[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100658787":3},{"organization":4,"outcomesModule":7,"designInfo":14,"detailedDescription":15,"studyPopulation":16,"armGroups":17,"interventions":13,"overallOfficials":21,"centralContacts":26,"locations":13,"responsibleParty":35,"collaborators":38,"id":85,"slug":86,"hasResults":87,"nctId":88,"briefTitle":89,"officialTitle":89,"acronym":90,"eligibilityCriteria":91,"healthyVolunteers":92,"sex":93,"minAge":94,"maxAge":95,"enrollmentInfo":96,"targetDuration":13,"studyType":99,"phases":13,"briefSummary":100,"conditions":101,"keywords":106,"overallStatus":112,"whyStopped":13,"lastUpdateSubmitDate":113,"lastUpdatePostDateStruct":114,"startDateStruct":117,"completionDateStruct":119,"leadSponsor":121,"locationsCount":13},{"fullName":5,"class":6},"Nanjing Medical University","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":13},[9],{"measure":10,"description":11,"timeFrame":12},"Glycemic status transition","Participants will be classified according to their glycemic status during follow-up as: (1) progression to type 2 diabetes, defined as fasting plasma glucose (FPG) ≥7.0 mmol\u002FL, 2-hour plasma glucose (2h-PG) ≥11.1 mmol\u002FL, or HbA1c ≥6.5%; (2) persistent prediabetes; or (3) reversion to normal glucose regulation, defined as FPG \\\u003C6.1 mmol\u002FL and HbA1c \\\u003C5.7%. The proportion of participants in each glycemic outcome category will be assessed.","From baseline through 3 years of follow-up",null,{"allocation":13,"interventionModel":13,"interventionModelDescription":13,"primaryPurpose":13,"observationalModel":6,"timePerspective":6,"maskingInfo":13},"This is a multicenter observational study integrating prospective and retrospective cohort data with a case-control component to investigate the development and progression of prediabetes in Chinese adults. The study is designed to characterize the heterogeneity of prediabetes by combining clinical, metabolic, lifestyle, environmental, genetic, and longitudinal health data. No pharmacological treatment is assigned by the study, and participation does not replace or modify routine clinical care.\n\nThe study has three major components. First, data from existing cohorts, including the previous cohort, participating hospitals, and health examination programs will be harmonized to identify clinical, behavioral, environmental, and genetic factors associated with prediabetes and its long-term progression. Multivariable statistical methods and machine-learning approaches will be used to identify important risk factors and explore interactions among genetic background, environmental exposure, lifestyle, and metabolic characteristics.\n\nSecond, a prospective observational cohort will undergo standardized baseline and follow-up assessments. Data collection may include questionnaires on health status and lifestyle, anthropometric measurements, oral glucose tolerance testing, biochemical measurements, body composition assessment, liver transient elastography, pulse wave velocity, urine testing, and continuous glucose monitoring. Blood and other biological samples will be collected for selected research analyses, including genetic testing and metabolomic profiling. Participants will be followed longitudinally to characterize changes in glucose metabolism and related metabolic phenotypes.\n\nThird, a case-control component will compare participants with prediabetes with individuals who have normal glucose regulation but other metabolic risk factors. Genetic, metabolic, behavioral, and environmental characteristics will be compared between groups to identify factors associated with abnormal glucose regulation. Genetic information from genome-wide genotyping will also be used to construct polygenic risk scores, which will be integrated with clinical and metabolic data.\n\nLongitudinal data will be used to identify metabolic subtypes of prediabetes and to develop prediction models for future changes in glucose regulation. Unsupervised clustering and other machine-learning methods will be used to characterize distinct metabolic phenotypes. Time-series data will also be used to develop and validate prediction models, including Transformer-based models, for estimating the risk of future progression of glucose abnormalities.\n\nThe planned observational cohort will include at least 30,000 participants. This sample size was selected to provide an adequate number of longitudinal outcome events for multivariable risk modeling and high-dimensional machine-learning analyses. A separate case-control component will include approximately 3,000 participants, with equal numbers of prediabetes cases and metabolically at-risk controls.\n\nStandardized operating procedures will be used across participating centers for participant recruitment, informed consent, data collection, laboratory testing, sample handling, follow-up, data management, and quality control. Study personnel and clinical research coordinators will receive standardized training before participating in study procedures.\n\nEach participant will be assigned a unique study identifier. Study identifiers, barcodes, scheduled assessment times, sample information, and completion status will be used to maintain traceability between participants, clinical assessments, biological samples, and study data.\n\nData will be obtained from multiple sources, including hospital information systems, structured questionnaires, case report forms, laboratory systems, study examinations, wearable devices, and continuous glucose monitoring systems. Where applicable, registry data will be compared with source medical records, laboratory records, case report forms, and device-generated data to evaluate data accuracy and completeness.\n\nAutomated and manual data checks will be used to identify values outside predefined ranges, inconsistent information across variables, duplicate records, missing data, and other potential data-quality problems. Suspected errors will be reviewed against available source records before correction. Key study procedures and protocol deviations will be documented and remain traceable.\n\nA standardized data dictionary and coding framework will be used across participating centers. The data dictionary will define study variables, data sources, formats, coding rules, allowable values, and relevant units. Data will be stored in a centralized, de-identified research database with access controls and data security procedures.\n\nQuality monitoring will include routine centralized review and planned site-level monitoring. Monitoring will focus on informed consent, participant identification, completeness of key study assessments, timing of oral glucose tolerance testing, sample tracking, device data, protocol deviations, and consistency between source information and the research database.\n\nMissing or incomplete data will be characterized before analysis. Depending on the extent and pattern of missingness, statistical approaches such as multiple imputation may be used. Sensitivity analyses will be performed to evaluate the robustness of major findings to missing data and different analytical assumptions.\n\nStatistical analyses will include descriptive analyses, multivariable regression, longitudinal risk modeling, subgroup and interaction analyses, and machine-learning approaches. Logistic regression and time-to-event models will be used where appropriate to evaluate associations between baseline or longitudinal factors and changes in glucose regulation. Machine-learning and clustering methods will be used to identify metabolic subtypes and develop prediction models. Model performance will be evaluated using internal and, where available, external validation datasets.","Adults aged 20 to 69 years will be recruited from participating hospitals, previous cohort populations, and health examination programs. The study population will include individuals with prediabetes and individuals with normal glucose metabolism who serve as a comparison group. Participants with prediabetes will meet at least one criterion for impaired fasting glucose, impaired glucose tolerance, or elevated HbA1c without meeting diagnostic criteria for diabetes. Participants in the normal glucose metabolism group will have normal fasting glucose, 2-hour glucose during a 75-g oral glucose tolerance test, and HbA1c, with no previous diagnosis of diabetes or prediabetes.",[18],{"label":19,"type":13,"description":20,"interventionNames":13},"Prediabetes cohort","Adults with prediabetes, defined as impaired fasting glucose, impaired glucose tolerance, and\u002For HbA1c 5.7-6.4%, without a diagnosis of type 2 diabetes.",[22],{"name":23,"affiliation":24,"role":25},"Tao Yang","The First Affiliated Hospital with Nanjing Medical University","PRINCIPAL_INVESTIGATOR",[27,31],{"name":23,"role":28,"phone":29,"phoneExt":13,"email":30},"CONTACT","0086-13851498409","yangt@njmu.edu.cn",{"name":32,"role":28,"phone":33,"phoneExt":13,"email":34},"Jingyang Gao","0086-13127526220","gaojingyang2011@163.com",{"type":25,"investigatorFullName":36,"investigatorTitle":37,"investigatorAffiliation":5,"oldNameTitle":13,"oldOrganization":13},"Yang Tao","Professor and Director, Department of Endocrinology",[39,41,43,45,47,49,51,53,55,57,59,61,64,66,68,70,73,75,77,79,81,83],{"name":40,"class":6},"The Affiliated Hospital Of Guizhou Medical University",{"name":42,"class":6},"The First Affiliated Hospital of Zhengzhou University",{"name":44,"class":6},"Suqian First Hospital",{"name":46,"class":6},"Jiangsu Taizhou People's Hospital",{"name":48,"class":6},"The First People's Hospital of Lianyungang",{"name":50,"class":6},"The Second People's Hospital of Huai'an",{"name":52,"class":6},"Wuxi People's Hospital",{"name":54,"class":6},"Nantong First People's Hospital",{"name":56,"class":6},"Yancheng First People's Hospital",{"name":58,"class":6},"The First Hospital of Jilin University",{"name":60,"class":6},"Fujian Medical University Union Hospital",{"name":62,"class":63},"Shandong Provincial Hospital","OTHER_GOV",{"name":65,"class":6},"The First Affiliated Hospital of Nanchang University",{"name":67,"class":6},"People's Hospital of Xinjiang Uygur Autonomous Region",{"name":69,"class":6},"Xijing Hospital",{"name":71,"class":72},"Dalian Central Hospital","UNKNOWN",{"name":74,"class":6},"Xinqiao Hospital of Chongqing",{"name":76,"class":6},"Suzhou Municipal Hospital",{"name":78,"class":6},"Wuhu City Second People's Hospital",{"name":80,"class":72},"Shangrao People's Hospital",{"name":82,"class":72},"The Fourth Affiliated Hospital of Nanjing Medical University",{"name":84,"class":6},"Changzhou Second People's Hospital affiliated with Nanjing Medical University","100658787","multimodal-risk-factor-graph-mapping-metabolic-subtyping-and-digital-intelligent-chronic-disease-management-for-prediabetes-an-integrated-cohort-and-case-control-clinical-study-100658787",false,"NCT07854002","Multimodal Risk Factor Graph Mapping, Metabolic Subtyping, and Digital Intelligent Chronic Disease Management for Prediabetes: An Integrated Cohort and Case-Control Clinical Study","DM-PIONEER","Inclusion Criteria\n\nParticipants must meet all of the following common criteria (Items 1-3) and meet either the population definition in Item 4 or Item 5:\n\nAged ≥20 years and \\\u003C70 years on the date of signing the informed consent form. No restriction on sex. The overall multicenter recruitment plan aims to maintain an approximately 1:1 male-to-female ratio.\n\nAble to use smartphone-based applications, including a WeChat mini-program or mobile application, and willing to participate in up to 3 years of follow-up and digital health management. Written informed consent must be provided by the participant or his\u002Fher legal guardian.\n\nPrediabetes group: Participants must not meet diagnostic criteria for diabetes and must meet at least one of the following criteria for prediabetes:\n\nImpaired fasting glucose (IFG): 6.1 mmol\u002FL ≤ fasting plasma glucose (FPG) \\\u003C7.0 mmol\u002FL; Impaired glucose tolerance (IGT): 7.8 mmol\u002FL ≤ 2-hour plasma glucose (2h-PG) \\\u003C11.1 mmol\u002FL during a 75-g oral glucose tolerance test (OGTT); Hemoglobin A1c (HbA1c): 5.7% ≤ HbA1c \\\u003C6.5%. Normal glucose metabolism group: FPG \\\u003C6.1 mmol\u002FL, 2-hour plasma glucose \\\u003C7.8 mmol\u002FL during a 75-g OGTT, and HbA1c \\\u003C5.7%, with no previous diagnosis of diabetes or prediabetes.\n\nExclusion Criteria\n\nParticipants meeting any of the following criteria will be excluded:\n\nPrevious diagnosis of type 2 diabetes, type 1 diabetes, or other specific types of diabetes, including gestational diabetes mellitus or pancreatogenic diabetes.\n\nClinically significant severe cardiac, hepatic, or renal dysfunction, or an advanced major medical condition, including:\n\nestimated glomerular filtration rate (eGFR) \\\u003C45 mL\u002Fmin\u002F1.73 m²; acute myocardial infarction within 6 months before baseline; unstable angina; congestive heart failure, New York Heart Association (NYHA) class III-IV; severe arrhythmia; stroke, including cerebral infarction or intracerebral hemorrhage, within 6 months before baseline.\n\nActive malignancy currently being treated with chemotherapy, radiotherapy, or immunotherapy; acute or chronic infection or autoimmune disease that may compromise the safety of follow-up; psychiatric disorders, including severe depression, schizophrenia, or bipolar disorder; or severe cognitive impairment or impaired consciousness that may affect adherence to study questionnaires or the reliability of follow-up data.\n\nPregnant or breastfeeding women, or women planning pregnancy within the next 24 months.\n\nCurrent participation in another interventional clinical trial, or participation in another drug or medical device clinical trial within 3 months before baseline; or participants considered by the investigator to be at high risk of withdrawal or loss to follow-up for non-medical reasons, such as frequent changes in permanent residence.",true,"ALL","20 Years","70 Years",{"count":97,"type":98},30000,"ESTIMATED","OBSERVATIONAL","This observational study aims to understand the metabolic characteristics and long-term changes in adults with prediabetes and to identify risk and protective factors associated with progression to diabetes or return to normal glucose regulation. The study will include adults aged 20 to 69 years with prediabetes.\n\nThe main questions this study aims to answer are:\n\nWhich clinical characteristics, lifestyle factors, social and environmental factors, and genetic factors are associated with progression or improvement of prediabetes? How do blood glucose levels, pancreatic islet function, and other metabolic indicators change over time in people with prediabetes?\n\nParticipants will complete questionnaires about their health status and lifestyle at baseline and during follow-up. According to the study schedule, they will also undergo blood glucose and other metabolic assessments, including an oral glucose tolerance test (OGTT). Some participants will undergo additional assessments, such as body composition analysis, liver elasticity measurement, and arterial stiffness testing. Blood, urine, and other biological samples may also be collected for further research.\n\nParticipants will be followed over time to assess changes in glucose metabolism and lifestyle. Researchers will evaluate factors associated with return to normal glucose regulation, persistent prediabetes, or progression to diabetes. The findings may help improve early identification and personalized management of people at high risk of developing diabetes.",[102,103,104,105],"Prediabetes","Prediabetes (Insulin Resistance, Impaired Glucose Tolerance)","Impaired Fasting Glucose","Impaired Glucose Tolerance (Prediabetes)",[102,107,108,109,110,111],"metabolic disease","Glucose Metabolism","Insulin Resistance","Beta-cell Function","Diabetes","NOT_YET_RECRUITING","2026-09-27",{"date":115,"type":116},"2026-10-02","ACTUAL",{"date":118,"type":98},"2026-10-08",{"date":120,"type":98},"2029-08-31",{"name":5,"class":6}]