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Machine learning model for predicting postoperative pain risk in ambulatory laparoscopic cholecystectomy

Machine learning model for predicting postoperative pain risk in ambulatory laparoscopic cholecystectomy

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500106179
Enrollment
Unknown
Registered
2025-07-18
Start date
2025-07-20
Completion date
Unknown
Last updated
2025-07-21

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

Conditions

Postoperative pain

Interventions

Observation group:None

Sponsors

Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 75 Years

Inclusion criteria

Inclusion criteria: 1.Adult patients (aged 18-75 years) undergoing laparoscopic cholecystectomy in ambulatory surgery units 2.With complete baseline data, intraoperative anesthesia records, and postoperative follow-up data

Exclusion criteria

Exclusion criteria: Patients with unplanned termination of the clinical pathway for ambulatory surgery or transfer out of the ambulatory surgery unit

Design outcomes

Primary

MeasureTime frame
Numeric Rating Scale (NRS) pain score;—

Countries

China

Contacts

Public ContactFan Dan

Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital

369392862@qq.com+86 177 0813 0205

Outcome results

None listed

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