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| Name | Class |
|---|---|
| The First Affiliated Hospital of Guangzhou Medical University | OTHER |
| Nankai University | OTHER |
| Jilin University | OTHER |
| Shanghai Pulmonary Hospital, Shanghai, China |
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This project aimed to: 1) construct a cohort of no less than 10000 cases of f-ILD (including pneumoconiosis ≥3000 cases) with continuous regular follow-up to reveal the clinical phenotypes closely related to the development, progression and prognosis of pulmonary fibrosis; 2) systematically evaluate the safety and effectiveness of frozen lung biopsy, surgical lung biopsy/thoracoscopic lung biopsy and other techniques, and to optimize the histological diagnosis method of f-ILD; 3) construct a set of artificial intelligence (AI) evaluation system for quantitative evaluation of pulmonary fibrosis and its severity, and develop application software; 4) excavate and verify important molecular targets for the formation of pulmonary fibrosis and identify biomarkers; 5) combined with clinical phenotype, imaging, pathology and biomarkers to establish f-ILD early recognition and progress model, intervention strategies, guidelines and consensus, and applicated nationwide.
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| Measure | Description | Time Frame |
|---|---|---|
| Clinical diagnostic protocol of ILD tissue biopsy | Report on the reliability and safety assessment of TBLC and SLB diagnostics. | 3 years |
| Predict model | The contents were based on the f-ILD cohort, combined with clinical, imaging, pathological, lung function and biomarker analysis, and constructed a multidimensional model for the early recognition and progression of f-ILD. | 3 years |
| Severity of fibrosis in HRCT assessed by AI system in patients with ILD | Explore the diversity of abnormal image performance in patients with f-ILD, and extract multidimensional information based on deep learning and other methods. Realize the intelligent quantitative analysis of the severity of fibrosis. | 3 years |
| F-ILD cohort | The researchers used inclusion/exclusion criteria for screening, and collected the demographic information, clinical symptoms and signs, laboratory tests, treatment, survival and other conditions of the patients who agreed to participate in the program and signed the informed consent, and collected biological specimens. | 6 years |
| Important molecular targets and biomarkers identified by multi-omics | Single cell map of lung tissue in the early stage of ILD, key molecular targets and biomarkers for the development and progression of pulmonary fibrosis. | 3 years |
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Inclusion Criteria:
Exclusion Criteria:
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Patients were selected during hospitalization from medical organization.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Huaping Dai, M.D. Ph.D. | Contact | 0086-10-84206271 | daihuaping@sina.com |
| Name | Affiliation | Role |
|---|---|---|
| Huaping Dai, M.D. Ph.D. | China-Japan Friendship Hospital | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| China-Japan Friendship Hospital | Recruiting | Beijing | Beijing Municipality | 100029 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 41198211 | Derived | Wang S, Zhang X, Xie B, Ren Y, Geng J, Luo S, He X, Jiang D, He J, Hu Y, Zhu L, Li J, Zhou G, Liu M, Zhao L, Dai H. Fibrotic Interstitial Lung Disease Early Recognition and Strategic Therapy Study in China (FIRST): protocol for a prospective, multicentre registry study. BMJ Open. 2025 Nov 5;15(11):e105980. doi: 10.1136/bmjopen-2025-105980. |
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| ID | Term |
|---|---|
| D017563 | Lung Diseases, Interstitial |
| ID | Term |
|---|---|
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
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| OTHER |
| Shanghai Chest Hospital | OTHER |
| Institute of Basic Medical Sciences CAMS | UNKNOWN |
| Tongji Hospital | OTHER |
| National Institute for Occupational Health and Poison Control | UNKNOWN |
| Infervision Medical Technology Company Limited | UNKNOWN |
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