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Machine learning-based predictive models for postoperative pulmonary pomplications undergoing laparoscopic hepatectomy

Machine learning-based predictive models for postoperative pulmonary pomplications undergoing laparoscopic hepatectomy

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500105449
Enrollment
Unknown
Registered
2025-07-03
Start date
2025-07-03
Completion date
Unknown
Last updated
2025-07-07

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

Conditions

postoperative pulmonary complications (PPCs) in laparoscopic hepatectomy

Interventions

PPCs group:None
Non-PPCs group.:None

Sponsors

Weifang People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.A total of 996 patients undergoing laparoscopic hepatectomy from November 2019 to June 2025 were retrospectively collected, 662 males and 334 females, aged >= 18 years, ASA physical status I-III.

Exclusion criteria

Exclusion criteria: 1.Preoperative severe cardiopulmonary disease; 2.preoperative pulmonary infection or imaging abnormalities; 3.preoperative coagulation dysfunction; 4.surgical approach being open laparotomy or conversion to open surgery; 5.without intraoperative portal triad clamping (Pringle maneuver);

Design outcomes

Primary

MeasureTime frame
Postoperative pulmonary complications (PPCs);—

Countries

China

Contacts

Public ContactYajuan Zhao

Weifang People's Hospital

785043167@qq.com+86 137 8082 4980

Outcome results

None listed

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