Multicenter Clinical Study on Robotic-Assisted Surgical Management of Posterior Cruciate Ligament Tibial Avulsion Fractures

Overview

The primary objective of this clinical trial is to evaluate the efficacy of robotic-assisted surgery in the management of posterior cruciate ligament (PCL) avulsion fractures involving the tibial insertion site of the cruciate ligament. Specifically, the study seeks to determine: (1) whether robotic-assisted surgery yields superior anatomical reduction accuracy-particularly in restoring the native position of the tibial avulsion fragment-compared with conventional open reduction and internal fixation (ORIF); and (2) whether such improved precision translates into enhanced long-term functional recovery of the knee joint.

Patients diagnosed with posterior cruciate ligament (PCL) tibial avulsion fractures-confirmed according to established radiographic and clinical diagnostic criteria-were prospectively enrolled from three geographically distinct regional medical centers. Prior to enrollment, all participants received comprehensive oral and written information detailing the study's objectives, methodology, potential risks and benefits, and the two comparative surgical interventions: robotic-assisted fixation and conventional open reduction and internal fixation (ORIF). Written informed consent was obtained from each participant following a mandatory reflection period and prior to randomization or any study-related procedures. All enrolled patients underwent standardized preoperative imaging, including anteroposterior and lateral radiographs of the knee, computed tomography (CT), and magnetic resonance imaging (MRI). Imaging interpretation was performed independently by two board-certified musculoskeletal radiologists blinded to group allocation; consensus adjudication resolved discrepancies. Radiological assessment confirmed diagnosis, classified fracture morphology using the Meyers-McKeever classification , and verified adherence to prespecified inclusion and exclusion criteria. Participants were then allocated in a 1:1 ratio to either the robotic-assisted surgery group (intervention group) or the ORIF group (control group) via centralized, stratified randomization-stratified by ageand fracture type . Baseline demographic, clinical, and functional assessments-including physical examination and validated patient-reported outcome measures (e.g., IKDC subjective score)-were completed preoperatively. All surgical procedures were performed by senior orthopedic surgeons with subspecialty expertise in knee trauma, either directly or under their immediate supervision, to ensure procedural fidelity and minimize interoperator variability. Primary and secondary outcomes were assessed at prespecified time points using objective, validated, and reproducible metrics. Radiographic evaluation of reduction accuracy entailed measurement of maximal sagittal displacement of the avulsed fragment on postoperative CT scans acquired within 72 ± 24 hours after surgery. The IKDC subjective score was collected at 24 weeks (±2 weeks) and 12 months (±1 month) postoperatively. Fracture union was determined radiologically using CT criteria and knee range of motion (ROM) was measured using a standard goniometer at 12 weeks (±1 week) and 24 weeks (±2 weeks). Intraoperative process metrics-including operative duration, intraoperative fluoroscopic exposure count, estimated blood loss (measured gravimetrically and volumetrically), and incidence of adverse events (e.g., surgical site infection, neurovascular injury, implant-related complications, or unplanned reoperation)-were systematically documented and compared between groups. Randomization was implemented using a computer-generated, permuted-block randomization sequence managed centrally and stratified as noted above. Statistical analyses adhered to a prespecified analysis plan: normality of continuous variables was assessed using the Shapiro-Wilk test; normally distributed data are presented as mean ± standard deviation and compared using independent-samples t-tests; non-normally distributed data are reported as median (interquartile range) and analyzed using the Mann-Whitney U test. Missing data were addressed via multiple imputation , followed by sensitivity analyses using complete-case and worst-case scenarios. Categorical variables are expressed as frequency (percentage) and compared using the chi-square test or Fisher's exact test, as appropriate.