[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100654202":3},{"organization":4,"outcomesModule":7,"designInfo":28,"detailedDescription":31,"studyPopulation":32,"armGroups":33,"interventions":27,"overallOfficials":27,"centralContacts":40,"locations":50,"responsibleParty":66,"collaborators":70,"id":74,"slug":75,"hasResults":76,"nctId":77,"briefTitle":78,"officialTitle":78,"acronym":79,"eligibilityCriteria":80,"healthyVolunteers":81,"sex":82,"minAge":83,"maxAge":84,"enrollmentInfo":85,"targetDuration":27,"studyType":88,"phases":27,"briefSummary":89,"conditions":90,"keywords":92,"overallStatus":98,"whyStopped":27,"lastUpdateSubmitDate":99,"lastUpdatePostDateStruct":100,"startDateStruct":103,"completionDateStruct":105,"leadSponsor":107,"locationsCount":108},{"fullName":5,"class":6},"Peking Union Medical College Hospital","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":27},[9],{"measure":10,"description":11,"timeFrame":12},"Sensitivity and specificity of the wearable-based deep learning model for binary anemia classification","Agreement between the model-derived anemia versus non-anemia classification and venous hemoglobin measurement as the reference standard. Venous blood sampling is performed within 3 days before or after wearable signal acquisition.Reported as sensitivity and specificity with 95% confidence intervals in the independent validation cohort.","Day 1",[14,17,20,24],{"measure":15,"description":16,"timeFrame":12},"Model performance stability under 24-hour continuous wear","Sensitivity and specificity of the model using signals acquired during 24-hour continuous wearable monitoring in hospitalized participants.",{"measure":18,"description":19,"timeFrame":12},"Effect of red blood cell size classification on model estimation accuracy","Model sensitivity and specificity stratified by red blood cell size category (microcytic, normocytic, macrocytic) based on mean corpuscular volume",{"measure":21,"description":22,"timeFrame":23},"Model performance stability under exercise load","Comparison of model classification performance using signals acquired before versus after a six-minute walk test in hospitalized participants.","Day 1 (immediately before and after the six-minute walk test)",{"measure":25,"description":26,"timeFrame":12},"Agreement of classification results between left and right wrist placement","Concordance of the model-derived anemia classification between signals acquired with the device worn on the left wrist and on the right wrist in outpatient participants.",null,{"allocation":27,"interventionModel":27,"interventionModelDescription":27,"primaryPurpose":27,"observationalModel":29,"timePerspective":30,"maskingInfo":27},"COHORT","PROSPECTIVE","This is a prospective, observational, diagnostic accuracy study conducted at a single tertiary care hospital in Beijing, China. The purpose is to develop and evaluate a deep learning model for non-invasive binary classification of anemia using multimodal physiological signals acquired from a commercially available consumer wrist-worn wearable device.\n\nStudy procedures. Participants will be enrolled in two sequential stages. In the first stage, 250 participants will be enrolled for algorithm development and tuning. In the second stage, an additional 150 participants will be enrolled for independent testing of the locked model and for supporting iterative optimization. All participants will undergo wearable signal acquisition and venous blood sampling for hemoglobin measurement, which serves as the reference standard.\n\nSignal acquisition differs by care setting. Hospitalized participants will undergo 24-hour continuous wearable monitoring and paired signal acquisition before and after a six-minute walk test. Outpatient participants will undergo short-duration resting acquisition with the device worn alternately on the left and right wrist. Outpatient participants may undergo up to three additional assessments if they return for routine clinical visits; these visits are opportunistic and recorded as they occur. Hospitalized participants undergo a single acquisition without follow-up.\n\nReference standard. Anemia is defined according to Chinese sea-level criteria: hemoglobin below 120 g\u002FL in adult men, below 110 g\u002FL in non-pregnant women, and below 100 g\u002FL in pregnant women.\n\nSample size. The primary endpoint is diagnostic sensitivity. Assuming an expected sensitivity of 70%, an allowable error of 6%, and a confidence level of 95%, at least 225 participants with anemia are required. Allowing for approximately 10% dropout or unusable data, the anemia group is set at 300 or more participants. At least 90 participants with normal hemoglobin will be enrolled to estimate specificity. To support deep learning model training and generalizability assessment, the total target enrollment is 400 participants.\n\nStatistical analysis. Model performance will be reported as sensitivity and specificity. Cross-validation will be used to assess model stability, and an independent test set will be used to assess generalizability.\n\nThe wearable device is non-invasive. Study participation does not alter any aspect of the clinical management of participants.","Adults aged 18 to 80 years recruited from inpatient wards and outpatient clinics at a single tertiary care hospital in Beijing, China. The population includes both participants with a hospital-confirmed diagnosis of anemia and control participants with hemoglobin within the normal reference range. Anemia is defined according to Chinese sea-level criteria: hemoglobin below 120 g\u002FL in adult men, below 110 g\u002FL in non-pregnant adult women, and below 100 g\u002FL in pregnant women. For participants with anemia, a hemoglobin result obtained within the 3 days and a diagnostic report specifying anemia severity, red blood cell size classification, and anemia type are required. Enrollment targets at least 300 participants with anemia and at least 90 participants with normal hemoglobin. Participants are enrolled consecutively as they present for routine clinical care and meet eligibility criteria.",[34,37],{"label":35,"type":27,"description":36,"interventionNames":27},"Model development cohort","First 250 participants. Wearable multimodal physiological signals and venous hemoglobin measurement are collected in parallel and used for deep learning model development and tuning.",{"label":38,"type":27,"description":39,"interventionNames":27},"Independent validation cohort","Subsequent 150 participants. Data are used for independent testing of the model and to support iterative optimization.",[41,46],{"name":42,"role":43,"phone":44,"phoneExt":27,"email":45},"Jian Li, PhD","CONTACT","010-69155027","lijian@pumch.cn",{"name":47,"role":43,"phone":48,"phoneExt":27,"email":49},"Miao Chen, PHD","+86 18618230229","chenm@pumch.cn",[51],{"facility":5,"status":27,"city":52,"state":53,"zip":54,"country":55,"countryCode":56,"cosmosGeoPoint":57,"geoPoint":62,"contacts":63},"Beijing","Beijing Municipality","100730","China","CN",{"type":58,"coordinates":59},"Point",[60,61],116.39723,39.9075,{"lat":61,"lon":60},[64],{"name":65,"role":43,"phone":44,"phoneExt":27,"email":45},"Jian Li, Phd",{"type":67,"investigatorFullName":68,"investigatorTitle":69,"investigatorAffiliation":5,"oldNameTitle":27,"oldOrganization":27},"PRINCIPAL_INVESTIGATOR","Chen Miao","Chief, Department of Hematology",[71],{"name":72,"class":73},"Huawei Device Co., Ltd","INDUSTRY","100654202","wearable-device-based-screening-for-anemia-risk-100654202",false,"NCT07796542","Wearable Device-Based Screening for Anemia Risk","WEAR-ANEMIA","Inclusion Criteria:\n\n1. Age 18 to 80 years, any sex\n2. Willing to participate and able to provide written informed consent\n3. Able to comply with wearable device wear, venous blood sampling, and functional assessment (e.g., six-minute walk test)\n4. For participants with anemia: a hemoglobin test result obtained within 3 days before or after wearable signal acquisition and a hospital diagnostic report, including anemia severity, red blood cell size classification, and anemia type. Anemia is defined according to Chinese sea-level criteria: hemoglobin below 120 g\u002FL in adult men, below 110 g\u002FL in non-pregnant adult women, and below 100 g\u002FL in pregnant women\n5. For control participants: hemoglobin within the normal reference range -\n\nExclusion Criteria:\n\n1. Axillary temperature 37.3°C or higher on the day of data collection or on the preceding day\n2. Acute exacerbation of a severe comorbid condition (e.g., decompensated heart failure, respiratory failure, acute infection)\n3. Skin breakdown, rash, deformity, amputation, or any other condition of the upper limb precluding proper wear of the device\n4. Refusal of, or intolerance to, invasive venous blood sampling\n5. Concurrent participation in another interventional clinical trial -",true,"ALL","18 Years","80 Years",{"count":86,"type":87},400,"ESTIMATED","OBSERVATIONAL","Anemia is a common condition, but it often goes undiagnosed because confirming it requires a venous blood test. This study looks at whether a commercially available wrist-worn smartwatch can help identify people who may have anemia, without taking blood.\n\nThe watch continuously records several types of physiological signals, including photoplethysmography (a light-based measure of blood flow), movement, heart rate, blood oxygen saturation, and heart rate variability. Researchers will use these signals to build a computer model that sorts participants into two groups: likely to have anemia, or unlikely to have anemia.\n\nAbout 400 adults between 18 and 80 years of age will take part at one hospital in Beijing, China. Both patients with anemia and people with normal hemoglobin levels will be included. Each participant will wear the watch and also have a standard venous blood test to measure hemoglobin, which serves as the reference for comparison.\n\nData from the first 250 participants will be used to develop the model. Data from the next 150 participants will be used to test how well the model works in a separate group. The main question is how accurately the watch-based result matches the blood test result.",[91],"Anemia",[93,94,95,96,97],"anemia screening","wearable device","smartwatch","photoplethysmography","non-invasive diagnosis","NOT_YET_RECRUITING","2026-08-28",{"date":101,"type":102},"2026-09-01","ACTUAL",{"date":104,"type":87},"2026-09-05",{"date":106,"type":87},"2027-07-15",{"name":5,"class":6},1]