Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
The key technology research and standard evaluation system of elderly heart valve disease evaluation is to further establish a domestic multi center and large sample full information big data platform of elderly heart valve disease based on the previous Chinese elderly valve disease cohort and clinical research platform and the national valve disease surgery data platform.
Establish clinical and Imaging Database
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| imaging | Diagnostic Test | (1) Build the first full information big data cloud platform for diagnosis, treatment and clinical research of senile valvular disease in China (2) To establish a cohort of elderly patients with valvular disease in China and a complete database covering clinical information, functional, imaging evaluation, treatment and follow-up; (3) To analyze the clinical characteristics, functional status and imaging characteristics of senile valvular disease in China, and to understand the current situation of diagnosis and treatment; To establish a whole process standardized comprehensive evaluation system of clinical indicators of senile valvular disease combined with a variety of imaging for Chinese people. |
| Measure | Description | Time Frame |
|---|---|---|
| all-cause mortality | all-cause mortality | Time Frame: 2years |
Not provided
Not provided
Inclusion Criteria:
Patients with heart valve disease who are ≥ 65 years old and diagnosed by echocardiography meet the requirements
One of the following criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Inpatients in each research center
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| haiyan xu, doctor | Contact | +86 13681012249 | xuhaiyan@fuwaihospital.org |
| Name | Affiliation | Role |
|---|---|---|
| yongjian wu, doctor | Fuwai Hospital, National Center for Cardiovascular Diseases,Chinese Academy of Medical Sciences | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Fuwai Hospital, National Center for Cardiovascular Diseases,Chinese Academy of Medical Sciences | Recruiting | Beijing | Beijing Municipality | 100037 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 41558358 | Derived | Mao Y, Liu Y, Zhai M, Jin P, Chen F, Zhang G, Wei L, Liu J, Guo Y, Wu Y, Yang J. Predictors of Paravalvular Leakage After Transcatheter Aortic Valve Replacement in Patients With BAV: A Machine Learning Model. JACC Adv. 2026 Feb;5(2):102566. doi: 10.1016/j.jacadv.2025.102566. Epub 2026 Jan 20. | |
| 41491442 | Derived |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D006349 | Heart Valve Diseases |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
Not provided
Not provided
| ID | Term |
|---|---|
| D003952 | Diagnostic Imaging |
| ID | Term |
|---|---|
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
Not provided
Not provided
Not provided
Not provided
Not provided
| Mao Y, Liu Y, Zhai M, Jin P, Li W, Chen F, Yang Y, Zhang G, Liu J, Guo Y, Pan X, Wu Y, Yang J. Clinical significance of machine learning algorithm in predicting PPM during TAVR in small annuli. Cardiovasc Interv Ther. 2026 Apr;41(2):402-413. doi: 10.1007/s12928-025-01215-5. Epub 2026 Jan 5. |
| 41445779 | Derived | Mao Y, Liu Y, Zhai M, Jin P, Li W, Dong X, Chen F, Wang X, Wang Y, Zhang G, Li H, Yang Y, Zhang H, Liu J, Guo Y, Wu Y, Xue Y, Zhang J, Frangi A, Yang J. Precision TAVR quantification- AI-accelerated TAVR planning reduces assessment time by 80% in bicuspid aortic stenosis. Eur Heart J Imaging Methods Pract. 2025 Dec 5;3(4):qyaf153. doi: 10.1093/ehjimp/qyaf153. eCollection 2025 Oct. |