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Establishment and validation of prediction model of pulmonary complications after thoracic surgery based on deep learning

Establishment and validation of prediction model of pulmonary complications after thoracic surgery based on deep learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200062180
Enrollment
Unknown
Registered
2022-07-27
Start date
2022-07-27
Completion date
Unknown
Last updated
2023-04-03

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

Conditions

Postoperative pulmonary complications

Interventions

NA:None

Sponsors

Peking Union Medical College Hospital, Chinese Academy of Medical Sciences
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1.Age = 18 2.The main diagnosis was lung cancer, lung mass, lung nodule or lung shadow

Exclusion criteria

Exclusion criteria: 1.Patients who change the operation mode during operation; 2.Postoperative chest X-ray examination was missing; 3.Based on the existing medical records, it is impossible to judge whether the patient has postoperative pulmonary complications;

Design outcomes

Primary

MeasureTime frame
Postoperative pulmonary complications;—

Secondary

MeasureTime frame
Length of stay;Total cost during hospitalization;ICU occupancy;—

Countries

China

Contacts

Public ContactJiali Tang

Peking Union Medical College Hospital, Chinese Academy of Medical Sciences

tangjiali@pumch.cn18500252430

Outcome results

None listed

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