Ignite Creation Date:
2025-12-25 @ 2:29 AM
Ignite Modification Date:
2026-01-08 @ 1:50 AM
Study NCT ID:
NCT06453434
Status:
NOT_YET_RECRUITING
Last Update Posted:
2024-06-11
First Post:
2024-05-30
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Diabetes Self-management With Continuous Glucose Monitoring
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003922', 'term': 'Diabetes Mellitus, Type 1'}], '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': 'D001327', 'term': 'Autoimmune Diseases'}, {'id': 'D007154', 'term': 'Immune System Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'OTHER'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 500}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2024-07-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-04', 'completionDateStruct': {'date': '2026-08', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-06-05', 'studyFirstSubmitDate': '2024-05-30', 'studyFirstSubmitQcDate': '2024-06-05', 'lastUpdatePostDateStruct': {'date': '2024-06-11', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-06-11', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-08', 'type': 'ESTIMATED'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Frequency of daily CGM readings', 'timeFrame': '14 days', 'description': 'How many times the participants open the LibreView app to assess their CGM data during the day'}, {'measure': 'Diurnal variation of daily CGM readings', 'timeFrame': '14 days', 'description': 'Numbers in the morning (06.00-11.59), afternoon (12.00-17.59), in the evening (18.00-23.59) and in the night (00.00-05.59)'}, {'measure': 'Active sensor', 'timeFrame': '14 days', 'description': 'Percentage of sensor data obtained'}, {'measure': 'Frequency of daily between-meal insulin corrections', 'timeFrame': '14 days', 'description': 'How many times the participants take between-meal insulin corrections daily'}, {'measure': 'Frequency of hypoglycaemic events preceded by correction of hyperglycaemia with insulin,', 'timeFrame': '14 days', 'description': 'For each hypoglycaemic event (defined as a glucose level ≥ 10 mmol/L (180 mg/dL)) a cause of the event will be interpreted based on 4-hours data and classified as either preceded by 1) premeal-insulin, 2) insulin correction of hyperglycemia or 3) physical activity'}, {'measure': 'Frequency of hyperglycaemic events preceded by correction of hypoglycaemia with carbohydrates', 'timeFrame': '14 days', 'description': 'For each hyperglycaemic event (defined as glucose level ≥ 10 mmol/L (180 mg/dL) ≥ 15 consecutive minutes) a cause of the event will be interpreted based on 4-hours data and classified as either preceded by 1) carbohydrate intake without premeal insulin, 2) carbohydrate intake with premeal insulin, or 3) correction of hypoglycaemia with carbohydrate'}, {'measure': 'High glucose alarm threshold', 'timeFrame': 'At baseline', 'description': 'Mean/median alarm threshold level at baseline'}, {'measure': 'Low glucose alarm threshold', 'timeFrame': 'At baseline', 'description': 'Mean/median alarm threshold level at baseline'}, {'measure': 'Frequency of high glucose alarms', 'timeFrame': '14 days', 'description': 'Number of high glucose alarms during the study'}, {'measure': 'Frequency of low glucose alarms', 'timeFrame': '14 days', 'description': 'Number of low glucose alarms during the study'}, {'measure': 'Low alarms enabled', 'timeFrame': '14 days', 'description': 'Percentage of time low alarms are activated'}, {'measure': 'High alarms enabled', 'timeFrame': '14 days', 'description': 'Percentage of time high alarms are activated'}, {'measure': 'Diurnal variation of high alarms', 'timeFrame': '14 days', 'description': 'Numbers in the morning (06.00-11.59), afternoon (12.00-17.59), evening (18.00-23.59) and night (00.00-05.59)'}, {'measure': 'Diurnal variation of low alarms', 'timeFrame': '14 days', 'description': 'Numbers in the morning (06.00-11.59), afternoon (12.00-17.59), evening (18.00-23.59) and night (00.00-05.59)'}, {'measure': 'Smart pen engagement', 'timeFrame': '14 days', 'description': 'Number of days with data uploads during the study period'}, {'measure': 'Total daily dose (TDD) of insulin', 'timeFrame': '14 days', 'description': 'Mean of the study period. Recorded by smartpens.'}, {'measure': 'Total daily dose (TDD) of basal insulin', 'timeFrame': '14 days', 'description': 'Mean of the study period. Recorded by smartpens.'}, {'measure': 'Total daily dose (TDD) of insulin delivered as premeal boluses', 'timeFrame': '14 days', 'description': 'Mean of the study period. Recorded by smartpens.'}, {'measure': 'Total daily dose (TDD) of insulin delivered as correctional boluses', 'timeFrame': '14 days', 'description': 'Mean of the study period. Recorded by smartpens.'}, {'measure': 'Percentage of TDD of insulin delivered as correctional boluses out of TDD of insulin', 'timeFrame': '14 days', 'description': 'Percentage'}, {'measure': 'Missing basal insulin dose', 'timeFrame': '14 days', 'description': '≥ 40 hours between basal insulin injections'}, {'measure': 'Missing meal boluses', 'timeFrame': '14 days', 'description': 'No bolus injection within 15 minutes before and 60 minutes after the start of a meal. Meals identified using a food diary/CGM signal by using the GRID algorithm.'}, {'measure': 'Diurnal variation of correctional boluses', 'timeFrame': '14 days', 'description': 'Numbers in the morning (06.00-11.59), afternoon (12.00-17.59), in the evening (18.00-23.59) and in the night (00.00-05.59), respectively'}, {'measure': 'Step count per day', 'timeFrame': '14 days', 'description': 'From activity sensor'}, {'measure': 'Moderate and vigorous physical activity (MVPA)', 'timeFrame': '14 days', 'description': 'From activity sensor. Time spent on moderate and vigorous physical activity (MVPA)'}, {'measure': 'Low-intensity physical activity (LPA)', 'timeFrame': '14 days', 'description': 'From activity sensor. Time spent on low-intensity physical activity (LPA) time'}, {'measure': 'Total physical activity (TPA) level', 'timeFrame': '14 days', 'description': 'From activity sensor. TPA measured in counts per minute'}, {'measure': 'Sleep', 'timeFrame': '14 days', 'description': 'From activity sensor. Sleep hours per night'}, {'measure': 'Food intake', 'timeFrame': '14 days', 'description': 'Database which contains food intake data (amount of food in carbohydrates) retrieved from the diary app (LibreLink).'}, {'measure': 'Food intake', 'timeFrame': '14 days', 'description': 'Database which contains food intake data (timing of food intake) retrieved from the diary app (LibreLink).'}, {'measure': 'Clarke score', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding awareness of hypoglycemia.'}, {'measure': 'Gold score', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding awareness of hypoglycemia.'}, {'measure': 'Hilleroed method', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding awareness of hypoglycemia.'}, {'measure': 'Glucose Monitoring Satisfaction Survey (GMSS)', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding CGM satisfaction'}, {'measure': 'Perceived Competence in Diabetes (PCD)', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding diabetes self-management'}, {'measure': 'Diabetes Treatment Satisfaction Questionnaire status (DTSQs)', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding diabetes treatment satisfaction'}, {'measure': 'Hypoglycaemia Fear Survey-II Short Form (HFS-SF)', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding fear of hypoglycemia'}, {'measure': 'The Danish Health Literacy Questionnaire (HLQ)', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding health literacy'}, {'measure': 'Based on Saltin-Grimby Physical Activity Level Scale (SGPALS)', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding physical activity'}, {'measure': 'Well-Being Index (WHO-5)', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding psychological well-being'}, {'measure': 'Pittsburgh Sleep Quality Index (PSQI)', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding sleep quality'}, {'measure': 'Type D scale (DS-14)', 'timeFrame': 'At baseline', 'description': 'Patient-reported outcome regarding type D personality trait'}, {'measure': 'VAS-A', 'timeFrame': 'Each morning and each evening during the study period', 'description': 'Patient-reported outcome regarding anxiety'}, {'measure': 'EQ-VAS', 'timeFrame': 'Each morning during the study period', 'description': 'Patient-reported outcome regarding overall health'}], 'primaryOutcomes': [{'measure': 'Diabetes Distress', 'timeFrame': 'At baseline and after 14 days.', 'description': 'Type 1 Diabetes Distress Scale (T1-DDS-28)) Score. Likert scale. Score from 1 to 5. Higher scores indicate higher grade of diabetes distress.'}], 'secondaryOutcomes': [{'measure': 'Time in range (TIR)', 'timeFrame': '14 days', 'description': 'Time in range defined as the percentage of time the sensor glucose is 3.9-10.0 mmol/L (70-180 mg/dL)'}, {'measure': 'Time in tight range (TIR)', 'timeFrame': '14 days', 'description': 'The percentage of time the sensor glucose is 3.9-7.8 mmol/L (70-140 mg/dL)'}, {'measure': 'Time below range level 1 (TBR1)', 'timeFrame': '14 days', 'description': 'The percentage of time the sensor glucose is 3.0-3.9 mmol/L (54-70 mg/dL)'}, {'measure': 'Time below range level 2 (TBR2)', 'timeFrame': '14 days', 'description': 'The percentage of time the sensor glucose is \\<3.0 mmol/L (\\<54 mg/dL)'}, {'measure': 'TBR1 night', 'timeFrame': '14 days', 'description': 'TBR 3.0-3.9 from 0000h to 0559h, level 1 night'}, {'measure': 'TBR1 day', 'timeFrame': '14 days', 'description': 'TBR 3.0-3.9 from 0600h to 2359h, level 1 day'}, {'measure': 'TBR2 night', 'timeFrame': '14 days', 'description': 'TBR \\<3.0 from 0000h to 0559h, level 2 night'}, {'measure': 'TBR2 day', 'timeFrame': '14 days', 'description': 'TBR \\<3.0 from 0600h to 2359h, level 2 day'}, {'measure': 'Time above range level 1 (TAR1)', 'timeFrame': '14 days', 'description': 'The percentage of time the sensor glucose is 10.1-13.9 mmol/L (181-250 mg/dL)'}, {'measure': 'Time above range level 2 (TAR2)', 'timeFrame': '14 days', 'description': 'The percentage of time the sensor glucose is 13.9 mmol/L (\\>250 mg/dL)'}, {'measure': 'TAR1 night', 'timeFrame': '14 days', 'description': 'TAR1 10.1-13.9 from 0000h to 0559h, level 1 night'}, {'measure': 'TAR1 day', 'timeFrame': '14 days', 'description': 'TAR1 10.1-13.9 from 0600h to 2359h, level 1 day'}, {'measure': 'TAR2 night', 'timeFrame': '14 days', 'description': 'TAR2 \\>13.9 from 0000h to 0559h, level 1 night'}, {'measure': 'TAR2 day', 'timeFrame': '14 days', 'description': 'TAR2 \\>13.9 from 0600h to 2359h, level 1 day'}, {'measure': 'Coefficient of variation (CV)', 'timeFrame': '14 days', 'description': 'Measure of glucose variability. Calculated as 100 x (SD divided by mean glucose)'}, {'measure': 'Mean sensor glucose', 'timeFrame': '14 days', 'description': 'Mean sensor glucose (mmol/L and mg/dL)'}, {'measure': 'Standard deviation of mean glucose (SD)', 'timeFrame': '14 days', 'description': 'Standard deviation of mean glucose (SD) (mmol/L and mg/dL)'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Continuous Glucose Monitoring', 'Self-management', 'Diabetes Technology', 'Type 1 Diabetes', 'Diabetes Distress', 'Patient-reported Outcomes'], 'conditions': ['Type 1 Diabetes']}, 'referencesModule': {'references': [{'pmid': '40897486', 'type': 'DERIVED', 'citation': 'Nitschke MJ, Demir C, Brosen JMB, Tapager IW, Norgaard K, Kristensen PL, Pedersen-Bjergaard U. Diabetes self-management observational study investigating how CGM use impacts diabetes distress, glycaemia and functions as a technological substitute for hypoglycaemia awareness: a study protocol. BMJ Open. 2025 Sep 2;15(9):e103469. doi: 10.1136/bmjopen-2025-103469.'}]}, 'descriptionModule': {'briefSummary': 'The overall goal of this observational study is to investigate the interaction between people with type 1 diabetes and continuous glucose monitoring (CGM) and the impact of this interaction on quality of life, particularly the level of diabetes distress, and glycaemic metrics.\n\nParticipants will:\n\n* Visit the clinic twice with a 14-day interval\n* Fill out a survey before the first and at the last visit\n* Use CGM as usual and use smart insulin pens and an activity tracker\n* Register food intake\n* Answer two-three questions twice a day in REDCap', 'detailedDescription': 'A two-centre observational study conducted in Denmark, including adults with type 1 diabetes (n=500) on multiple daily injections already using FreeStyle Libre 2.\n\nUpon recruitment, participants will complete a survey of 11 validated questionnaires, including T1-DDS-28. For 14 days, participants will continue regular CGM use, smart insulin pens will record real-time insulin dosage, and an activity sensor will monitor physical activity and sleep. Participants will register food intake in the LibreLink app and respond to queries on quality of life twice daily through REDCap. At the end of the study, participants will complete the T1-DDS-28 and Health Literacy Questionnaire.\n\nOur primary objectives is to investigate the association between diabetes distress (assessed by Type 1 Diabetes Distress Scale (T1-DDS-28)) and:\n\n1. frequency of reading CGM data,\n2. frequency of low glucose alarms,\n3. frequency of high glucose alarms,\n4. frequency of daily between-meal insulin corrections,\n5. frequency of hypoglycaemic events preceded by correction of hyperglycaemia with insulin,\n6. frequency of hyperglycaemic events preceded by correction of hypoglycaemia with carbohydrates, and\n7. sociodemographic and psychosocial characteristics of CGM users.\n\nOur secondary objective is to investigate the association between glycaemic metrics and the variables described above. Glycaemic metrics will be reported as CGM-metrics, including time in range defined as the percentage of time the sensor glucose is 3.9-10.0 mmol/L (70-180 mg/dL), per international consensus (ATTD, 2022)'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '85 Years', 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Adults with type 1 diabetes (n=500) on multiple daily insulin injections already using FreeStyle Libre 2.', 'healthyVolunteers': False, 'eligibilityCriteria': "Inclusion Criteria:\n\n1. Age between 18 and 85 years.\n2. Diagnosed with T1D over one year ago.\n3. Actively using FreeStyle Libre 2 (\\>80% sensor activity).\n4. Used FreeStyle Libre 2 for over three months.\n5. Uses multiple daily insulin injections.\n6. Capable of providing written informed consent.\n7. Willing and able to complete study procedures, including using smart caps or pens and completing questionnaires at the investigator's discretion.\n\nExclusion Criteria:\n\n1. History of allergic reactions to materials or adhesives used in CGM devices.\n2. Presence of severe cognitive or psychiatric conditions that could hinder the effective use of CGM or smart caps or pens - at the investigator's discretion.\n3. Current use of steroids unless part of a chronic therapy plan.\n4. Daily consumption of vitamin C ≥ 500 mg."}, 'identificationModule': {'nctId': 'NCT06453434', 'acronym': 'DIASELF', 'briefTitle': 'Diabetes Self-management With Continuous Glucose Monitoring', 'organization': {'class': 'OTHER', 'fullName': 'Nordsjaellands Hospital'}, 'officialTitle': 'The Impact of Continuous Glucose Monitoring Based Self-management on Patient-Reported Outcomes and Glycaemia in Type 1 Diabetes', 'orgStudyIdInfo': {'id': 'U1111-1306-6133'}}, 'contactsLocationsModule': {'locations': [{'zip': '2730', 'city': 'Herlev', 'state': 'Capital Region', 'country': 'Denmark', 'contacts': [{'name': 'Kirsten Nørgaard, Professor', 'role': 'CONTACT', 'email': 'kirsten.noergaard@regionh.dk', 'phone': '+45 27 13 10 11'}, {'name': 'Kirsten Nørgaard, Professor', 'role': 'PRINCIPAL_INVESTIGATOR'}], 'facility': 'Steno Diabetes Center Copenhagen', 'geoPoint': {'lat': 55.72366, 'lon': 12.43998}}, {'zip': '3400', 'city': 'Hillerød', 'state': 'Capital Region', 'country': 'Denmark', 'contacts': [{'name': 'Mette J Nitschke, PhD student', 'role': 'CONTACT', 'email': 'mette.juul.nitschke@regionh.dk', 'phone': '+45 41 24 72 16'}, {'name': 'Mette J Nitschke, PhD student', 'role': 'SUB_INVESTIGATOR'}, {'name': 'Ulrik Pedersen-Bjergaard, Professor', 'role': 'PRINCIPAL_INVESTIGATOR'}], 'facility': 'Copenhagen University Hospital, North Zealand - Hilleroed', 'geoPoint': {'lat': 55.92791, 'lon': 12.30081}}], 'centralContacts': [{'name': 'Mette J Nitschke, PhD Student', 'role': 'CONTACT', 'email': 'mette.juul.nitschke@regionh.dk', 'phone': '+45 41 24 72 16'}, {'name': 'Ulrik Pedersen-Bjergaard, Professor', 'role': 'CONTACT', 'email': 'ulrik.pedersen-bjergaard@outlook.dk'}], 'overallOfficials': [{'name': 'Ulrik Pedersen-Bjergaard, Professor', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Copenhagen University Hospital, North Zealand - Hollered'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Nordsjaellands Hospital', 'class': 'OTHER'}, 'collaborators': [{'name': 'Steno Diabetes Center Copenhagen', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}