Development of Algorithm for Diagnosis and Treatment of Periprosthetic Joint Infection (PJI) by Using Artificial Intelligence (AI)

Development of Algorithm for Diagnosis and Treatment of Periprosthetic Joint Infection (PJI) by Using Artificial Intelligence (AI) - Development of Algorithm for PJI by Using AI

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000030180

Enrollment

160

Registered

2017-12-01

Start date

2017-12-01

Completion date

Unknown

Last updated

2026-06-29

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

Conditions

Periprosthetic Joint Infection

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Patients who meet the following criterions 1) and 2): 1) irrespective of age or gender; 2) underwent either (A) or (B) at Yokohama City University Hospital during the period between January 2007 and September 2016: (A) underwent total arthroplasty (hip or knee) or debridement with implant retaining for the case of suspected aseptic loosening or PJI; (B) underwent total arthroplasty for the first time and neither aseptic loosening nor PJI was suspected.

Exclusion criteria

Exclusion criteria: Exclude patients who fall into any of the following conditions: 1) patients with sepsis and septic shock that could become life-threatening; 2) patients who are disqualified as sample for this research by principal and co-investigator.

Design outcomes

Primary

Measure	Time frame
Apply machine learning to analyze the statistics by using the following data: 1) Clinical findings and clinical test results of pre- and post-operative 3, 6 and 12 months; 2) Pre- and intra-operative stage of periarthritis determined by the results of clinical findings, synovial fluid test, histopathologic examination and operative data; 3) Post-operative data; 4) Pre- and post- operative Imaging test results.	—

Measure

Time frame

Apply machine learning to analyze the statistics by using the following data: 1) Clinical findings and clinical test results of pre- and post-operative 3, 6 and 12 months; 2) Pre- and intra-operative stage of periarthritis determined by the results of clinical findings, synovial fluid test, histopathologic examination and operative data; 3) Post-operative data; 4) Pre- and post- operative Imaging test results.

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Countries

Japan

Contacts

Public ContactYutaka Inaba

Yokohama City University Hospital Department of Orthopaedic Surgery

yute0131@med.yokohama-cu.ac.jp045-787-2800

Outcome results