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Precision medicine starts with a precision diagnosis. Yet up to 80% of cases of monogenic diabetes, a form of diabetes characterized by mutations in a single gene, are either overlooked or misdiagnosed. A genetic test for monogenic diabetes does not always lead to a precise diagnosis, as novel variants are often classified as variants of unknown significance. Variant interpretation requires collation of a framework of evidence, including population, computational, and segregation data, and can be assisted by functional analysis. The inclusion of functional data can be challenging, depending on the number of benign and pathogenic variants available for benchmarking assays. Glucokinase is the rate-limiting step for glucose metabolism in the pancreatic beta-cell and governs the threshold for glucose-stimulated insulin release. Loss-of-function alleles in the glucokinase (GCK) gene are a cause of stable fasting hyperglycemia from birth and/or diabetes. In this study, we functionally characterized 25 variants identified during diagnostic testing or in exome sequencing studies. We assessed their kinetic characteristics, stability, and interaction with pharmacological and physiological regulators. We integrated our functional data with existing data from the ClinGen Monogenic Diabetes Variant Curation Expert Review panel using a gene-specific framework to assist variant classification. We show how functional evidence can aid variant classification, thus enabling diagnostic certainty.

ObjectivesIndividuals under-recruited in diabetes research studies include those not seen at endocrinology centres and those from rural, low socioeconomic and/or under-represented racial/ethnic groups. The purpose of this descriptive analysis is to detail recruitment and retention efforts of Project ECHO Diabetes clinical sites affiliated with Stanford University and University of Florida.DesignProspective collection of participant engagement and qualitative analysis of barriers and facilitators of research engagement within Project ECHO Diabetes, a virtual tele-education programme for healthcare providers in the management of individuals with insulin-requiring diabetes.SettingData were collected at the patient level, provider level and clinic level between 1 May 2021 and 31 July 2022.ParticipantsParticipants and study personnel were recruited from 33 Project ECHO Diabetes sites in California and Florida.OutcomesWe report study completion rates for participants recruited into 33 Project ECHO Diabetes sites. Using barrier analysis, a methodology designed for the real-time assessment of interventions and system processes to identify barriers and facilitators, study personnel identified significant barriers to recruitment and retention and mapped them to actionable solutions.ResultsIn total, 872 participants (California n=495, Florida n=377) were recruited with differing recruitment rates by site (California=52.7%, Florida=21.5%). Barrier analysis identified lack of trust, unreliable contact information, communication issues and institutional review board (IRB) requirements as key recruitment barriers. Culturally congruent staff, community health centre (CHC) support, adequate funding and consent process flexibility were solutions to address recruitment challenges. Barriers to retention were inconsistent postal access, haemoglobin A1c kit collection challenges, COVID-19 pandemic and broadband/connectivity issues. Additional funding supporting research staff and analogue communication methods were identified as solutions address barriers to retention.ConclusionsFunded partnerships with CHCs, trusted by their local communities, were key in our recruitment and retention strategies. IRB consent process flexibility reduced barriers to recruitment. Recruiting historically under-represented populations is feasible with funding aimed to address structural barriers to research participation.

Background Microcephaly, epilepsy, and diabetes syndrome (MEDS) is a rare syndromic form of monogenic diabetes caused by bi-allelic loss of function mutations in IER3IP1 . In vitro studies have shown that loss of IER31P leads to apoptosis in both neurons and pancreatic β-cells. Simultaneous management of seizures and diabetes is challenging in patients with MEDS. We present the challenges and successes in the use of ketogenic diet in an infant with insulinopenic diabetes. Case presentation Our term female proband presented at 2 months of age with new onset multifocal seizures followed by the onset of infantile spasms (IS) at 4 months of age. An epilepsy gene panel identified bi-allelic variants, c.239T > G (p.Leu80*) and c.2T > A (initiator codon), in IER3IP1 that were subsequently shown to be inherited in trans. Following initiation of steroid therapy for IS, the patient developed clinically apparent insulin requiring diabetes. Her epilepsy was ultimately refractory to multiple antiseizure medications, thus the ketogenic diet (KD) was initiated. We were able to successfully titrate to a therapeutic KD ratio of 3:1 and maintain a ketotic state without diabetic ketoacidosis (DKA). With intercurrent illnesses, however, the patient had rapid decompensation and mild DKA due to delays in treatment, and for this reason, KD was discontinued after 5 months. Conclusions We report two novel IER31P1 mutations in a patient with MEDS and the successful management of the cooccurring conditions of IS and insulinopenic diabetes with the KD. Our experience underscores the importance of careful monitoring during KD as our patient had DKA more easily when on the KD.

Clinics continue to adopt care models shaped by the algorithmic analysis of continuous glucose monitoring (CGM) data, such as remote patient monitoring for type 1 diabetes. No clinic-facing quantitative framework currently exists to track the impact of such algorithm-directed care on patient outcomes and clinical workload. We used CGM data from the Teamwork, Targets, Technology, and Tight Control (4T) Study (Pilot n=135 and Study 1 n=133), in which algorithms enable precision, whole-population care by directing clinician attention to patients with deteriorating glucose management. Youth meeting criteria for clinical review are then contacted by Certified Diabetes Care and Education Specialists. Through iterative data analysis and meetings with a variety of stakeholders, we identified metrics for reviewing and revising clinical workloads, glucose management, and timeliness of care. For each metric, we developed an interactive dashboard to provide clinical and administrative leaders with an overview of the program. The metrics to track clinical workload were the total number of youths (1) in the program, (2) in each study, and (3) cared for by each clinician. The metrics to track glucose management were the number of youths meeting each criterion for review, including (4) total, (5) for each clinician, and (6) for each study. The metric to track timeliness of care was (7) the number of days since meeting criteria for clinical review. When presented at regular program leadership meetings, the metrics facilitated data-driven decision-making about clinical and operational components of the program. In this paper, we describe the process of developing and operationalizing this reproducible, clinician-facing key performance indicator tool to monitor an algorithm-enabled remote patient monitoring program. As the role of algorithms grows in directing clinical effort and prioritizing patients for care, this framework may help clinics track clinical workload, patient outcomes, and the timeliness of care.

摘要 背景:DiabetesWise是一个无品牌的, 以数据驱动的在线资源, 根据胰岛素需求者的偏好和优先事项, 量身定制设备推荐。本研究的目的是研究DiabetesWise是否能增加胰岛素需求者使用胰岛素治疗设备的比率, 这些设备经过实证支持可改善血糖和心理社会结果。 方法:样本包括458名参与者(平均年龄=37.1岁, 标准差=9.73；66%女性；81%为1型糖尿病患者), 这些参与者在入组时使用胰岛素治疗且对糖尿病设备的使用较少。参与者使用DiabetesWise并完成在线调查。使用卡方检验和t检验评估使用DiabetesWise后1个月和3个月内器械处方请求, 接受处方和开始使用新设备的比率。还研究了这些变量的基线预测因素, 过去连续血糖监测(CGM)使用情况以及使用后糖尿病困扰变化。 结果:在与DiabetesWise互动的第一个月内, 有19%的参与者要求处方以获取糖尿病设备。在前三个月内, 这一比率上升至31%。这些要求导致了样本中16%的参与者在前三个月内开始使用新的设备。虽然几个因素与先前CGM使用, 接受处方和开始使用新设备有关, 但更多的糖尿病困扰(t(343)=‐3.13, p=0.002)是要求处方的唯一相关因素。与DiabetesWise互动后, 一个月内(t(193)=3.51, p<0.001)和三个月内(t(180)=5.23, p<0.001), 糖尿病困扰程度减少。 结论:在与DiabetesWise互动的三个月内, 三分之一的参与者要求处方以获取新的糖尿病设备, 并且平均困扰程度降低, 表明这个低强度在线平台具有益处。

Digital Technology for DiabetesMonitors to measure glucose levels have been paired with software controlling insulin delivery. The authors examine the state of the art in digital technology to manage diabetes (types 1 and 2).

Background: There are well-documented disparities in diabetes care outcomes and technology usage, stemming from differences in healthcare access, distrust in healthcare providers, and other factors. This study evaluated patient-level outcomes of a diabetes support coach (DSC) intervention aimed at improving underserved adults’ diabetes technology use, diabetes distress, and HbA1c levels.Methods: As part of a Project Extension for Community Healthcare Outcomes (ECHO) Diabetes program, a social support intervention involving 28 DSCs was piloted at 33 Federally Qualified Health Centers (FQHCs) in Florida and California from May 2021 to May 2022. DSCs, who were adults with diabetes, served in a capacity similar to peer mentors and community health workers and received uniform training/oversight by a clinical team. Intervention participants (n=74 adults with insulin-requiring diabetes at FQHCs) self-enrolled and engaged with DSCs via text messages, phone calls, and events. Participants’ outcomes were evaluated cross-sectionally via the Diabetes Distress Scale (DDS-17) and a diabetes technology usage survey and longitudinally via HbA1c tests upon enrollment and at 6-month follow-up. A group of adults with insulin-requiring diabetes from the same FQHCs who did not receive the DSC intervention (n=363) was used for comparison. Descriptive statistics were computed for all outcomes (n, percentage; mean, SD/95% CI). Between-group comparisons were evaluated via chi-squared and t-tests.Results: DSC intervention participants reported significantly lower diabetes distress than the comparison group (DDS-17 score mean=1.6 vs. 2.1, p<0.001), and significantly more participants in the DSC intervention regularly used continuous glucose monitors (CGMs) than the comparison group (69.9% vs. 38.8%, p<0.0001). There were no significant differences in insulin pump usage or HbA1c.Conclusions: Lower diabetes distress and greater CGM usage among intervention participants suggest that the DSCs’ shared lived experiences and healthcare navigation support positively influenced underserved adults’ outcomes. These findings show DSCs’ potential for improving diabetes care and technology equity.

IntroductionDiabetes disparities exist based on socioeconomic status, race, and ethnicity. The aim of this study is to compare two cohorts with diabetes from California and Florida to better elucidate how health outcomes are stratified within underserved communities according to state location, race, and ethnicity.Research design and methodsTwo cohorts were recruited for comparison from 20 Federally Qualified Health Centers as part of a larger ECHO Diabetes program. Participant-level data included surveys and HbA1c collection. Center-level data included Healthcare Effectiveness Data and Information Set metrics. Demographic characteristics were summarized overall and stratified by state (frequencies, percentages, means (95% CIs)). Generalized linear mixed models were used to compute and compare model-estimated rates and means.ResultsParticipant-level cohort: 582 adults with diabetes were recruited (33.0% type 1 diabetes (T1D), 67.0% type 2 diabetes (T2D)). Mean age was 51.1 years (95% CI 49.5, 52.6); 80.7% publicly insured or uninsured; 43.7% non-Hispanic white (NHW), 31.6% Hispanic, 7.9% non-Hispanic black (NHB) and 16.8% other. Center-level cohort: 32 796 adults with diabetes were represented (3.4% with T1D, 96.6% with T2D; 72.7% publicly insured or uninsured). Florida had higher rates of uninsured (p<0.0001), lower continuous glucose monitor (CGM) use (18.3% Florida; 35.9% California, p<0.0001), and pump use (10.2% Florida; 26.5% California, p<0.0001), and higher proportions of people with T1D/T2D>9% HbA1c (p<0.001). Risk was stratified within states with NHB participants having higher HbA1c (mean 9.5 (95% CI 8.9, 10.0) compared with NHW with a mean of 8.4 (95% CI 7.8, 9.0), p=0.0058), lower pump use (p=0.0426) and CGM use (p=0.0192). People who prefer to speak English were more likely to use a CGM (p=0.0386).ConclusionsCharacteristics of medically underserved communities with diabetes vary by state and by race and ethnicity. Florida’s lack of Medicaid expansion could be a factor in worsened risks for vulnerable communities with diabetes.

Objective Continuous glucose monitor (CGM) use is associated with improved glucose control. We describe the effect of continued and interrupted CGM use on hemoglobin A1c (HbA1c) in youth with public insurance. Methods We reviewed 956 visits from 264 youth with type 1 diabetes (T1D) and public insurance. Demographic data, HbA1c and two‐week CGM data were collected. Youth were classified as never user, consistent user, insurance discontinuer, and self‐discontinuer. Visits were categorized as never‐user visit, visit before CGM start, visit after CGM start, visit with continued CGM use, visit with initial loss of CGM, visit with continued loss of CGM, and visit where CGM is regained after loss. Multivariate regression adjusting for age, sex, race, diabetes duration, initial HbA1c, and body mass index were used to calculate adjusted mean and delta HbA1c. Results Adjusted mean HbA1c was lowest for the consistent user group (HbA1c 8.6%;[95%CI 7.9,9.3]). Delta HbA1c (calculated from visit before CGM start) was lower for visit after CGM start (−0.39%;[95%CI −0.78,−0.02]) and visit with continued CGM use (−0.29%;[95%CI −0.61,0.02]), whereas it was higher for visit with initial loss of CGM (0.40%;[95%CI −0.06,0.86]), visit with continued loss of CGM (0.46%;[95%CI 0.06,0.85]), and visit where CGM is regained after loss (0.57%;[95%CI 0.06,1.10]). Conclusions Youth with public insurance using CGM have improved HbA1c, but only when CGM use is uninterrupted. Interruptions in use, primarily due to gaps in insurance coverage of CGM, were associated with increased HbA1c. These data support both initial and ongoing coverage of CGM for youth with T1D and public insurance.