Early Discrimination of Periprosthetic Hip Infections Using Neural Networks (SEPTIC-ANNR)
NCT04119804 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 36
Last updated 2024-10-28
Summary
The study is about the role of cellular neural networks-genetic algorithm in the diagnosis of periprosthetic hip infections. A retrospective case series of septic and aseptic loosening of primary hip arthroplasties is selected. The diagnosis of septic loosening is made according to well-established criteria (CDC 2014 and culture samples). The serial radiographs of the selected patients are processed using cellular neural networks-genetic algorithm. The purpose of this study is to evaluate whether neural networks (cellular neural networks-genetic algorithm), applied to conventional radiographies, are accurate, sensitive and specific for the early-discrimination of a periprosthetic hip infection, already diagnosed with well-recognized methods (CDC 2014).
Conditions
- Hip Prosthesis Infection
Interventions
- DIAGNOSTIC_TEST
-
cellular neural networks-genetic algorithm
Cellular neural networks-genetic algorithm applied to conventional radiographs of hip implants with a well-established diagnosis of loosening. The study is not intended to use a software without a CE mark as a medical device, or to use the software as a tool to diagnose or prevent human disease, according to Directive 93/42 / European Economic Community. The study will evaluate if the software, properly calibrated, is able to recognize with adequate accuracy infections already diagnosed with validated methods.
Sponsors & Collaborators
-
Università degli studi di Messina
collaborator UNKNOWN -
Istituto Ortopedico Rizzoli
lead OTHER
Principal Investigators
-
Francesco Traina, PhD · IRCCS Istituto Ortopedico Rizzoli
Eligibility
- Min Age
- 18 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2019-10-03
- Primary Completion
- 2024-01-20
- Completion
- 2024-01-20
Countries
- Italy
Study Locations
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