Implementation of Psychosocial Screening into Diabetes Clinics: Experience from the Type 1 Diabetes Exchange Quality Improvement Network.

PURPOSE OF REVIEW: Although advances in diabetes technology and pharmacology have significantly and positively impacted diabetes management and health outcomes for some, diabetes care remains burdensome and can be challenging to balance with other life priorities. The purpose of this article is to review the rationale for assessment of psychosocial domains in diabetes care settings and strategies for the implementation of psychosocial screening into routine practice. Survey data from the Type 1 Diabetes Exchange Quality Improvement Network is highlighted. RECENT FINDINGS: Implementation of psychosocial screening requires identifying the population; selecting validated tools to assess target domains; determining frequency of screening and mode of survey delivery; and scoring, interpreting, documenting, and facilitating referrals such that these processes are part of clinical workflows. Recognizing the influence of psychosocial factors for people with diabetes (PWD), professional society guidelines for comprehensive diabetes care recommend the integration of psychosocial screening into routine care.

Understanding pediatric long COVID using a tree-based scan statistic approach: an EHR-based cohort study from the RECOVER Program.

Objectives: Post-acute sequalae of SARS-CoV-2 infection (PASC) is not well defined in pediatrics given its heterogeneity of presentation and severity in this population. The aim of this study is to use novel methods that rely on data mining approaches rather than clinical experience to detect conditions and symptoms associated with pediatric PASC. Materials and Methods: We used a propensity-matched cohort design comparing children identified using the new PASC ICD10CM diagnosis code (U09.9) (N = 1309) to children with (N = 6545) and without (N = 6545) SARS-CoV-2 infection. We used a tree-based scan statistic to identify potential condition clusters co-occurring more frequently in cases than controls. Results: We found significant enrichment among children with PASC in cardiac, respiratory, neurologic, psychological, endocrine, gastrointestinal, and musculoskeletal systems, the most significant related to circulatory and respiratory such as dyspnea, difficulty breathing, and fatigue and malaise. Discussion: Our study addresses methodological limitations of prior studies that rely on prespecified clusters of potential PASC-associated diagnoses driven by clinician experience. Future studies are needed to identify patterns of diagnoses and their associations to derive clinical phenotypes. Conclusion: We identified multiple conditions and body systems associated with pediatric PASC. Because we rely on a data-driven approach, several new or under-reported conditions and symptoms were detected that warrant further investigation.

4. Comprehensive Medical Evaluation and Assessment of Comorbidities: Standards of Care in Diabetes-2023.

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Impact of diabetes status and related factors on COVID-19-associated hospitalization: A nationwide retrospective cohort study of 116,370 adults with SARS-CoV-2 infection.

AIMS: We examined diabetes status (no diabetes; type 1 diabetes [T1D]; type 2 diabetes [T2D]) and other demographic and clinical factors as correlates of coronavirus disease 2019 (COVID-19)-related hospitalization. Further, we evaluated predictors of COVID-19-related hospitalization in T1D and T2D. METHODS: We analyzed electronic health record data from the de-identified COVID-19 database (December 2019 through mid-September 2020; 87 US health systems). Logistic mixed models were used to examine predictors of hospitalization at index encounters associated with confirmed SARS-CoV-2 infection. RESULTS: In 116,370 adults (>=18 years old) with COVID-19 (93,098 no diabetes; 802 T1D; 22,470 T2D), factors that independently increased risk for hospitalization included diabetes, male sex, public health insurance, decreased body mass index (BMI; <25.0-29.9 kg/m2), increased BMI (>25.0-29.9 kg/m2), vitamin D deficiency/insufficiency, and Elixhauser comorbidity score. After further adjustment for concurrent hyperglycemia and acidosis in those with diabetes, hospitalization risk was substantially higher in T1D than T2D and in those with low vitamin D and elevated hemoglobin A1c (HbA1c). CONCLUSIONS: The higher hospitalization risk in T1D versus T2D warrants further investigation. Modifiable risk factors such as vitamin D deficiency/insufficiency, BMI, and elevated HbA1c may serve as prognostic indicators for COVID-19-related hospitalization in adults with diabetes.

The COVID-19 Pandemic Affects Seasonality, With Increasing Cases of New-Onset Type 1 Diabetes in Children, From the Worldwide SWEET Registry.

OBJECTIVE: To analyze whether the coronavirus disease 2019 (COVID-19) pandemic increased the number of cases or impacted seasonality of new-onset type 1 diabetes (T1D) in large pediatric diabetes centers globally. RESEARCH DESIGN AND METHODS: We analyzed data on 17,280 cases of T1D diagnosed during 2018-2021 from 92 worldwide centers participating in the SWEET registry using hierarchic linear regression models. RESULTS: The average number of new-onset T1D cases per center adjusted for the total number of patients treated at the center per year and stratified by age-groups increased from 11.2 (95% CI 10.1-12.2) in 2018 to 21.7 (20.6-22.8) in 2021 for the youngest age-group, <6 years; from 13.1 (12.2-14.0) in 2018 to 26.7 (25.7-27.7) in 2021 for children ages 6 to <12 years; and from 12.2 (11.5-12.9) to 24.7 (24.0-25.5) for adolescents ages 12-18 years (all P < 0.001). These increases remained within the expected increase with the 95% CI of the regression line. However, in Europe and North America following the lockdown early in 2020, the typical seasonality of more cases during winter season was delayed, with a peak during the summer and autumn months. While the seasonal pattern in Europe returned to prepandemic times in 2021, this was not the case in North America. Compared with 2018-2019 (HbA1c 7.7%), higher average HbA1c levels (2020, 8.1%; 2021, 8.6%; P < 0.001) were present within the first year of T1D during the pandemic. CONCLUSIONS: The slope of the rise in pediatric new-onset T1D in SWEET centers remained unchanged during the COVID-19 pandemic, but a change in the seasonality at onset became apparent.

An Evaluation of Point-of-Care HbA1c, HbA1c Home Kits, and Glucose Management Indicator: Potential Solutions for Telehealth Glycemic Assessments.

During the COVID-19 pandemic, fewer in-person clinic visits resulted in fewer point-of-care (POC) HbA1c measurements. In this sub-study, we assessed the performance of alternative glycemic measures that can be obtained remotely, such as HbA1c home kits and Glucose Management Indicator (GMI) values from Dexcom Clarity. Home kit HbA1c (n = 99), GMI, (n = 88), and POC HbA1c (n = 32) were collected from youth with T1D (age 9.7 ± 4.6 years). Bland-Altman analyses and Lin's concordance correlation coefficient (ρc) were used to characterize the agreement between paired HbA1c measures. Both the HbA1c home kit and GMI showed a slight positive bias (mean difference 0.18% and 0.34%, respectively) and strong concordance with POC HbA1c (ρc = 0.982 [0.965, 0.991] and 0.823 [0.686, 0.904], respectively). GMI showed a slight positive bias (mean difference 0.28%) and fair concordance (ρc = 0.750 [0.658, 0.820]) to the HbA1c home kit. In conclusion, the strong concordance of GMI and home kits to POC A1c measures suggest their utility in telehealth visits assessments. Although these are not candidates for replacement, these measures can facilitate telehealth visits, particularly in the context of other POC HbA1c measurements from an individual.

'Much more convenient, just as effective': Experiences of starting continuous glucose monitoring remotely following Type 1 diabetes diagnosis.

AIM: Initiating continuous glucose monitoring (CGM) shortly after Type 1 diabetes diagnosis has glycaemic and quality of life benefits for youth with Type 1 diabetes and their families. The SARS-CoV-2 pandemic led to a rapid shift to virtual delivery of CGM initiation visits. We aimed to understand parents' experiences receiving virtual care to initiate CGM within 30 days of diagnosis. METHODS: We held focus groups and interviews using a semi-structured interview guide with parents of youth who initiated CGM over telehealth within 30 days of diagnosis during the SARS-CoV-2 pandemic. Questions aimed to explore experiences of starting CGM virtually. Groups and interviews were audio-recorded, transcribed and analysed using thematic analysis. RESULTS: Participants were 16 English-speaking parents (age 43 ± 6 years; 63% female) of 15 youth (age 9 ± 4 years; 47% female; 47% non-Hispanic White, 20% Hispanic, 13% Asian, 7% Black, 13% other). They described multiple benefits of the virtual visit including convenient access to high-quality care; integrating Type 1 diabetes care into daily life; and being in the comfort of home. A minority experienced challenges with virtual care delivery; most preferred the virtual format. Participants expressed that clinics should offer a choice of virtual or in-person to families initiating CGM in the future. CONCLUSION: Most parents appreciated receiving CGM initiation education via telehealth and felt it should be an option offered to all families. Further efforts can continue to enhance CGM initiation teaching virtually to address identified barriers.

BMI Changes in Youth with Type 2 Diabetes during COVID-Shelter-in-Place: The Role of Neighborhood Risk Factors

The California government imposed a shelter-in-place (SIP) order on 3/15/2020 to slow the spread of COVID-19. For many children and adolescents, particularly youth with type 2 diabetes (T2D) , school closures led to major changes in daily routines, affecting physical activity levels and dietary choices. We performed a retrospective descriptive study on youth ages 7 to 21 years with T2D who were seen at our health care system at least one time in the year preceding SIP and again in the year after, allowing us to calculate change in BMI over time during SIP. Utilizing databases from the United States government, we examined the effects of living in an area with at least one risk factor ("food deserts" with a paucity of healthy food, "food swamps" with an abundance of unhealthy food, or rural regions) on BMI change compared to low-risk neighborhoods. We included 78 youth with T2D and 46% lived in at-risk areas. Overall, youth had a slight increase in BMI during SIP (0.± 0.2 kg/m2/month) . Youth living in at-risk areas had a rise in BMI during this time period (0.02 ± 0.2 kg/m2/month) , whereas youth in low-risk areas had a small drop in BMI (-0.± 0.2 kg/m2/month) . As this study was not powered to detect group differences, further investigation of neighborhood risk factors is needed to aid in tailoring community-level interventions to combat obesity in youth with T2D.

Closing Disparities in Pediatric Diabetes Telehealth Care: Lessons From Telehealth Necessity During the COVID-19 Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic necessitated using telehealth to bridge the clinical gap, but could increase health disparities. This article reports on a chart review of diabetes telehealth visits occurring before COVID-19, during shelter-in-place orders, and during the reopening period. Visits for children with public insurance and for those who were non-English speaking were identified. Telehealth visits for children with public insurance increased from 26.2% before COVID-19 to 37.3% during shelter-in-place orders and 34.3% during reopening. Telehealth visits for children who were non-English speaking increased from 3.5% before COVID-19 to 17.5% during shelter-in-place orders and remained at 15.0% during reopening. Pandemic-related telehealth expansion included optimization of workflows to include patients with public insurance and those who did not speak English. Increased participation by those groups persisted during the reopening phase, indicating that prioritizing inclusive telehealth workflows can reduce disparities in access to care.

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.

Understanding CGM Metrics in Children with T1D Before and After the COVID-19 Shelter-in-Place Order

To slow the spread of COVID-19, a shelter in place (SIP) order was imposed in California between 03/16/2020 - 05/31/2020. We assessed the impact of SIP on glycemic control in a pediatric population with T1D using a continuous glucose monitor (CGM). We hypothesized that glucose control would improve due to increased supervision at home. The retrospective study included 96 patients between the ages of 3-22 years who were diagnosed with T1D at least one year earlier. We analyzed CGM data during three time periods: baseline, SIP, and post SIP (06/01/2020 - 07/30/2020) and compared standard CGM metrics controlling for gender (56% male), race (55% White), ethnicity (70% non-Hispanic), age (mean 11 yrs ± 3.9), and insurance type (8.4% public). The mean time in range (70-180 mg/dL: TIR) increased across the three time periods: from 59.9% ± 15.1 at baseline to 62.8% ± 15.9 during SIP (p<0.001) and maintained at 63.5% ± 16.6 during post-SIP period (p=0.23) compared with SIP. Increases in TIR were seen in both privately insured (2.9% ± 6.0) and publicly insured (3.7% ± 6.2) individuals during SIP vs. baseline with no increase in time with hypoglycemia (<70 mg/dl) in privately insured (0.1% ± 1.4) and publicly insured (-0.08%±1.3). Our analyses highlight the impact of the SIP order on glycemic control. Better understanding of the factors associated with improved TIR could translate to better glycemic control post-COVID.

Good Concordance between Home Kit A1C, Glucose Management Indicator, and Point-of-Care A1C: Potential Solutions to Glycemic Assessment during the SARS CoV-2 Pandemic

Due to the SARS CoV-2 pandemic, fewer in-person clinic visits have resulted in fewer point-of-care (POC) A1c measurements in youth with T1D. Therefore, there is an increased need to use alternate methods to assess A1c, including continuous glucose monitoring-derived Glucose Management Indicator (GMI) and home kit A1c. The University of Minnesota's home kit A1c (n=59), GMI (n=56), and POC A1c (n=16) were collected from youth with T1D (age 10.0 [5.3, 13.0] years, 42% female, and baseline A1c 12.4 ± 2.2%). Matched pairs were used for Bland Altman analyses and Lin's concordance correlation coefficient (pc) to evaluate the agreement between A1c measures. GMI data (up to 90 days) was captured using Dexcom Clarity. In relation to POC A1c, both home kit A1c (panel A) and GMI (panel B) showed a slight positive bias (mean difference 0.13 and 0.22%, respectively). Home kit A1c and GMI showed strong concordance to POC A1c (pc = 0.987 [0.963, 0.995] and 0.930 [0.835, 0.971], respectively). GMI (panel C) also showed a slight positive bias (mean difference 0.26%) and good concordance (pc = 0.803 [0.703, 0.871]) to home kit A1c. These data demonstrate that home kit A1c and GMI show strong concordance with POC A1c. Overall, home kit A1c and GMI may be potential solutions to glycemic assessment for telehealth visits, including during the SARS CoV-2 pandemic.

Improved individual and population-level HbA1c estimation using CGM data and patient characteristics.

Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by COVID-19.