Population-level management of Type 1 diabetes via continuous glucose monitoring and algorithm-enabled patient prioritization: Precision health meets population health

OBJECTIVE: To develop and scale algorithm-enabled patient prioritization to improve population-level management of type 1 diabetes (T1D) in a pediatric clinic with fixed resources, using telemedicine and remote monitoring of patients via continuous glucose monitor (CGM) data review. RESEARCH DESIGN AND METHODS: We adapted consensus glucose targets for T1D patients using CGM to identify interpretable clinical criteria to prioritize patients for weekly provider review. The criteria were constructed to manage the number of patients reviewed weekly and identify patients who most needed provider contact. We developed an interactive dashboard to display CGM data relevant for the patients prioritized for review. RESULTS: The introduction of the new criteria and interactive dashboard was associated with a 60% reduction in the mean time spent by diabetes team members who remotely and asynchronously reviewed patient data and contacted patients, from 3.2 ± 0.20 to 1.3 ± 0.24 min per patient per week. Given fixed resources for review, this corresponded to an estimated 147% increase in weekly clinic capacity. Patients who qualified for and received remote review (n = 58) have associated 8.8 percentage points (pp) (95% CI = 0.6–16.9 pp) greater time-in-range (70–180 mg/dl) glucoses compared to 25 control patients who did not qualify at 12 months after T1D onset. CONCLUSIONS: An algorithm-enabled prioritization of T1D patients with CGM for asynchronous remote review reduced provider time spent per patient and was associated with improved time-in-range

Type of unanticipated stimulus affects lower extremity kinematics and kinetics during sidestepping

Including an unanticipated stimulus has significant impacts on lower extremity biomechanics during dynamic movements. It is unknown how a live, human defender affects lower extremity biomechanics. The purpose of this study was thus to determine the effects of two types of unanticipated stimuli (visual stimulus; defensive opponent) on lower extremity kinematics and kinetics in males and females during 45° sidestepping trials. Eight males and eight females completed two unanticipated stimuli sidestepping conditions. Numeric visual analog scales for reaction difficulty and movement realism were collected and analysed using a 2 × 2 mixed-model ANOVA. Three-dimensional hip, knee, and ankle kinematics and kinetics were measured during the stance phase of the sidestep and analysed using statistical parametric mapping. Participants reported greater difficulty and less realistic movements with the visual stimulus. Unanticipated stimulus main effects were observed for knee abduction angle, and hip extension and adduction, and knee extension and adduction moments. Sex main effects were observed for hip flexion, hip abduction, and ankle dorsiflexion angles, as well as hip abduction, ankle plantarflexion and ankle eversion moments and vertical ground reaction forces. Participants responded differently to two unanticipated stimuli. Careful consideration should be used when determining the type of unanticipated stimulus used

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

<b>Role and Perspective of Certified Diabetes Care and Education Specialists in the Development of the 4T Program</b>

The Diabetes Control and Complications Trial (DCCT) clearly delineated the benefits of intensive diabetes management in preventing long-term complications in people with insulin-dependent diabetes (1). Despite the data from the DCCT, a majority of youth with type 1 diabetes do not meet glycemic targets. One aspect of the DCCT intervention was frequent insulin dose adjustments by a care team member. Although this was a landmark clinical trial, translation of its findings into clinical practice has been challenging because of barriers in implementing glucose data-sharing technology and clinical time constraints. There is also a shortage of diabetes care team members (2) to review glucose data and communicate insulin dosing advice and provide diabetes self-management education and support (DSMES). In particular, there is a nationwide shortage of certified diabetes care and education specialists (CDCESs) (2).</p