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Construction and validation of machine learning models for identifying risk factors of postoperative pain in patients with osteogenesis imperfecta undergoing osteotomy correction: a retrospective study based on data from a single-center rare disease center

Construction and validation of machine learning models for identifying risk factors of postoperative pain in patients with osteogenesis imperfecta undergoing osteotomy correction: a retrospective study based on data from a single-center rare disease center

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500099072
Enrollment
Unknown
Registered
2025-03-18
Start date
2024-01-01
Completion date
Unknown
Last updated
2025-04-21

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

Conditions

post operation analgesia data

Interventions

Trial group:no

Sponsors

The University of Hongkong - Shenzhen Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
1 Years to 18 Years

Inclusion criteria

Inclusion criteria: 1.All children who underwent lower limb osteotomy for osteogenesis imperfecta and received postoperative epidural or caudal analgesia.

Exclusion criteria

Exclusion criteria: 1.Children with osteogenesis imperfecta undergoing minimally invasive procedures such as external fixation or plaster immobilization; patients who did not receive intrathecal catheter placement or whose intrathecal catheters were dislodged during the course of treatment, rendering intrathecal analgesia impossible; and children with incomplete or missing analgesic data.

Design outcomes

Primary

MeasureTime frame
pain related factors;Accuracy;Precision;Recall;—

Countries

China

Contacts

Public ContactMu Jingjing

The University of Hongkong - Shenzhen Hospital

mujj@hku-szh.org+86 755 86913333

Outcome results

None listed

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