BACKGROUND:Micro-randomization is a common method used to design and tailor AI-driven digital health interventions. However, applying it in real-world clinical settings can be challenging particularly when there are operational or resource constraints. We propose a novel design that integrates micro-randomization with treatment allocation policies to address such constraints, inspired by a pediatric type 1 diabetes (T1D) program. METHODS:We evaluated the design's properties through an extensive simulation study and developed a simulation-based power calculator, MRThreshold, to support such trial designs. RESULTS:Operational constraints that led to imbalance in treatment assignment affected efficiency. However, increasing resources had less impact relative to increases in study length (i.e., opportunities for micro-randomization). We observed a > 50% increase in power when lengthening a 16-week study to a 40-week study. Using our power calculator, we demonstrated that a 40-week study with 100 patients provides 84.0% power to detect a 2% change in time spent in glucose control, providing design considerations for our study. CONCLUSIONS:Careful consideration of study length, sample size, and operational capacity is essential for thoughtful design. Our novel design and tool balance micro-randomization and treatment allocation under operational constraints.

Objective To assess, in youth with type 1 diabetes (T1D), whether the initiation of early continuous glucose monitoring (CGM) with programmatic support to address sociodemographic barriers is associated with reduced disparities and improved glycemia. Study design CGM was initiated <1 month postdiagnosis with remote monitoring and <7% glycosylated hemoglobin A1c (HbA1c) target in youth with new-onset T1D in the Teamwork, Targets, Technology, and Tight Glycemia program. We evaluated HbA1c stratified by race and ethnicity, insurance, deprivation, and language across 3 cohorts: historical (June 2014 to December 2016), pilot (July 2018 to June 2020), and study 1 (June 2020 to March 2022). Results At 12 months in study 1, HbA1c was lowest among non-Hispanic White (6.5%; 95% CI 6.2%-6.9%), low deprivation (6.5%; 95% CI 6.2%-6.9%), private insurance (6.6%; 95% CI 6.3%-7%), and English preference (6.7%; 95% CI 6.4%-7%). HbA1c disparities were attenuated in study 1: ethnicity slopes changed from historical (0.09; 95% CI-0.02 to 0.20) to pilot (0.14; 95% CI-0.04 to 0.31) to study 1 (0.08; 95% CI-0.07 to 0.23). Insurance slopes improved from historical (0.20; 95% CI 0.09-0.31) to pilot (0.12; 95% CI-0.06to 0.29) to study 1 (0.01; 95%CI-0.14 to 0.16). Deprivation (41.3%) and race and ethnicity (32.2%) contributed most to HbA1c variability. Conclusions Study 1 was associated with improved glycemic outcomes and attenuation of some disparities, particularly by insurance and ethnicity, supporting the Teamwork, Targets, Technology, and Tight Glycemia program as an effective equity-oriented care model. Deprivation emerged as a key model-derived contributor to variability in HbA1c and may represent an important target to reduce disparities in pediatric T1D glycemia.

Objectives:To compare antispike IgG levels over a period of 182 days of follow-up in healthy adults who received full or fractional booster doses of BNT162b2 or AZD1222 after completing a primary series of Sinovac, BNT162b2 or AZD1222. Design:Double-blind, parallel-arm, phase IV randomised trial. Setting:The study was conducted in Campo Grande, Brazil, and participants were recruited in neighbourhoods with the lowest booster vaccine coverage. Follow-up visits were home based. Participants:1451 (18-60 years) healthy adults who had received a full primary series of Sinovac (n=549), BNT162b2 (n=451) or AZD1222 (n=451) were included. Interventions:Participants were randomised to receive booster doses of either full or fractional doses of BNT162b2, AZD1222 or a full dose of Sinovac in the Sinovac-primed group. Antispike IgG antibody levels were measured at 0, 28, 84 and 182 days post-booster. Main outcome measures:Antispike IgG antibody levels were measured through blood samples at baseline and follow-up visits that were conducted 28, 84 and 182 days post-booster vaccination. Results:Throughout the 182-day follow-up period, full doses of BNT162b2 generated the highest antibody titres compared with fractional doses and other vaccines in all primary groups. Full-dose AZD1222 compared with its fractional dose showed a substantial difference only at day 28. BNT162b2 fractional doses produced higher antibodies than AZD1222 full doses. Sinovac-primed participants had the lowest baseline antibody titres, with Sinovac boosters continuing to show low titres, compared with BNT162b2 or AZD1222 full or fractional doses. Conclusions:Full doses of BNT162b2 consistently elicited higher antibody titres than fractional doses, AZD1222 and Sinovac at all time points. AZD1222 and Sinovac full doses produced lower titres than BNT162b2 fractional doses. Recommendations for using fractional doses of BNT162b2 as an alternative to full doses should be made cautiously, and further studies are needed to determine clinical protection levels. Trial registration number:NCT05343871.

Background:Long COVID is a heterogeneous post-infectious condition. Although patient-reported outcome (PRO) measures for diagnosis or therapeutic monitoring have been adapted from related complex chronic illnesses, no PRO has been validated specifically in Long COVID. The STOP-PASC randomized, placebo-controlled trial of nirmatrelvir/ritonavir (NMV/r) in adults with Long COVID showed no overall treatment effect. This exploratory analysis aimed to identify distinct symptom trajectories and clinical characteristics associated with improvement or worsening over time. Methods:We performed latent class trajectory modeling (LCTM) on PRO measures-including the Patient Global Impression of Severity (PGIS), Patient Global Impression of Change (PGIC), PROMIS domains, and core symptoms-among 155 randomized participants. Participants were followed for 15 weeks with serial symptom assessments. Trajectory groups were identified using Bayesian Information Criteria and characterized using descriptive statistics and absolute standardized differences. Results:LCTM revealed heterogeneity in symptom trajectories. Two groups emerged for PGIS (improving n = 17, persistent/severe n = 136) and PGIC (improving n = 130; worsening n = 22). PROMIS-Physical Function modeling identified four groups (improving, normal/mild, moderate, and severe), fatigue core symptom modeling identified three (improving; moderate; severe). Worsening groups had higher proportions of NMV/r-treated participants and greater prevalence of cardiovascular symptoms and low-dose naltrexone use. Improving groups had shorter time since infection and higher baseline physical function. No subgroup showed a clear benefit from NMV/r. Conclusions:Distinct PRO trajectories reflect the clinical heterogeneity of Long COVID. NMV/r showed no clear benefit across subgroups. These findings emphasize the need for validated, Long COVID-specific PRO instruments and targeted therapeutic trials tailored to Long COVID subtypes.

Background and Aims:The progress of artificial intelligence (AI) in endoscopy is at a crossroads. The positive results of randomized controlled trials of computer-aided detection (CADe) have not been replicated in multiple pragmatic CADe trials, including ours. This gap between efficacy and effectiveness remains to be understood. We surveyed and interviewed our trial's colonoscopists to gain insight into human-AI interactions. Methods:We used a sequential, mixed-methodology design. After the trial, we administered Survey 1, focusing on attitudes and beliefs before and after trying CADe. The trial's null results were disclosed, and we then administered Survey 2 and conducted open-ended interviews, focusing on reactions to the null results. Responses were analyzed overall and by baseline adenoma detection rate (ADR) tertile. We identified key themes using thematic analysis and qualitative software. Results:Nearly all colonoscopists responded (22 and 21 of 24 [92% and 88%] for Surveys 1 and 2, respectively). Most (96%) regarded endoscopic ability as critical to their professional identity. Large majorities conveyed trust in and enthusiasm for AI before and after trying CADe (82%-87%) and desired to have CADe available (72%). Nearly two-thirds (62%) were surprised by the null results. There were few differences by ADR. No unifying explanation for the null results emerged from surveys or individual interviews. Colonoscopists expressed a range of expectations for AI in endoscopy. Conclusions:Lack of enthusiasm or mistrust of AI/CADe do not explain our pragmatic CADe trial's null results. AI may need to target dimensions beyond optical recognition to realize its promise in endoscopy.

AimsPsychosocial impacts of early continuous glucose monitoring (CGM) initiation in youth soon after type 1 diabetes diagnosis are underexplored. We report parent/guardian and youth patient-reported outcomes (PROs) that measure psychosocial states for families in 4T Study 1.Materials and MethodsOf the 133 families in the 4T Study 1, 132 parent/guardian and 66 youth (>= 11 years) were eligible to complete PROs. PROs evaluated included diabetes distress, global health, diabetes technology attitudes and CGM benefits/burden scales. Temporal trends of PROs were assessed via generalised linear mixed effects regression. Sociodemographic and clinical characteristics associated with PROs were evaluated. Psychosocial associations were evaluated by regressing parental distress on youth distress.ResultsPRO completion rates were 85.6% and varied between parent/guardian and youth. Throughout the study, parent/guardian and youth distress remained low and youth had increased technology acceptance (p = 0.046). Each additional month of CGM use was associated with a 14% decrease in the odds of experiencing diabetes distress (aOR = 0.86, 95% CI [0.76, 0.99], p = 0.029). Additionally, higher time-in-range was associated with decreased diabetes distress (p = 0.048). Age, diabetic ketoacidosis at diagnosis, gender, ethnicity, insurance status and language spoken were not associated with PROs.ConclusionsInitiation of CGM shortly after type 1 diabetes diagnosis does not have unintended negative psychological consequences. Longer duration of CGM use was associated with decreased youth distress and technology acceptance increased throughout the study.

Background: Youth with type 1 diabetes (T1D) and public insurance have lower diabetes technology use. This pilot study assessed the feasibility of a program to support continuous glucose monitor (CGM) use with remote patient monitoring (RPM) to improve glycemia for youth with established T1D and public insurance. Methods: From August 2020 to June 2023, we provided CGM with RPM support via patient portal messaging for youth with established T1D on public insurance with challenges obtaining consistent CGM supplies. We prospectively collected hemoglobin A1c (HbA1c), standard CGM metrics, and diabetes technology use over 12 months. Results: The cohort included 91 youths with median age at enrollment 14.7 years, duration of diabetes 4.4 years, 33% non-English speakers, and 44% Hispanic. Continuous glucose monitor data were consistently available (≥70%) in 23% of the participants. For the 64% of participants with paired HbA1c values at enrollment and study end, the median HbA1c decreased from 9.8% to 9.0% ( P < .001). Insulin pump users increased from 31 to 48 and automated insulin delivery users increased from 11 to 38. Conclusions: We established a program to support CGM use in youth with T1D and barriers to consistent CGM supplies, offering lessons for other clinics to address disparities with team-based, algorithm-enabled, remote T1D care. This real-world pilot and feasibility study noted challenges with low levels of protocol adherence and obtaining complete data in this cohort. Future iterations of the program should explore RPM communication methods that better align with this population’s preferences to increase participant engagement.

Stanford University, USA; University of California San Diego, USA.

The 4T Study 1 is a clinical pragmatic research trial that starts continuous glucose monitoring (CGM) within 30 days of T1D diagnosis and monitors PROs. We report the longitudinal relationship of PROs between newly diagnosed youth and parents/guardians (PG). PROs surveys were administered to youth and PG at baseline, 3, and 6 months. PG PROs included the 20-item parent Diabetes Distress Scale (DDS-P) and youth PROs were the 2-item Diabetes Distress Scale (DDS-2) and the 7-item PROMIS Pediatric Global Health Scale (PGH-7). Pearson correlations evaluated the relationship between scores on the PG and youth PROs. Youth (n=60 who were aged ≥11 years) with new onset T1D and their PG (n=125) were eligible to complete PROs, yet response rates varied (at baseline, 3-, 6-months: Youth 59%, 53%, and 50% vs PG 74%, 70%, and 66%). Correlations showed that PG diabetes distress was positively correlated with child diabetes distress at baseline (r=0.48, p=0.003) and at 3 months (r= 0.35, p=0.058). However, by 6 months, this association decreased in strength and significance (r=0.16, p=0.42). Youth global health was inversely correlated with PG diabetes distress at baseline (r=-0.36, p=0.029) and 3 months (r=-0.53, p=0.002) and this correlation was not significant at 6 months (r =-0.049, p=0.81). These data suggest that the relationship between PG diabetes distress and youth psychosocial states are dynamic. PG and youth psychosocial states are strongly associated after diagnosis and decrease over time. Utilization of CGM, age, T1D duration, response rate, and changes in the PG-youth relationship (such as decreased adult involvement or increased independence of youth) may contribute to our findings. Further investigation of longitudinal relationships between PG and youth PROs may provide additional insight into PG and youth psychosocial states and diabetes outcomes and indicate optimal timing for assessment and treatment referral. Disclosure S.A.Alamarie: None. F.K.Bishop: None. D.P.Zaharieva: Advisory Panel; Dexcom, Inc., Research Support; Hemsley Charitable Trust, International Society for Pediatric and Adolescent Diabetes, Insulet Corporation, Speaker's Bureau; American Diabetes Association, Ascensia Diabetes Care, Medtronic. P.Prahalad: None. M.Desai: None. D.M.Maahs: Advisory Panel; Medtronic, LifeScan Diabetes Institute, MannKind Corporation, Consultant; Abbott, Research Support; Dexcom, Inc. K.K.Hood: Consultant; Cecelia Health. A.Addala: None. E.Pang: None. A.L.Cortes-navarro: None. N.Arrizon-ruiz: None. I.Balistreri: None. A.Loyola: None. A.Schneider-utaka: None. V.Ritter: None. B.Shaw: None. Funding National Institutes of Health (R18DK122422)

Psychosocial impacts of early CGM initiation in youth soon after T1D diagnosis are underexplored. We report parent/guardian (PG) and youth trends in Patient Reported Outcomes (PROs) for families in the 4T Study 1. Of the 133 participants in the 4T Study 1, 125 PG and 60 youth (≥11 years) were eligible for PROs. PROs included Diabetes Distress Scale - Parent (mean DDS-P) for PG and for youth, Diabetes Distress Scale (DDS sum), PROMIS Pediatric Global Health (PGH sum), Diabetes Technology Attitudes (DTA sum), and CGM Benefits/Burden (BenCGM and BurCGM sum). Kruskal Wallis rank sum test evaluated temporal trends and sociodemographics were evaluated (Numerical: Wilcoxon rank; Categorical: Fisher's if n<5, Chi-squared if n≥5). PROs completion rates were higher for PG than youth at baseline (74% v 59%), 3 months (70% v 53%), and 6 months (66% v 50%). PG DDS-P remained low throughout the study (Table). Youth had favorable psychosocial trends (low DDS and high PGH), and perceived technology positively (high DTA and BenCGM with low BurCGM). Age, DKA at diagnosis, gender, ethnicity, insurance status, and language spoken were not associated with PROs scores in PG or youth. CGM initiation shortly after T1D diagnosis is not associated with poor or worsening PROs for PG and youth. These data suggest that early CGM initiation does not adversely impact psychosocial states for families and youth with T1D. Disclosure A.Addala: None. F.K.Bishop: None. D.P.Zaharieva: Advisory Panel; Dexcom, Inc., Research Support; Hemsley Charitable Trust, International Society for Pediatric and Adolescent Diabetes, Insulet Corporation, Speaker's Bureau; American Diabetes Association, Ascensia Diabetes Care, Medtronic. P.Prahalad: None. M.Desai: None. D.M.Maahs: Advisory Panel; Medtronic, LifeScan Diabetes Institute, MannKind Corporation, Consultant; Abbott, Research Support; Dexcom, Inc. K.K.Hood: Consultant; Cecelia Health. V.Ritter: None. B.Shaw: None. E.Pang: None. A.L.Cortes-navarro: None. I.Balistreri: None. A.Loyola: None. S.A.Alamarie: None. A.Schneider-utaka: None. Funding National Institutes of Health (K23DK13134201, R18DK122422)

Psychosocial states significantly impact T1D care and management for youth and their families. As part of a clinical pragmatic study, we report the number of elevated Patient Reported Outcomes (PROs) in newly diagnosed families and track their progress to psychological care. Parents/guardians (PG, n=125/133 4T Study 1 participants) and youth ≥11 years (n=60) were eligible to complete baseline, 3-, and 6-month PROs. PG completed Diabetes Distress Scale - Parent (DDS-P) and youth completed Diabetes Distress Scale (DDS-2) and PROMIS Pediatric Global Health Scale (PGH). Elevated PROs were based on published guidelines and were referred to the clinic's psychological services. Survey completeness was verified by staff to identify false flags. Staff reapproached the participant's psychologist for re-flagged PROs >3 months after the last visit. Over the three study time periods, a total of 99 PROs flags were evaluated (Table). At baseline, there were 32% flagged PROs, which decreased to 27% and 23% at 3 and 6 months, respectively. Elevated DDS-P was the most common reason for referral (75%). Early psychological intervention may explain the reduction in elevated PROs over the study period. With the implementation of systematic PROs in this new onset population, we observed it was common to have diabetes distress and families were receptive to psychological services. Disclosure A.Schneider-utaka: None. F.K.Bishop: None. D.P.Zaharieva: Advisory Panel; Dexcom, Inc., Research Support; Hemsley Charitable Trust, International Society for Pediatric and Adolescent Diabetes, Insulet Corporation, Speaker's Bureau; American Diabetes Association, Ascensia Diabetes Care, Medtronic. P.Prahalad: None. M.Desai: None. D.M.Maahs: Advisory Panel; Medtronic, LifeScan Diabetes Institute, MannKind Corporation, Consultant; Abbott, Research Support; Dexcom, Inc. K.K.Hood: Consultant; Cecelia Health. A.Addala: None. E.Pang: None. A.L.Cortes-navarro: None. I.Balistreri: None. A.Loyola: None. N.Arrizon-ruiz: None. S.A.Alamarie: None. V.Ritter: None. B.Shaw: None. Funding National Institutes of Health (R18DK122422)