Wearable Device-Based Screening for Anemia Risk (WEAR-ANEMIA)
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.
The 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.
About 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.
Data 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.
Visão geral do estudo
Status
Condições
Descrição detalhada
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.
Study 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.
Signal 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.
Reference standard. Anemia is defined according to Chinese sea-level criteria: hemoglobin below 120 g/L in adult men, below 110 g/L in non-pregnant women, and below 100 g/L in pregnant women.
Sample 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.
Statistical 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.
The wearable device is non-invasive. Study participation does not alter any aspect of the clinical management of participants.
Tipo de estudo
Inscrição (Estimado)
Contactos e Locais
Contato de estudo
- Nome: Jian Li, Phd
- Número de telefone: 010-69155027
- E-mail: lijian@pumch.cn
Estude backup de contato
- Nome: Miao Chen, PHD
- Número de telefone: +86 18618230229
- E-mail: chenm@pumch.cn
Locais de estudo
-
-
Beijing Municipality
-
Beijing, Beijing Municipality, China, 100730
- Peking Union Medical College Hospital
-
Contato:
- Jian Li, Phd
- Número de telefone: 010-69155027
- E-mail: lijian@pumch.cn
-
-
Critérios de participação
Critérios de elegibilidade
Idades elegíveis para estudo
- Adulto
- Adulto mais velho
Aceita Voluntários Saudáveis
Método de amostragem
População do estudo
Descrição
Inclusion Criteria:
- Age 18 to 80 years, any sex
- Willing to participate and able to provide written informed consent
- Able to comply with wearable device wear, venous blood sampling, and functional assessment (e.g., six-minute walk test)
- 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/L in adult men, below 110 g/L in non-pregnant adult women, and below 100 g/L in pregnant women
- For control participants: hemoglobin within the normal reference range -
Exclusion Criteria:
- Axillary temperature 37.3°C or higher on the day of data collection or on the preceding day
- Acute exacerbation of a severe comorbid condition (e.g., decompensated heart failure, respiratory failure, acute infection)
- Skin breakdown, rash, deformity, amputation, or any other condition of the upper limb precluding proper wear of the device
- Refusal of, or intolerance to, invasive venous blood sampling
- Concurrent participation in another interventional clinical trial -
Plano de estudo
Como o estudo é projetado?
Detalhes do projeto
Coortes e Intervenções
Grupo / Coorte |
|---|
|
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.
|
|
Independent validation cohort
Subsequent 150 participants.
Data are used for independent testing of the model and to support iterative optimization.
|
O que o estudo está medindo?
Medidas de resultados primários
Medida de resultado |
Descrição da medida |
Prazo |
|---|---|---|
|
Sensitivity and specificity of the wearable-based deep learning model for binary anemia classification
Prazo: Day 1
|
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
|
Medidas de resultados secundários
Medida de resultado |
Descrição da medida |
Prazo |
|---|---|---|
|
Model performance stability under 24-hour continuous wear
Prazo: Day 1
|
Sensitivity and specificity of the model using signals acquired during 24-hour continuous wearable monitoring in hospitalized participants.
|
Day 1
|
|
Effect of red blood cell size classification on model estimation accuracy
Prazo: Day 1
|
Model sensitivity and specificity stratified by red blood cell size category (microcytic, normocytic, macrocytic) based on mean corpuscular volume
|
Day 1
|
|
Model performance stability under exercise load
Prazo: Day 1 (immediately before and after the six-minute walk test)
|
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)
|
|
Agreement of classification results between left and right wrist placement
Prazo: Day 1
|
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.
|
Day 1
|
Colaboradores e Investigadores
Patrocinador
Colaboradores
Publicações e links úteis
Publicações Gerais
- Zhu J, Sun R, Liu H, Wang T, Cai L, Chen Z, Heng B. A Non-Invasive Hemoglobin Detection Device Based on Multispectral Photoplethysmography. Biosensors (Basel). 2023 Dec 30;14(1):0. doi: 10.3390/bios14010022.
- Li L, Luo R, Medina A, Rozelle S. THE PREVALENCE OF ANEMIA IN CENTRAL AND EASTERN CHINA: EVIDENCE FROM THE CHINA HEALTH AND NUTRITION SURVEY. Southeast Asian J Trop Med Public Health. 2015 Mar;46(2):306-21.
- Li M, Hu Y, Mao D, Wang R, Chen J, Li W, Yang X, Piao J, Yang L. Prevalence of Anemia among Chinese Rural Residents. Nutrients. 2017 Feb 24;9(3):192. doi: 10.3390/nu9030192.
- Liu X, Wang B, Man S, Bao H, Huang Y, Yu C, Lyu J, Wang L, Li L, Liu H. Variations in the Prevalence of Anemia of Varying Severity Among Urban Non-Pregnant Women - China, 2021. China CDC Wkly. 2024 Mar 8;6(10):175-180. doi: 10.46234/ccdcw2024.036.
- Shwarz M. Burden of anemia in the United States from 1990 to 2019: a systematic analysis of the Global Burden of Disease Study 2019. Front Public Health. 2025 Oct 3;13:1653222. doi: 10.3389/fpubh.2025.1653222. eCollection 2025.
Datas de registro do estudo
Datas Principais do Estudo
Início do estudo (Estimado)
Conclusão Primária (Estimado)
Conclusão do estudo (Estimado)
Datas de inscrição no estudo
Enviado pela primeira vez
Enviado pela primeira vez que atendeu aos critérios de CQ
Primeira postagem (Real)
Atualizações de registro de estudo
Última Atualização Postada (Real)
Última atualização enviada que atendeu aos critérios de controle de qualidade
Última verificação
Mais Informações
Termos relacionados a este estudo
Palavras-chave
Termos MeSH relevantes adicionais
Outros números de identificação do estudo
- PUMCH-WEAR-ANEMIA-2026
Plano para dados de participantes individuais (IPD)
Planeja compartilhar dados de participantes individuais (IPD)?
Descrição do plano IPD
Informações sobre medicamentos e dispositivos, documentos de estudo
Estuda um medicamento regulamentado pela FDA dos EUA
Estuda um produto de dispositivo regulamentado pela FDA dos EUA
Essas informações foram obtidas diretamente do site clinicaltrials.gov sem nenhuma alteração. Se você tiver alguma solicitação para alterar, remover ou atualizar os detalhes do seu estudo, entre em contato com register@clinicaltrials.gov. Assim que uma alteração for implementada em clinicaltrials.gov, ela também será atualizada automaticamente em nosso site .