Overview
The goal of this clinical trial is to learn if imageless navigation is not inferior to image-based navigation in robotic-assisted total knee arthroplasty (RA-TKA) for treating patients with knee osteoarthritis.
The main questions the study aims to answer are:
- Does imageless procedure provide functional results comparable to those of image-based navigation?
- Are there differences in postoperative complications patients may experience after RA-TKA with imageless and image-based navigation? Researchers will compare imageless navigation with image-based navigation used in total knee arthroplasty to assess whether imageless navigation is comparable for the treatment of knee osteoarthritis.
Participants will:
- Answer survey questions about knee pain and function before RA-TKA.
- Undergo RA-TKA with imageless navigation or image-based navigation.
- Visit the Clinic after 6 months and 12 months after surgery for checkups and to answer the same survey questions about postoperative knee pain and function.
Description
The trial will include patients with end-stage osteoarthritis, qualified for Robotic-Assisted Total Knee Arthroplasty (RA-TKA). For each patient, a full-length standing radiograph will be taken with designated sensors. Based on these, a three-dimensional model of the knee joint will be generated, enabling preoperative planning and intraoperative navigation in the image-based mode. Patients who meet the criteria and provide informed consent will be included in the study. Immediately before surgery, patients will be randomly assigned by a computer programme to either the experimental or control group in a 1:1 ratio, remaining blinded to the chosen method. In the experimental group, RA-TKA will be performed using imageless navigation, whereas in the control group, it will be performed using image-based navigation. In both groups, the procedure will be performed by experienced specialists with several years of experience, according to a standardized protocol: a medial parapatellar approach with restricted kinematic alignment, using a medial congruent knee implant.
The total number of patients included in the study is planned to be 146, with 73 in the experimental group and 73 in the control group. The group size was calculated based on a power analysis; power level: 80%, significance level: α=0.05, minimal clinically important difference: 5 points on the Oxford Knee Score (OKS), standard deviation: 10 points on the OKS. The study's dropout rate is estimated at 15%.
Radiologic imaging, survey responses, and intraoperative records will be stored on physical disks and paper, as well as in a secure cloud-based database. All other records will be stored digitally only. Registry data will be compared with external data sources (medical records) every 6 months to assess their accuracy and completeness. A Linear Mixed-Effects Model will be used to account for correlation between OKS measurements in the same patient. Both Per-Protocol and Intention-to-Treat analyses will be reported. For comparing continuous variables, a t-test (if normally distributed) or a Mann-Whitney U test (if skewed) will be used. Categorical variables will be compared with Fisher's Exact Test or the Chi-squared test. A cost-minimization analysis will be conducted using economic data.
Eligibility
Inclusion Criteria:
- Symptomatic, radiologically confirmed advanced osteoarthritis of the knee.
- Patients referred for primary robotic-assisted total knee arthroplasty.
- Patients in whom a correctly performed radiograph with designated sensors has confirmed the possibility of performing robotic-assisted total knee arthroplasty with image-based navigation.
- Patients capable of giving informed consent to participate in the study and willing to attend all follow-up visits.
Exclusion Criteria:
- No informed consent for the surgery.
- No informed consent for taking part in the study.
- Pregnancy.
- Active infections.
- Diagnosed comorbidities: autoimmune arthritis, malignant tumors, serious neurological disorders affecting a reliable functional outcome measurement (e.g., severe stroke, severe Parkinson's disease).
