Ignite Creation Date:
2025-12-24 @ 9:12 PM
Ignite Modification Date:
2025-12-28 @ 5:20 PM
Study NCT ID:
NCT07291804
Status:
COMPLETED
Last Update Posted:
2025-12-18
First Post:
2025-12-05
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Efficacy and Safety of an Intelligent Insulin-Dosing Decision Support System for Glycemic Control in Patients With Type 2 Diabetes: A Randomized Controlled Study
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003924', 'term': 'Diabetes Mellitus, Type 2'}, {'id': 'D007333', 'term': 'Insulin Resistance'}], 'ancestors': [{'id': 'D003920', 'term': 'Diabetes Mellitus'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}, {'id': 'D006946', 'term': 'Hyperinsulinism'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['PARTICIPANT']}, 'primaryPurpose': 'TREATMENT', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 140}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2025-03-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-12', 'completionDateStruct': {'date': '2025-12-01', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2025-12-05', 'studyFirstSubmitDate': '2025-12-05', 'studyFirstSubmitQcDate': '2025-12-05', 'lastUpdatePostDateStruct': {'date': '2025-12-18', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2025-12-18', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2025-12-01', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'HbA1c', 'timeFrame': 'Baseline, Week 12', 'description': 'Change in HbA1c from Baseline to Week 12, measured from fasting venous blood samples using High-Performance Liquid Chromatography (HPLC).'}], 'secondaryOutcomes': [{'measure': 'Fasting Plasma Glucose (FPG) (mmol/L)', 'timeFrame': 'Baseline, Week 12', 'description': 'Change in FPG from Baseline to Week 12. FPG was self-measured daily upon waking (after ≥8 hours of fasting) using glucometer, with data automatically transmitted.'}, {'measure': '2-hour Postprandial Plasma Glucose (2h PPG) (mmol/L)', 'timeFrame': 'Baseline, Week 12', 'description': 'Change in 2h PPG from Baseline to Week 12. 2h PPG was self-measured 2 hours after the start of a standardized meal using the same glucometer, with automatic data upload.'}, {'measure': 'Hypoglycemic Events', 'timeFrame': 'From Baseline to Week 12', 'description': 'Frequency of hypoglycemic episodes (defined as any self-measured plasma glucose value ≤3.9 mmol/L).'}, {'measure': 'Psychological Insulin Resistance', 'timeFrame': 'Baseline, Week 12', 'description': 'Measured using the My Opinion on Insulin (27 items, 5-point Likert).'}, {'measure': 'Empowerment Ability', 'timeFrame': 'Baseline, Week 12', 'description': 'Measured using the Diabetes Empowerment Scale-Short Form (DES-SF, 5 items, total score 0-100).'}, {'measure': 'Self-Management Behaviors', 'timeFrame': 'Baseline, Week 12', 'description': 'Measured using the Summary of Diabetes Self-Care Activities (SDSCA, 13 items) questionnaire, reporting days per week for each behavior (diet, exercise, blood glucose monitoring, foot care, medication, smoking).'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Insulin', 'Intelligent Decision Support System'], 'conditions': ['Diabetes Mellitus，Type 2']}, 'descriptionModule': {'briefSummary': 'The goal of this clinical trial is to learn if an intelligent insulin-dosing decision support system can improve glycemic control in adults with type 2 diabetes who are starting basal insulin therapy. The trial also aims to evaluate the safety of using this system for insulin dose adjustment.\n\nThe main questions it aims to answer are:\n\n* Does the intelligent decision support system improve fasting glucose, postprandial glucose, and HbA1c?\n* Does the system provide safe insulin titration without raising hypoglycemia risk and improve empowerment, self-management, and insulin-related attitudes?\n\nResearchers will compare the intelligent insulin-dosing decision support system with usual care to see if the system leads to more effective and safer insulin titration.\n\nParticipants will:\n\n* Upload blood glucose data using a smart glucometer connected to a mobile health platform\n* Receive basal insulin therapy with ongoing dose adjustments\n\nIntervention group: use the intelligent decision support system that provides algorithm-based insulin dose recommendations with remote monitoring and guidance Control group: receive standard diabetes education and routine outpatient insulin titration', 'detailedDescription': "This study evaluates an intelligent insulin dosing decision support system designed to support basal insulin titration in adults with type 2 diabetes. The system operates on an internet-of-things platform that synchronizes glucose data and insulin dose records from a smart glucometer and an insulin logging device to a cloud-based server. Patients and clinical staff access the system through a mobile interface, which enables real time data transmission, automated dose calculation, and remote supervision.\n\nThe system contains four major components. The first component is a comprehensive assessment module that collects demographic information, clinical characteristics, and a full panel of islet function indicators including fasting glucose, postprandial glucose, glycated hemoglobin, fasting insulin, and multiple C-peptide values. A validated hypoglycemia risk prediction model classifies each participant into low, intermediate, or high risk categories. Competency in insulin injection and dose verification is assessed using a standardized questionnaire.\n\nThe second component determines the initial basal insulin dose. This calculation follows guideline recommendations and incorporates the islet function results and hypoglycemia risk category to generate an individualized starting dose.\n\nThe third component evaluates insulin sensitivity and glucose response patterns. Continuous transmission of glucose values and insulin doses allows the system to estimate the participant's insulin sensitivity level and to update these estimates as additional data are obtained.\n\nThe fourth component produces dose adjustment recommendations. Titration is structured into three time-based phases with clearly defined monitoring frequencies and clinical review points. During the initial titration phase from day three to day fourteen, fasting glucose is measured daily and the system generates dose recommendations every three days using the mean of the most recent fasting glucose values. Nurses review glucose patterns and safety concerns on day four and at the end of the first week, while physicians perform dose verification on day four. During the stable titration phase from week three to week twelve, fasting glucose is measured every three days and the system generates weekly dose recommendations based on the most recent value. Nurses conduct follow up assessments and provide stepwise guidance at week one, week two, week four, week eight, and week twelve. Physicians review system-generated recommendations at the same time points. During the long term maintenance phase from week thirteen to week twenty four, fasting glucose is measured weekly and the system continues to produce weekly dose recommendations. Participants who demonstrate sufficient accuracy in dose verification by week twelve may be authorized to review system-generated dose units independently from week thirteen onward under remote supervision. Physicians complete a final evaluation at week twenty four.\n\nSafety supervision is integrated throughout the entire study. The system continuously evaluates glucose fluctuations and recalculates hypoglycemia risk at each dose adjustment. When a fasting glucose value falls below the predefined safety threshold or when a proposed adjustment exceeds the predetermined limit, a safety alert is automatically triggered. Nurses are required to conduct follow up within twenty four hours and document the event. Both self-reported and device-captured hypoglycemia events are recorded and reviewed across the study period.\n\nThe mobile platform provides automated reminders for glucose monitoring, displays dose recommendations, and delivers educational content related to insulin use. Patients may submit questions and receive guidance through text or image messages. The clinician interface summarizes glucose trends, allows review of system-generated dose recommendations at scheduled verification points, and supports real time management of safety alerts.\n\nThe intervention incorporates a structured empowerment-based management process that aligns with the titration timeline. The five components include identifying patient challenges during insulin initiation, addressing concerns and emotional responses, establishing short term and long term treatment goals, developing individualized action plans, and evaluating outcomes at specific time points. Nurses and physicians conduct these steps at the designated visits that coincide with the initial, stable, and maintenance titration phases. The process is designed to gradually strengthen the participant's ability to verify dose adjustments, prevent hypoglycemia, and maintain long term adherence to basal insulin therapy.\n\nOutcome measurements are collected at baseline and week twelve. These include glycemic indicators, hypoglycemia frequency, empowerment ability, self-management behaviors, and attitudes toward insulin therapy. Through this integrated system of algorithm-guided titration, continuous data monitoring, structured follow up, and staged empowerment education, this study aims to determine whether the intelligent dosing system can improve the precision and safety of basal insulin titration and enhance behavioral readiness for long term insulin self management."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria: Patients who\n\n1. were diagnosed with T2DM according to the Guideline for the Prevention and Treatment of Diabetes Mellitus in China (2024 edition);\n2. were prescribed basal insulin therapy for the first time;\n3. were aged 18 years or older;\n4. voluntarily participated in this study; and\n5. had access to mobile devices and the internet.\n\nExclusion Criteria: Individuals who:\n\n1. had severe diabetes-related complications (e.g., cardiac, hepatic, cerebral, or renal insufficiency);\n2. were unable to participate in regular follow-ups;\n3. had communication or cognitive barriers;\n4. had diagnosed psychiatric disorders; or\n5. discontinued basal insulin therapy for non-glycaemic reasons.'}, 'identificationModule': {'nctId': 'NCT07291804', 'briefTitle': 'Efficacy and Safety of an Intelligent Insulin-Dosing Decision Support System for Glycemic Control in Patients With Type 2 Diabetes: A Randomized Controlled Study', 'organization': {'class': 'OTHER', 'fullName': 'Third Affiliated Hospital, Sun Yat-Sen University'}, 'officialTitle': 'Efficacy and Safety of an Intelligent Insulin-Dosing Decision Support System for Glycemic Control in Patients With Type 2 Diabetes: A Randomized Controlled Study', 'orgStudyIdInfo': {'id': 'RG-2025-025-02'}, 'secondaryIdInfos': [{'id': '2025A1515012706', 'type': 'OTHER_GRANT', 'domain': 'Guangdong Basic and Applied Basic Research Foundation'}, {'id': 'YHJH202404', 'type': 'OTHER_GRANT', 'domain': '3rd Affiliated Hospital of Sun Yat-sen University, Clinical Research Program'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'NO_INTERVENTION', 'label': 'Control Group', 'description': 'The control group received standard usual care, which included standardized diabetes education on the first day and routine follow-up where physicians adjusted insulin doses based on FPG levels during scheduled outpatient visits at Weeks 4, 8, 12, and 24.'}, {'type': 'EXPERIMENTAL', 'label': 'Intervention Group', 'description': 'The intervention group received usual care plus a structured program based on empowerment theory and implemented via an intelligent mHealth platform. This platform provided personalized dose recommendations and supported real-time data transmission ; physicians reviewed and confirmed dose adjustments at Day 4, Weeks 1, 2, 4, 8, 12, and 24 , and from Week 13 onward, patients were gradually authorized to self-adjust insulin doses under remote supervision.', 'interventionNames': ['Device: Intelligent Insulin-Dosing Decision Support System']}], 'interventions': [{'name': 'Intelligent Insulin-Dosing Decision Support System', 'type': 'DEVICE', 'description': "This intelligent insulin dosing system for type 2 diabetes operates on an IoT platform. Its core function begins with a comprehensive assessment that integrates patient data and islet function indicators to stratify hypoglycemia risk, followed by generating an individualized initial insulin dose based on guidelines and the risk category. The system then continuously estimates the patient's dynamic insulin sensitivity using real-time streams of glucose and insulin data. Dose titration is executed in three structured phases: an initial phase (Day 3-14) with adjustments every 3 days based on daily glucose, a stable phase (Week 3-12) with weekly adjustments using tri-weekly data, and a long-term maintenance phase (Week 13-24) with weekly recommendations, where eligible patients can begin remote-supervised self-management.", 'armGroupLabels': ['Intervention Group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '510630', 'city': 'Guangzhou', 'state': 'Guangdong', 'country': 'China', 'facility': 'Third Affiliated Hospital of Sun Yat-sen University', 'geoPoint': {'lat': 23.11667, 'lon': 113.25}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'The data are currently being verified for quality and are not yet in a format suitable for sharing.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Third Affiliated Hospital, Sun Yat-Sen University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Chief Nurse', 'investigatorFullName': 'Xiling Hu', 'investigatorAffiliation': 'Third Affiliated Hospital, Sun Yat-Sen University'}}}}