Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 4 appraisals
Journal of medical Internet research
A Digital Diabetes Self-Management Education and Support Program Integrated With Continuous Glucose Monitoring for Type 2 Diabetes: Randomized Controlled Trial
BACKGROUND: Previous research has demonstrated that the use of continuous glucose monitoring (CGM) can improve glycemic control in people with type 2 diabetes when used regularly alongside a digital diabetes self-management education and support (DSMES) program. However, to date, there is limited evidence showing the benefits of a digitally delivered DSMES program combined with real-time CGM for adults with type 2 diabetes. OBJECTIVE: The objective of this study is to evaluate the impact of a DSMES program coupled with CGM on hemoglobin A1c (HbA1c) and CGM-derived glycemic measures compared to usual care for adults with type 2 diabetes over 6 months. METHODS: Participants with type 2 diabetes and HbA1c of 8% or higher (64 mmol/mol) who were not using mealtime bolus insulin (aged 26-83 y; mean HbA1c 9.6%, SD 1.4% [mean 81.2 mmol/mol, SD 15.8 mmol/mol]) were randomly assigned to a digital DSMES+CGM integrated solution (n=51) or usual care (n=49) for 6 months. The primary outcome was HbA1c. The secondary outcomes were CGM-derived glycemic measures, including glucose management indicator, percent time in range 70 to 180 mg/dL, percent time above range (>180 mg/dL), percent time below range (<70 mg/dL), and mean glucose. Linear mixed effects models were used for intention-to-treat analyses. RESULTS: HbA1c was lower among the intervention group versus the usual care group at 3 months (difference=-0.7%, 95% CI -1.4% to -0.1% or difference=-8.1 mmol/mol, 95% CI -15.5 to -0.7 mmol/mol; P=.03) and at 6 months (difference=-0.6%, 95% CI -1.4% to 0.2% or difference=-6.9 mmol/mol, 95% CI -15.7 to 1.9 mmol/mol; P=.12) but only reached statistical significance at 3 months. CGM-derived glycemic measures, including glucose management indicator (difference=-0.9%, 95% CI -1.7% to -0.1%; P=.03), time in range (difference=14.6%, 95% CI 1.0% to 28.2%; P=.04), time above range (difference=-14.9%, 95% CI -29.0% to -0.9%; P=.04), and mean glucose (difference=-36.4 mg/dL, 95% CI -70.0 to -2.9 mg/dL; P=.03), also significantly improved for the intervention group versus the usual care group at 6 months. CONCLUSIONS: The combination of digital DSMES+CGM is effective for supporting adults with type 2 diabetes in managing their condition and has the potential to reduce the risk of long-term health complications.
16 May 2026
Read appraisal →BMC endocrine disorders
Effects of digital and remote exercise interventions on HbA1c in type 2 diabetes: a systematic review and network meta-analysis
BACKGROUND: To compare the effects of different digitally and remotely deliveredexercise interventions on glycated hemoglobin (HbA1c) in adults with type 2diabetes mellitus (T2DM) using a network meta-analysis (NMA), and to clarifythe relative effectiveness of distinct delivery models. METHODS: A systematic review and network meta-analysis of randomized controlledtrials was conducted following PRISMA-NMA guidelines and prospectivelyregistered in PROSPERO (CRD420261288210). Major databases were searched frominception to November 11, 2025. Exercise-centered digital and remoteinterventions were categorized as digital exercise interventions (DEX),structured exercise prescription (SEP), multi-behavior lifestyle interventions(MBLI), and tele-exercise/tele-rehabilitation (TEX). The primary outcome waschange in HbA1c. RESULTS: Fifty-four RCTs were included. Compared with control, TEX demonstratedthe greatest reduction in HbA1c (MD -0.51%, 95% CrI -0.88 to -0.14), followedby MBLI (MD -0.32%, 95% CrI -0.51 to -0.13). SEP showed a non-significanttrend, and DEX did not significantly reduce HbA1c. SUCRA rankings favored TEX(0.87), followed by MBLI (0.66), SEP (0.62), and DEX (0.24). Subgroup analysessuggested that HbA1c reductions with TEX and MBLI were more evident among olderadults (≥60 years) and those with longer diabetes duration（>10 years）;however, network inconsistency was detected in these subgroups, and findingsshould be interpreted cautiously. CONCLUSIONS: Digitally and remotelydelivered exercise interventions differ in their effectiveness for HbA1ccontrol in T2DM. Interventions incorporating ongoing professional supervisionare associated with the most consistent glycemic benefits, whereas largelyautomated approaches show limited effects, highlighting the importance ofdelivery structure and supervision intensity.
15 May 2026
Read appraisal →Journal of medical systems
VR-Based Physical Activity and Self-Management Interventions for Glycemic Control and Behavioral Outcomes in Type 2 Diabetes: A Systematic Review and Meta-Analysis
A growing body of original research has recently investigated virtual reality (VR)-based interventions for physical activity and self-management, yet yielded inconsistent results. This systematic review and meta-analysis aims to evaluate the effectiveness of VR-based physical activity and self-management interventions in improving glycemic control and modifying health-related behaviors among patients with type 2 diabetes mellitus (T2DM). A total of 10 studies involving 1,005 adults with T2DM were included, comprising 5 randomized controlled trials (RCTs), 1 non-randomized controlled trial (nRCT), and 4 self-controlled before-after studies. Of these, participants in the intervention groups received VR-based interventions, including immersive or interactive VR programs for diabetes self-management education or physical activity promotion, with most intervention durations ranging from 8 to 24 weeks. Control groups received traditional approaches, including routine care, in-person diabetes self-management programs, and content-equivalent 2D websites. The pre-post intervention analysis revealed that glycated hemoglobin (HbA1c) levels decreased significantly post-intervention (mean difference (MD) = -0.50, 95% CI: -0.92 to -0.08, p = 0.02). While VR-based physical activity and self-management interventions did not demonstrate superior efficacy to traditional intervention methods in glycemic control or behavioral outcomes, their unique advantages - including enhanced adherence, greater accessibility, and reduced spatiotemporal constraints - position them as a viable alternative for diabetes management. Nevertheless, the field requires more rigorously designed RCTs to establish efficacy and a systematic exploration of VR implementation protocols to maximize therapeutic benefits.
14 May 2026
Read appraisal →JAMA
An AI-Powered Lifestyle Intervention vs Human Coaching in the Diabetes Prevention Program: A Randomized Clinical Trial
IMPORTANCE: Prediabetes is common, yet evidence-based lifestyle interventions are underutilized. OBJECTIVE: To determine whether referral to an exclusively artificial intelligence (AI)-led lifestyle intervention based on the Diabetes Prevention Program (DPP) is noninferior to referral to a human-led DPP in achieving recommended thresholds for weight loss, hemoglobin A1c (HbA1c) reduction, and weekly physical activity among adults with prediabetes and overweight or obesity. DESIGN, SETTING, AND PARTICIPANTS: This phase 3, parallel-group, pragmatic, noninferiority randomized clinical trial was conducted from October 11, 2021, to December 16, 2024 (last follow-up) at 2 US clinical sites in Baltimore, Maryland, and Reading, Pennsylvania. Adults 18 years or older with prediabetes and overweight or obesity were enrolled. INTERVENTIONS: Participants were randomized in a 1:1 ratio to receive either a referral to an AI-powered DPP lifestyle intervention delivered via a mobile app and Bluetooth-enabled digital scale or a referral to a human coach-led DPP lifestyle intervention delivered remotely. Both interventions were delivered independently of the study team over a 12-month period. MAIN OUTCOMES AND MEASURES: The primary outcome was a composite of maintaining an HbA1c less than 6.5% throughout the study and achievement of at least 5% weight loss, at least 4% weight loss plus at least 150 minutes of weekly physical activity (assessed with actigraphy), or an absolute reduction in HbA1c of at least 0.2 percentage points at 12 months. Noninferiority of referral to the AI-led DPP compared with referral to the human-led DPP was prespecified to be determined if the 1-sided 95% CI lower boundary of the risk difference did not cross -15%. RESULTS: A total of 368 participants were included (median [IQR] age, 58 [50-65] years; 71% were female, 27% were Black, 6% were Hispanic, and 61% were White; median [IQR] BMI, 32.3 [28.5-37.1]). After referral, 171 of 183 participants (93.4%) initiated the AI-led DPP and 153 of 185 (82.7%) initiated the human-led DPP. The primary outcome was achieved by 58 of 183 participants (31.7%) in the AI-led DPP group and 59 of 185 (31.9%) in the human-led DPP group (risk difference, -0.2% [1-sided 95% CI, -8.2%]), meeting the criterion for noninferiority. Findings were consistent across individual components of the composite end point and in sensitivity analyses. CONCLUSIONS AND RELEVANCE: Among adults with prediabetes and overweight or obesity, referral to a fully automated AI-led DPP was noninferior to referral to a human-led DPP in achieving a composite outcome based on weight reduction, physical activity, and HbA1c. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05056376.
1 Dec 2025
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