[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"observational-cohort-study\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:observational-cohort-study":33},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,2,0,[8,48],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":16,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":19,"targetDuration":22,"studyType":23,"phases":4,"briefSummary":24,"conditions":25,"keywords":4,"overallStatus":35,"whyStopped":4,"lastUpdateSubmitDate":36,"lastUpdatePostDateStruct":37,"startDateStruct":40,"completionDateStruct":42,"leadSponsor":44,"locationsCount":47},"100644884","clinical-risk-score-prediction-for-risk-of-dementia-among-late-life-population-with-depression-100644884",false,"NCT07676851","Clinical Risk Score Prediction for Risk of Dementia Among Late-life Population With Depression","Development of a Clinical Risk Score Prediction Tool for 5-, 9-, and 13-year Risk of Dementia Among Late-life Population With Depression: a Longitudinal Cohort Study","Inclusion Criteria:\n\n* Adults aged ≥50 years.\n* A diagnosis of depression clearly recorded by a clinician in the electronic medical record at baseline (based on structured or unstructured diagnostic documentation formed through routine clinical practice).\n* Complete baseline electronic medical record data available, including at least demographic information (age, sex), clinical diagnoses, comorbidities, and medication records.\n* At least one follow-up record available in the electronic medical record system to enable determination of incident dementia outcomes.\n* Informed consent provided for the use of routine medical data for this research analysis.\n\nExclusion Criteria:\n\n* Any type of dementia diagnosis recorded in the electronic medical record at baseline (including Alzheimer's disease, vascular dementia, and other types of dementia).\n* Medical record documentation indicating that the diagnosis of dementia preceded the diagnosis of depression, or an inability to clearly determine the chronological order of the two diagnoses.\n* Presence of other neurological diseases at baseline that may independently cause severe cognitive impairment (e.g., Parkinson's disease, multiple sclerosis, brain tumor, normal pressure hydrocephalus).\n* Missing key baseline electronic medical record data that would preclude subsequent risk model analysis.\n* Incomplete follow-up information or inability to clearly confirm incident dementia outcomes through the electronic medical record system.\n* Refusal to participate in the study or withdrawal of informed consent.",true,"ALL","50 Years",{"count":20,"type":21},44,"ESTIMATED","13 Years","OBSERVATIONAL","The goal of this observational study is to learn about the ability of a point risk score prediction model, developed using electronic medical record data, to predict the risk of progression from geriatric depression to dementia in older Chinese adults. The main questions it aims to answer are:\n\nDoes a higher point risk score increase the risk of developing dementia in older adults with depression?\n\nWhat is the accuracy of the point risk score prediction model in identifying individuals at high risk of dementia among older adults with depression?\n\nParticipants will receive their usual medical care as they normally would. No new treatments, tests, or procedures will be performed specifically for this study. The research team will collect data from their electronic medical records, including depression diagnoses, dementia diagnoses, comorbidities, medication records, and follow-up information. The point risk score will be calculated based on these routinely collected clinical data.",[26,27,28,29,30,31,32,33,34],"Alzheimer Dementia (AD)","Dementia","Late Life Depression (LLD)","Risk Scores","Prediction","Chinese Population","Obs e r","Observational Cohort Study","External Validation","RECRUITING","2026-06-24",{"date":38,"type":39},"2026-06-30","ACTUAL",{"date":41,"type":39},"2006-06-01",{"date":43,"type":21},"2030-06-30",{"name":45,"class":46},"Second Affiliated Hospital of Nanchang University","OTHER",1,{"id":49,"slug":50,"hasResults":11,"nctId":51,"briefTitle":52,"officialTitle":52,"acronym":4,"eligibilityCriteria":53,"healthyVolunteers":16,"sex":17,"minAge":54,"maxAge":4,"enrollmentInfo":55,"targetDuration":57,"studyType":23,"phases":4,"briefSummary":58,"conditions":59,"keywords":4,"overallStatus":35,"whyStopped":4,"lastUpdateSubmitDate":66,"lastUpdatePostDateStruct":67,"startDateStruct":69,"completionDateStruct":70,"leadSponsor":71,"locationsCount":47},"100640845","phenotypic-age-acceleration-phenoageaccel-for-joint-prediction-of-disease-risk-mortality-risk-life-expectancy-and-disease-free-healthspan-in-major-chronic-diseases-100640845","NCT07595094","Phenotypic Age Acceleration (PhenoAgeAccel) for Joint Prediction of Disease Risk, Mortality Risk, Life Expectancy, and Disease-Free Healthspan in Major Chronic Diseases","Inclusion Criteria:\n\n* Adults aged 35-73 years old. Complete routine blood test data available at baseline to calculate Phenotypic -Age (including albumin, alkaline phosphatase, creatinine, glucose, C-reactive protein, lymphocyte percentage, mean corpuscular volume, red cell distribution width, and white blood cell count).\n\nComplete demographic and clinical data (e.g., sex, BMI, comorbidities) available at baseline.\n\n* Consent to use routine medical data for research follow-up analysis.\n\nExclusion Criteria:\n\n* Presence of end-stage diseases (e.g., end-stage liver\u002Frenal failure) other than the major chronic diseases of interest at baseline.\n* Key baseline data missing, making Phenotypic Age calculation impossible. Incomplete follow-up information or inability to confirm outcomes (e.g., death, disease onset) via database linkage.\n* Refusal to participate in the study or withdrawal of informed consent.","35 Years",{"count":56,"type":21},2000000,"10 Years","The goal of this observational study is to learn about the ability of Phenotypic Age Acceleration (PhenoAgeAccel) to predict four key health outcomes in Chinese people with or at risk of major chronic diseases: the risk of developing new chronic diseases, the risk of dying, life expectancy, and disease-free healthspan.\n\nThe main questions this study aims to answer are:\n\n* Does higher PhenoAgeAccel increase the risk of developing major chronic diseases (including diabetes, dementia, cancer, and chronic respiratory diseases) in Chinese adults?\n* Does higher PhenoAgeAccel increase the risk of death from all causes in Chinese adults?\n* How do life expectancy and disease-free healthspan differ between people with high versus low PhenoAgeAccel?\n\nWho can take part in this study? Adults aged 35 or above years old who receive routine care at participating hospitals in China, have complete routine blood test data available, and have provided consent to use their health information for research purposes.\n\nWhat will participants go through? Participants will receive their usual medical care as they normally would. No new treatments, tests, or procedures will be performed specifically for this study. We will collect data from their medical records, including blood test results used to calculate PhenoAgeAccel, diagnoses of new diseases, and dates of death.\n\nWhat are the potential benefits? Participants will not receive direct personal benefits from taking part in this study. However, the information learned may help us better understand biological aging and improve future risk assessment and health management for people with chronic diseases.\n\nIs this study safe? Yes. This is an observational study that does not involve any new drugs, devices, or invasive procedures. All data used in the study will be de-identified and kept strictly confidential to protect participants' privacy.",[60,61,62,63,64,65,31,33],"Phenotypic Age Acceleration","Biological Aging Marker","Mortality Risk Prediction","Disease Risk Prediction","Life Expectancy","Disease-Free Healthspan","2026-05-16",{"date":68,"type":39},"2026-05-19",{"date":41,"type":39},{"date":43,"type":21},{"name":45,"class":46}]