AI-Assisted Blood Glucose Management Study

NCT07160985 | Completed DMC

• 1 other identifier: 2025-06
• Study Type: interventional
• Target: 131
• Locations: 1 country
• Sites: 1

Brief Summary

AI-driven health management tools can leverage continuous glucose monitoring (CGM), physical activity, and dietary data to provide real-time, individualized feedback, improving self-management and adherence. The X Life model integrates AI algorithms with wearable devices to dynamically adjust dietary and exercise recommendations. Preliminary user studies suggest good usability and user experience, with potential to promote positive behavior change. This trial aims to preliminarily evaluate whether the X Life AI system can improve glucose tolerance (measured by oral glucose tolerance test \[OGTT\] incremental area under the curve \[iAUC\]) in adults with prediabetes, providing effect size and protocol design reference for a future confirmatory randomized controlled trial. The investigators designed this trial with the assistance of a digital twin-based clinical research system (termed X Town).

Conditions

Pre-diabetes

Outcome Measures

Primary Outcomes (1)

• Change in OGTT Glucose Incremental Area Under the Curve (iAUC)

  Difference between groups in the incremental area under the curve for plasma glucose concentration during a 2-hour oral glucose tolerance test (OGTT), calculated from measurements at 0, 60, and 120 minutes, adjusting for baseline values.

  Baseline and at the end of the 28-day intervention period.

Secondary Outcomes (8)

• Change in OGTT Plasma Glucose Levels

  Baseline and at the end of the 28-day intervention period.

• Change in Continuous Glucose Monitoring (CGM) Metrics

  Baseline (7-day run-in period) and during the 28-day intervention period.

• Change in OGTT Plasma Insulin Levels

  Baseline and at the end of the 28-day intervention period.

• Composite Body Composition Outcomes

  Baseline and at the end of the 28-day intervention period.

• Composite Metabolic Parameters

  Baseline and at the end of the 28-day intervention period.

Study Arms (2)

X Life Lifestyle Guidance

EXPERIMENTAL

Other: AI-based Lifestyle Management

Standard Care

ACTIVE COMPARATOR

Other: Lifestyle Management

Interventions

Lifestyle Management OTHER

Participants will receive guideline-based lifestyle counseling according to national prediabetes prevention guidelines, delivered via mobile terminal, without AI-generated recommendations.

Standard Care

AI-based Lifestyle Management OTHER

Participants will use the X Life system for 28 days, receiving real-time, personalized dietary and exercise recommendations triggered by glucose level and activity tracker data. Participants can interact with the system by uploading meal images, physical activity data, and wearable-derived metrics.

X Life Lifestyle Guidance

Eligibility Criteria

• Age: 18 Years - 70 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age 18-70 years
• Prediabetes (per ADA or WHO criteria)
• Stable lifestyle and body weight (±5%) for ≥3 months
• Owns and can operate a smartphone
• Able to understand and sign informed consent

You may not qualify if:

• Current glucose-lowering medication use
• Severe cardiovascular disease, liver/kidney dysfunction, or active malignancy
• Psychiatric or cognitive disorders affecting participation
• Planned major surgery or long-distance travel during the study
• Allergy/intolerance to CGM sensor materials

Sponsors & Collaborators

• Li Huating: lead

Study Sites (1)

Shanghai Sixth People's Hospital

Shanghai, China

Location

MeSH Terms

Conditions

Glucose Intolerance

Condition Hierarchy (Ancestors)

Hyperglycemia; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: August 21, 2025
• First Posted: September 8, 2025
• Study Start: September 7, 2025
• Primary Completion: November 23, 2025
• Study Completion: November 30, 2025
• Last Updated: February 12, 2026

Record last verified: 2026-02

Locations

CN (1)