Ignite Creation Date:
2025-12-25 @ 2:59 AM
Ignite Modification Date:
2025-12-31 @ 8:36 PM
Study NCT ID:
NCT04369833
Status:
COMPLETED
Last Update Posted:
2022-05-09
First Post:
2020-04-27
Is NOT Gene Therapy:
True
Has Adverse Events:
True
Brief Title:
Development of Continuous Glucose Monitoring System Cohort for Personalized Diabetes Prevention and Management Platform
Sponsor:
Organization:
Raw JSON
{'hasResults': True, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D011236', 'term': 'Prediabetic State'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D003920', 'term': 'Diabetes Mellitus'}], 'ancestors': [{'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}]}, 'interventionBrowseModule': {'meshes': [{'id': 'D000095583', 'term': 'Continuous Glucose Monitoring'}], 'ancestors': [{'id': 'D001774', 'term': 'Blood Chemical Analysis'}, {'id': 'D019963', 'term': 'Clinical Chemistry Tests'}, {'id': 'D019411', 'term': 'Clinical Laboratory Techniques'}, {'id': 'D019937', 'term': 'Diagnostic Techniques and Procedures'}, {'id': 'D003933', 'term': 'Diagnosis'}, {'id': 'D003940', 'term': 'Diagnostic Techniques, Endocrine'}, {'id': 'D008991', 'term': 'Monitoring, Physiologic'}, {'id': 'D008919', 'term': 'Investigative Techniques'}]}}, 'resultsSection': {'moreInfoModule': {'pointOfContact': {'email': 'drsskim7@gmail.com', 'phone': '+82-51-240-7837', 'title': 'Dr. Sang Soo Kim', 'organization': 'Pusan national university hospital'}, 'certainAgreement': {'piSponsorEmployee': True}}, 'adverseEventsModule': {'timeFrame': '1 week', 'eventGroups': [{'id': 'EG000', 'title': 'Continuous Glucose Monitoring Group', 'description': 'all participants wearing a continuous glucose monitoring device\n\ncontinuous glucose monitoring system: wearing continuous glucose monitoring device (iPro2 professional continuous glucose monitoring, MedtronicⓇ, California, USA)', 'otherNumAtRisk': 129, 'deathsNumAtRisk': 129, 'otherNumAffected': 1, 'seriousNumAtRisk': 129, 'deathsNumAffected': 0, 'seriousNumAffected': 0}], 'otherEvents': [{'term': 'bleeding on CGM insertion site', 'stats': [{'groupId': 'EG000', 'numAtRisk': 129, 'numEvents': 1, 'numAffected': 1}], 'organSystem': 'Skin and subcutaneous tissue disorders', 'assessmentType': 'NON_SYSTEMATIC_ASSESSMENT'}], 'frequencyThreshold': '0'}, 'outcomeMeasuresModule': {'outcomeMeasures': [{'type': 'PRIMARY', 'title': 'Number of Participants With Insulin Resistance', 'denoms': [{'units': 'Participants', 'counts': [{'value': '129', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Continuous Glucose Monitoring Group', 'description': 'all participants wearing a continuous glucose monitoring device\n\ncontinuous glucose monitoring system: wearing continuous glucose monitoring device (iPro2 professional continuous glucose monitoring, MedtronicⓇ, California, USA)'}], 'classes': [{'categories': [{'measurements': [{'value': '69', 'groupId': 'OG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'timeFrame': '1 week', 'description': 'the prevalence of insulin resistance in participants was measured. Insulin resistance was calculated by HOMA-IR(homeostatic model assessment of insulin resistance), QUICKI (quantitative insulin sensitivity check index) and Matsuda index', 'unitOfMeasure': 'Participants', 'reportingStatus': 'POSTED'}]}, 'participantFlowModule': {'groups': [{'id': 'FG000', 'title': 'Continuous Glucose Monitoring Group', 'description': 'all participants wearing a continuous glucose monitoring device\n\ncontinuous glucose monitoring system: wearing continuous glucose monitoring device (iPro2 professional continuous glucose monitoring, MedtronicⓇ, California, USA)'}], 'periods': [{'title': 'Overall Study', 'milestones': [{'type': 'STARTED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '130'}]}, {'type': 'COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '129'}]}, {'type': 'NOT COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '1'}]}]}]}, 'baselineCharacteristicsModule': {'denoms': [{'units': 'Participants', 'counts': [{'value': '129', 'groupId': 'BG000'}]}], 'groups': [{'id': 'BG000', 'title': 'Continuous Glucose Monitoring Group', 'description': 'all participants wearing a continuous glucose monitoring device\n\ncontinuous glucose monitoring system: wearing continuous glucose monitoring device (iPro2 professional continuous glucose monitoring, MedtronicⓇ, California, USA)'}], 'measures': [{'title': 'Age, Continuous', 'classes': [{'categories': [{'measurements': [{'value': '56.6', 'spread': '12.15', 'groupId': 'BG000'}]}]}], 'paramType': 'MEAN', 'unitOfMeasure': 'years', 'dispersionType': 'STANDARD_DEVIATION'}, {'title': 'Sex: Female, Male', 'classes': [{'categories': [{'title': 'Female', 'measurements': [{'value': '96', 'groupId': 'BG000'}]}, {'title': 'Male', 'measurements': [{'value': '33', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Race (NIH/OMB)', 'classes': [{'categories': [{'title': 'American Indian or Alaska Native', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Asian', 'measurements': [{'value': '129', 'groupId': 'BG000'}]}, {'title': 'Native Hawaiian or Other Pacific Islander', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Black or African American', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'White', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'More than one race', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Unknown or Not Reported', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Region of Enrollment', 'classes': [{'title': 'South Korea', 'categories': [{'measurements': [{'value': '129', 'groupId': 'BG000'}]}]}], 'paramType': 'NUMBER', 'unitOfMeasure': 'participants'}, {'title': 'Mean CGM glucose', 'classes': [{'categories': [{'measurements': [{'value': '122.6', 'spread': '15.5', 'groupId': 'BG000'}]}]}], 'paramType': 'MEAN', 'unitOfMeasure': 'mg/dL', 'dispersionType': 'STANDARD_DEVIATION'}, {'title': 'the coefficient of variation of CGM glucose', 'classes': [{'categories': [{'measurements': [{'value': '19.6', 'spread': '6.4', 'groupId': 'BG000'}]}]}], 'paramType': 'MEAN', 'unitOfMeasure': 'percentage of coefficient of variation', 'dispersionType': 'STANDARD_DEVIATION'}], 'populationDescription': 'Patients who have high risk for developing diabetes with wearing CGM.'}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2020-11-15', 'size': 243289, 'label': 'Study Protocol and Statistical Analysis Plan', 'hasIcf': False, 'hasSap': True, 'filename': 'Prot_SAP_000.pdf', 'typeAbbrev': 'Prot_SAP', 'uploadDate': '2021-04-07T20:57', 'hasProtocol': True}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITHOUT_DNA', 'description': 'blood sample (for HbA1c, Total cholesterol, LDL-C, HDL-C, Triglyceride, aspartate aminotransferase, alanine aminotransferase, Creatinine, free fatty acid etc), Feces (for evaluating microbiomes)'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 130}, 'targetDuration': '7 Days', 'patientRegistry': True}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2020-05-11', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-02', 'completionDateStruct': {'date': '2020-09-30', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2022-02-26', 'studyFirstSubmitDate': '2020-04-27', 'resultsFirstSubmitDate': '2021-03-13', 'studyFirstSubmitQcDate': '2020-04-27', 'lastUpdatePostDateStruct': {'date': '2022-05-09', 'type': 'ACTUAL'}, 'resultsFirstSubmitQcDate': '2022-02-26', 'studyFirstPostDateStruct': {'date': '2020-04-30', 'type': 'ACTUAL'}, 'resultsFirstPostDateStruct': {'date': '2022-05-09', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2020-09-30', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Number of Participants With Insulin Resistance', 'timeFrame': '1 week', 'description': 'the prevalence of insulin resistance in participants was measured. Insulin resistance was calculated by HOMA-IR(homeostatic model assessment of insulin resistance), QUICKI (quantitative insulin sensitivity check index) and Matsuda index'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['PreDiabetes', 'Glucose Metabolism Disorders', 'Diabetes Mellitus']}, 'referencesModule': {'references': [{'pmid': '18508669', 'type': 'BACKGROUND', 'citation': 'Kang H, Han K, Jo J, Kim J, Choi MY. Systems of pancreatic beta-cells and glucose regulation. Front Biosci. 2008 May 1;13:6421-31. doi: 10.2741/3163.'}, {'pmid': '7037815', 'type': 'BACKGROUND', 'citation': 'Hansen BC, Jen KC, Belbez Pek S, Wolfe RA. Rapid oscillations in plasma insulin, glucagon, and glucose in obese and normal weight humans. J Clin Endocrinol Metab. 1982 Apr;54(4):785-92. doi: 10.1210/jcem-54-4-785.'}, {'pmid': '386121', 'type': 'BACKGROUND', 'citation': 'Lang DA, Matthews DR, Peto J, Turner RC. Cyclic oscillations of basal plasma glucose and insulin concentrations in human beings. N Engl J Med. 1979 Nov 8;301(19):1023-7. doi: 10.1056/NEJM197911083011903.'}, {'pmid': '30735238', 'type': 'BACKGROUND', 'citation': 'Mendes-Soares H, Raveh-Sadka T, Azulay S, Edens K, Ben-Shlomo Y, Cohen Y, Ofek T, Bachrach D, Stevens J, Colibaseanu D, Segal L, Kashyap P, Nelson H. Assessment of a Personalized Approach to Predicting Postprandial Glycemic Responses to Food Among Individuals Without Diabetes. JAMA Netw Open. 2019 Feb 1;2(2):e188102. doi: 10.1001/jamanetworkopen.2018.8102.'}, {'pmid': '31339012', 'type': 'BACKGROUND', 'citation': 'Kim BY, Won JC, Lee JH, Kim HS, Park JH, Ha KH, Won KC, Kim DJ, Park KS. Diabetes Fact Sheets in Korea, 2018: An Appraisal of Current Status. Diabetes Metab J. 2019 Aug;43(4):487-494. doi: 10.4093/dmj.2019.0067. Epub 2019 Jul 17.'}, {'pmid': '30113144', 'type': 'BACKGROUND', 'citation': 'Ha KH, Lee YH, Song SO, Lee JW, Kim DW, Cho KH, Kim DJ. Development and Validation of the Korean Diabetes Risk Score: A 10-Year National Cohort Study. Diabetes Metab J. 2018 Oct;42(5):402-414. doi: 10.4093/dmj.2018.0014. Epub 2018 Jul 6.'}, {'pmid': '22688547', 'type': 'BACKGROUND', 'citation': 'Lee YH, Bang H, Kim HC, Kim HM, Park SW, Kim DJ. A simple screening score for diabetes for the Korean population: development, validation, and comparison with other scores. Diabetes Care. 2012 Aug;35(8):1723-30. doi: 10.2337/dc11-2347. Epub 2012 Jun 11.'}, {'pmid': '26590418', 'type': 'BACKGROUND', 'citation': 'Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A, Ben-Yacov O, Lador D, Avnit-Sagi T, Lotan-Pompan M, Suez J, Mahdi JA, Matot E, Malka G, Kosower N, Rein M, Zilberman-Schapira G, Dohnalova L, Pevsner-Fischer M, Bikovsky R, Halpern Z, Elinav E, Segal E. Personalized Nutrition by Prediction of Glycemic Responses. Cell. 2015 Nov 19;163(5):1079-1094. doi: 10.1016/j.cell.2015.11.001.'}, {'pmid': '3292558', 'type': 'BACKGROUND', 'citation': 'Shapiro ET, Tillil H, Polonsky KS, Fang VS, Rubenstein AH, Van Cauter E. Oscillations in insulin secretion during constant glucose infusion in normal man: relationship to changes in plasma glucose. J Clin Endocrinol Metab. 1988 Aug;67(2):307-14. doi: 10.1210/jcem-67-2-307.'}, {'pmid': '4655495', 'type': 'BACKGROUND', 'citation': 'Kraegen EW, Young JD, George EP, Lazarus L. Oscillations in blood glucose and insulin after oral glucose. Horm Metab Res. 1972 Nov;4(6):409-13. doi: 10.1055/s-0028-1094019. No abstract available.'}, {'pmid': '3102544', 'type': 'BACKGROUND', 'citation': 'Simon C, Brandenberger G, Follenius M. Ultradian oscillations of plasma glucose, insulin, and C-peptide in man during continuous enteral nutrition. J Clin Endocrinol Metab. 1987 Apr;64(4):669-74. doi: 10.1210/jcem-64-4-669.'}]}, 'descriptionModule': {'briefSummary': 'The purpose of this study is to collect a variety of clinical data and blood glucose changes using a continuous glucose monitoring device for high-risk diabetes patients (prediabetes) in order to develop a personalized diabetes prevention and management platform based on artificial intelligence model using mathematical analysis.', 'detailedDescription': 'After being informed about the study and potential risks, all patients giving written informed consent wear a continuous glucose monitoring device ("iPro2" professional continuous glucose monitoring, MedtronicⓇ, California, USA) and smart band ("Fitbit Inspire HR", FitbitⓇ, California, USA) for 1 week.\n\nDuring this period, all patients are tested oral glucose tolerance test and take a standard diet (calorie calculated) at morning.\n\nThe patient\'s data from this study is compared to a predicted values by mathematical analysis model for diabetes prevention.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Subjects of pre-diabetes who visited the Department of Internal Medicine and division of Endodrinology \\& Metabolism and the Health Examination Center, Pusan National University Hospital', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Above 18 years old.\n* Prediabetes\n\n 1. Fasting plasma glucose : 100\\~125mg/dL, fasting is defined as no caloric intake for at least 8 hours.\n\n OR\n 2. 2-hour plasma glucose during 75g oral glucose tolerance test : 140 \\~ 199mg/dL\n\n OR\n 3. Glycated hemoglobin(HbA1c) : 5.7\\~6.4% (39-47mmol/mol)\n\nExclusion Criteria:\n\n* with a history of newly diagnosed and treated cancer within the last 5 years\n* with a history of hospitalization for active disease within the last 3 months\n* with a history of severe cardiovascular disease within the last 3 months\n* with a history of steroid treatment in the last 3 months\n* people who have had major surgery planned within the last 3 months or who have had surgery within 3 months\n* people who are pregnant or have been in the last 3 months after giving birth'}, 'identificationModule': {'nctId': 'NCT04369833', 'briefTitle': 'Development of Continuous Glucose Monitoring System Cohort for Personalized Diabetes Prevention and Management Platform', 'organization': {'class': 'OTHER', 'fullName': 'Pusan National University Hospital'}, 'officialTitle': 'Development of Continuous Glucose Monitoring System Cohort for Personalized Diabetes Prevention and Management Platform Based on Artificial Intelligence Model Using Mathematical Analysis', 'orgStudyIdInfo': {'id': 'H-2003-033-088'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'continuous glucose monitoring group', 'description': 'all participants wearing a continuous glucose monitoring device', 'interventionNames': ['Device: continuous glucose monitoring system']}], 'interventions': [{'name': 'continuous glucose monitoring system', 'type': 'DEVICE', 'description': 'wearing continuous glucose monitoring device (iPro2 professional continuous glucose monitoring, MedtronicⓇ, California, USA)', 'armGroupLabels': ['continuous glucose monitoring group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '49241', 'city': 'Busan', 'country': 'South Korea', 'facility': 'Pusan national university hospital', 'geoPoint': {'lat': 35.10168, 'lon': 129.03004}}], 'overallOfficials': [{'name': 'Sang soo Kim, Master', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Pusan National University Hospital'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'The data are not publicly available due to privacy or ethical restrictions.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Pusan National University Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}