An Artificial Intelligence-based Approach in Total Knee Arthroplasty: From Inflammatory Responses to Personalized Medicine

Goal: The goal of this interventional study is to understand how multimodal preoperative data can predict outcomes after Total Knee Arthroplasty (TKA) and improve personalized medicine practices. Participant Population: The study will enroll 197 patients suffering from symptomatic, end-stage knee osteoarthritis, who are above 18 years old and have functionally intact ligaments. Main Questions: * Can multimodal preoperative data, genetic predisposition, and psycho-behavioral characteristics predict outcomes after TKA? * Can AI models effectively use this data to customize prostheses and surgical interventions, and predict patient outcomes? Comparison Group Information (If applicable): Not specified in the provided details. Participant Tasks: * Undergo TKA as per the normal clinical routine. * Participate in pre- and post-surgical follow-ups including: * Clinical-functional assessments. * Administration of clinical scores. * Collection of biological samples. * Biomechanical analysis using a stereophotogrammetric system. * Provide data for the comprehensive multimodal indexed database.

NCT Number	NCT06634654
Lead Sponsor	Fondazione Policlinico Universitario Campus Bio-Medico
Conditions	Knee Osteoarthritis
Enrollment	197 participants
Start Date	2024-10-14
Primary Completion	2026-06 (estimated)
Study Completion	2029-12 (estimated)
Updated on ClinicalTrials.gov	2026-03-04