Knee Osteoarthritis
Conditions
Keywords
Artificial Intelligence, Total Knee Arthroplasty, Biomechanics, Orthopaedic surgery, Alarmins, Oxidative Stress, Cytokine, Knee Inflammation, Knee Osteoarthritis
Brief summary
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.
Detailed description
Osteoarthritis is one of the most common causes of knee disorders, leading to pain, reduced mobility, and a decline in quality of life. Total knee arthroplasty (TKA) is one of the most established treatments for end-stage osteoarthritis. Despite advancements in surgical techniques, patient dissatisfaction remains high. After surgery, patients often experience swelling, pain, and difficulty with daily activities. Revision surgery is a major challenge, with aseptic loosening occurring in 15-20% of cases. Given the high disability rates and healthcare costs associated with TKA, optimizing patient care is crucial. Artificial intelligence (AI) offers the potential to identify new care profiles. For the first time, AI can integrate multimodal datasets. This approach could lead to personalized treatment for knee osteoarthritis patients, in line with precision medicine principles. This study takes a multidisciplinary approach to better understand the causes of failure and dissatisfaction following TKA. The primary aim of this study is is to create a multimodal database. This database will include structural, genetic, biomechanical, clinical, psychological, biological, stress-related, inflammatory, and demographic data. Using AI, the study aims to build predictive models for post-TKA outcomes. Insights from this research could improve patient management and lead to new therapeutic approaches. Patients suffering from knee osteoarthritis at Fondazione Policlinico Universitario Campus Bio-Medico will be enrolled in this study if they meet the inclusion/exclusion criteria described above. There are no risks for the patients recruited in the study. The total duration of the study is 5 years. The enrolment of patients will start on the 01/10/2024 and will last 12 months for each patient. The Italian Ministry of Health and the Fondazione Policlinico Universitario Campus Bio-Medico supported this study. The PI and also the main contact of this study is professor Umile Giuseppe Longo.
Interventions
PROCEDURETotal Knee Arthroplasty
Total Knee Arthroplasty is performed using conventional surgical techniques.
DIAGNOSTIC_TESTMultifaceted diagnostic assessments
Multifaceted diagnostic assessments involving genetic analysis, biomechanical data collection, radiographic imaging, and psychological evaluations.
BEHAVIORALFollow-ups
Postoperative follow-up includes behavioral interventions, such as lifestyle counseling and rehabilitation programs, tailored based on AI-driven insights into individual patient recovery profiles.
GENETICGenetic screening
Genetic screening and analysis, including whole exome sequencing, are conducted to identify genetic markers that might influence the outcomes of knee arthroplasty. This data is utilized within AI models to predict patient-specific surgical outcomes and recovery processes.
Sponsors
Fondazione Policlinico Universitario Campus Bio-Medico
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. Symptomatic, end-stage knee osteoarthritis 2. Ligaments functionally intact 3. Age: older than18 years old
Exclusion criteria
1. Neurological or other conditions affecting patients ability to join walking trials 2. Inflammatory or infectious arthritis 3. Previous articular fracture or knee surgery (excluding knee arthroscopy and meniscal surgery) 4. Active tumors or pregnancy.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change From Baseline in Knee Society Score (KSS) at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The KSS is a clinician-based assessment tool that evaluates both knee function and functional activities after knee replacement surgery. Minimum/Maximum Values: The KSS is divided into two parts: knee score and function score, with a combined score ranging from 0 to 100. Higher scores indicate a better outcome in terms of knee function and overall knee health. |
| Change From Baseline in Oxford Knee Score (OKS) at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The OKS is used to assess pain and function in individuals undergoing knee surgery or experiencing knee osteoarthritis, focusing on the patient\'s perspective. Minimum/Maximum Values: The OKS ranges from 0 to 48. Higher scores represent a better outcome, with less pain and better joint function. |
| Change From Baseline in Knee Injury and Osteoarthritis Outcome Score (KOOS) at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The KOOS is widely used to evaluate short- and long-term patient-reported outcomes following knee injury or surgery. Minimum/Maximum Values: The KOOS assesses five dimensions: pain, symptoms, function in daily living, function in sports/recreation, and knee-related quality of life. Each subscale ranges from 0 to 100. Higher scores reflect a better outcome, indicating fewer symptoms and better function. |
| Change From Baseline in Forgotten Joint Score Short Form (FJS-12) at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The FJS-12 measures how much a patient is aware of their joint in daily activities, particularly after joint replacement surgery, with higher scores reflecting greater joint integration. Minimum/Maximum Values: The FJS-12 ranges from 0 to 100. High scores indicate good outcomes |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Change From Baseline in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The WOMAC is commonly used to evaluate pain, stiffness, and physical function in patients with osteoarthritis, particularly in the knee and hip. Minimum/Maximum Values: The WOMAC ranges from 0 to 96. High scores indicate best functional status level |
| Change from baseline in knee range of motion (ROM) at 12 months | Before surgery (Baseline) and at 12 months postoperatively | Knee joint ROM (measured in degree) will be assessed during gait using a 3D motion capture system |
| Change from baseline in ground reaction forces at 12 months | Before surgery (Baseline) and at 12 months postoperatively | Ground reaction forces (measured in Newtons) during gait will be measured using force platforms synchronized with the 3D motion capture system |
| Change from baseline in center of pressure (CoP) at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The CoP (measured in meters) will be measured during gait using force platforms synchronized with the 3D motion capture system |
| Change from baseline in walking speed at 12 months | Before surgery (Baseline) and at 12 months postoperatively | Walking speed (measured in meters per seconds) will be extracted using force platforms synchronized with the 3D motion capture system |
| Change from baseline in cadence at 12 months | Before surgery (Baseline) and at 12 months postoperatively | Cadence (measured in steps per minute) will be assessed during gait using force platforms synchronized with the 3D motion capture system |
| Change from baseline in Step and Stride Length at 12 months | Before surgery (Baseline) and at 12 months postoperatively | Step and Stride length (measured in meters) will be evaluate during gait using force platforms synchronized with the 3D motion capture system |
| Change from baseline in osteoarthritis (OA) severity based on the Kellgren-Lawrence score at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The severity of OA will be assessed using the Kellgren-Lawrence global radiographic score. Changes in OA severity will be graded on a scale from 0 to 4, with 0 indicating no OA and 4 indicating severe OA |
| Change from baseline in joint alignment at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The changes in joint alignment (measured in degrees) will be evaluated using X-rays to determine any shifts in anatomical alignment post-surgery |
| Change from baseline in lateral distal femoral angle at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The lateral distal femoral angle (measured in degrees) will be measured using X-rays to assess the alignment of the femur |
| Change from baseline in medial proximal tibial angle at 12 months | Baseline (before surgery) and 12 months postoperatively | The medial proximal tibial angle will be measured to evaluate tibial alignment. X-rays will be used to assess changes in medial proximal tibial angle (measured in degrees) |
| Change from baseline in joint line convergence angle at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The joint line convergence angle (measured in degrees) will be measured using X-rays to evaluate the alignment of the knee joint |
| Change from baseline in tibial slope at 12 months | Before surgery (Baseline) and at 12 months postoperatively | The tibial slope (measured in degrees) will be assessed using X-rays to measure the posterior inclination of the tibial plateau |
| Change From Baseline in the fecal microbiota profiles at 12 months | Before surgery and at 12 months postoperatively | — |
Countries
Italy
Contacts
CONTACTUmile Giuseppe Longo, MD, MSc, PhD
Outcome results
None listed