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Machine learning model predicts airway stenosis requiring clinical intervention in patients after lung transplantation

Machine learning model predicts airway stenosis requiring clinical intervention in patients after lung transplantation

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300072830
Enrollment
Unknown
Registered
2023-06-26
Start date
2022-02-02
Completion date
Unknown
Last updated
2023-10-09

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

Conditions

Lung transplantation

Interventions

Airway stenosis group:Not applicable
Non-airway stenosis group:Not applicable

Sponsors

Wuxi Lung Transplant Center, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China
Lead Sponsor

Eligibility

Sex/Gender
All
Age
19 Years to 82 Years

Inclusion criteria

Inclusion criteria: Patients who underwent lung transplantation were included.

Exclusion criteria

Exclusion criteria: 1. The study excluded retransplant patients; 2. Pediatric lung transplant patients; 3. Patients who were lost to follow-up; 4. Patients with incomplete clinical records.

Design outcomes

Primary

MeasureTime frame
Airway stenosis;—

Countries

China

Contacts

Public ContactJing-Yu Chen

Wuxi Lung Transplant Center, Wuxi People's Hospital Affiliated to Nanjing Medical University

chenjy@wuxiph.com+86 133 5811 9213

Outcome results

None listed

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