NH Black and Hispanic presented with DKA compared to Whites (55% and 33% vs 13%, P < 0.001 and P = 0.008, respectively). After adjusting for potential confounders, NH Black patients continued to have greater odds of presenting with DKA compared with NH Whites (OR [95% CI]: 3.7 [1.4, 10.6]). CONCLUSION: We found that among T1D patients with COVID-19 infection, NH Black patients were more likely to present in DKA compared with NH White patients. Our findings demonstrate additional risk among NH Black patients with T1D and COVID-19.