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Optimization of PTE-CTEPH diagnosis and treatment strategy based on artificial intelligence technology

Optimization of PTE-CTEPH diagnosis and treatment strategy based on artificial intelligence technology

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400088972
Enrollment
Unknown
Registered
2024-08-29
Start date
2022-11-02
Completion date
Unknown
Last updated
2024-09-02

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

Conditions

chronic thromboembolic pulmonary hypertension,CTEPH

Interventions

Gold Standard:Artificially diagnosed imaging report results by human doctor
Index test:PTE-CTEPH diagnosis, risk stratification, and prognosis assessment model based on artificial intelligence technology and imaging omics.

Sponsors

Shanghai Eas Hospital (Tongji University Affiliated East Hospital)
Lead Sponsor

Eligibility

Sex/Gender
All
Age
13 Years to 100 Years

Inclusion criteria

Inclusion criteria: 1. Through V/Q imaging or Q-SPECT-CT imaging, as well as RHC examination, the diagnosis of CTEPH is confirmed. 2. The clinical and imaging data are complete. 3. Signed informed consent form.

Exclusion criteria

Exclusion criteria: 1. Age less than 13 years old; 2. Patients with combined other types of pulmonary arterial hypertension; 3. Clinical and imaging data are incomplete or of poor quality.

Design outcomes

Primary

MeasureTime frame
(Accuracy&Precision);

Secondary

MeasureTime frame
Sensitivity, specificity, F1 score.;AUC (Area Under Curve);

Countries

China

Contacts

Public ContactJi Yingqun

Shanghai East Hospital

jiyingqun@163.com+86 156 1865 4095

Outcome results

None listed

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