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Establishment and application of a predictive model for periprosthetic infection after artificial joint replacement surgery based on machine learning algorithm

Establishment and application of a predictive model for periprosthetic infection after artificial joint replacement surgery based on machine learning algorithm

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500096282
Enrollment
Unknown
Registered
2025-01-21
Start date
2025-02-15
Completion date
Unknown
Last updated
2025-01-27

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

Conditions

Periprosthetic Joint Infection

Interventions

Infection group:Periprosthetic Joint Infection
Non infectious group:Periprosthetic Joint Infection

Sponsors

The Third Affiliated Hospital of Guangzhou University of Chinese Medicine
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: (1) Patients after primary joint replacement; (2) For patients with postoperative periprosthetic infection, the diagnosis of periprosthetic infection meets the definition; (3) Patients who did not have periprosthetic infection after surgery; (4) The diagnostic criteria for periprosthetic infection are the diagnostic criteria for periprosthetic infection recommended by the International Consensus Working Group on Periprosthetic Infection.

Exclusion criteria

Exclusion criteria: 1. Age< 18 years old; 2. Patients with malignant tumors, organ failure and other end-stage diseases.

Design outcomes

Primary

MeasureTime frame
Periprosthetic Joint Infection;—

Countries

China

Contacts

Public ContactLiang Hongbiao

The Third Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine

497071196@qq.com+86 20 22292718

Outcome results

None listed

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