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NCT Number: NCT06634654

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.

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Key information

Conditions

Knee Osteoarthritis Arthritis Joint Diseases Musculoskeletal Diseases Osteoarthritis Osteoarthritis, Knee Rheumatic Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Fondazione Policlinico Universitario Campus Bio-Medico

Rome, Italy, 00128

Location status: Recruiting

Location contact

Umile Giuseppe Longo, MD, MSc, PhD

PRINCIPAL_INVESTIGATOR

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Symptomatic, end-stage knee osteoarthritis
  • Ligaments functionally intact
  • Age: older than18 years old

Exclusion criteria

  • Neurological or other conditions affecting patients ability to join walking trials
  • Inflammatory or infectious arthritis
  • Previous articular fracture or knee surgery (excluding knee arthroscopy and meniscal surgery)
  • Active tumors or pregnancy.

Treatment and study plan

Total knee arthroplasty

Procedure

Total Knee Arthroplasty is performed using conventional surgical techniques.

Multifaceted diagnostic assessments

Diagnostic Test

Multifaceted diagnostic assessments involving genetic analysis, biomechanical data collection, radiographic imaging, and psychological evaluations.

Follow-ups

Behavioral

Postoperative follow-up includes behavioral interventions, such as lifestyle counseling and rehabilitation programs, tailored based on AI-driven insights into individual patient recovery profiles.

Genetic Screening

Genetic

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.

Primary outcomes

  1. Change From Baseline in Knee Society Score (KSS) at 12 months

    Time frame: 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.

  2. Change From Baseline in Oxford Knee Score (OKS) at 12 months

    Time frame: 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.

  3. Change From Baseline in Knee Injury and Osteoarthritis Outcome Score (KOOS) at 12 months

    Time frame: 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.

  4. Change From Baseline in Forgotten Joint Score Short Form (FJS-12) at 12 months

    Time frame: 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 outcomes

  1. Change From Baseline in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) at 12 months

    Time frame: 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

  2. Change from baseline in knee range of motion (ROM) at 12 months

    Time frame: 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

  3. Change from baseline in ground reaction forces at 12 months

    Time frame: 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

  4. Change from baseline in center of pressure (CoP) at 12 months

    Time frame: 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

  5. Change from baseline in walking speed at 12 months

    Time frame: 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

  6. Change from baseline in cadence at 12 months

    Time frame: 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

  7. Change from baseline in Step and Stride Length at 12 months

    Time frame: 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

  8. Change from baseline in osteoarthritis (OA) severity based on the Kellgren-Lawrence score at 12 months

    Time frame: 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

  9. Change from baseline in joint alignment at 12 months

    Time frame: 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

  10. Change from baseline in lateral distal femoral angle at 12 months

    Time frame: 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

  11. Change from baseline in medial proximal tibial angle at 12 months

    Time frame: 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)

  12. Change from baseline in joint line convergence angle at 12 months

    Time frame: 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

  13. Change from baseline in tibial slope at 12 months

    Time frame: 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

  14. Change From Baseline in the fecal microbiota profiles at 12 months

    Time frame: Before surgery and at 12 months postoperatively

Study contacts

Contact information is provided by the study sponsor or research team.

Umile Giuseppe Longo, MD, MSc, PhD

CONTACT

[email protected]

+39 06225418816

Sponsors and collaborators

Lead sponsor

Fondazione Policlinico Universitario Campus Bio-Medico

Other

Registry information

Acronym: AI-TKA

Important dates

Study start
2024
Primary completion
2026
Study completion
2029
First posted
Oct 10, 2024
Registry last updated
Mar 4, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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