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Development of a Machine Learning Model for Early-warning of PRISm Using Multimodal Data

Development of a Machine Learning Model for Early-warning of PRISm Using Multimodal Data

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500100853
Enrollment
Unknown
Registered
2025-04-16
Start date
2025-05-06
Completion date
Unknown
Last updated
2025-04-21

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Preserved Ratio lmpaired Spirometry

Interventions

Observation group:None

Sponsors

Shanghai University of Traditional Chinese Medicine
Lead Sponsor

Eligibility

Sex/Gender
All
Age
40 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Age >=40 years old, gender is not limited; 2.Lung function FEV1/FVC>=0.7 after bronchodilator inhalation; 3.Willing to wear flexible wearable devices as required; 4.Be able to cooperate with the completion of assessment questionnaires and necessary tests such as lung function, lung imaging and blood collection; 5.Signed informed consent.

Exclusion criteria

Exclusion criteria: 1.Acute respiratory system infection; 2.A history of pulmonary resection; 3.Suffering from interstitial lung disease; 4.Are receiving medication that may affect lung function, such as long-term use of glucocorticoids or other immunosuppressants; 5.Suffering from malignant tumors; 6.There are contraindications of lung imaging detection, such as people with cardiac pacemakers and pregnant women; 7.There are contraindications in blood collection, such as coagulation disorders, fainting blood and fainting needles; 8.The combination of other system diseases resulting in inability to understand the researcher's instructions and inability to cooperate with standard tests; 9.Patients with orthopedic diseases, old age, inability to walk independently, pregnant women and other impact assessments.

Design outcomes

Primary

MeasureTime frame
Lung function;Modified Medical Research Council;COPD Assessment Test;High-resolution lung CT imaging indexes;TCM constitution classification and judgment;Incremental Shuttle Walking Test;30-second Sit-to-Stand Test;Body fat content, body fat percentage, muscle mass, etc;Activity amount and activity intensity ratio;ECG indicators;

Countries

China

Contacts

Public ContactLiu Xiaodan

Shanghai University of Traditional Chinese Medicine

lxdwwb@126.com+86 158 0066 8700

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026