Does Robotic Assistance In Total Knee Arthroplasty Improve Preoperative Planning And Intraoperative Decision-Making?

Does Robotic Assistance In Total Knee Arthroplasty Improve Preoperative Planning And Intraoperative Decision-Making?

David H. Figueroa, MD, CHILE Waldo Gonzalez Duque, MD, CHILE Rafael Calvo, MD, CHILE Francisco Figueroa, MD, CHILE

Clinica Alemana Santiago, Santiago, CHILE


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Anatomic Location

Anatomic Structure

Diagnosis / Condition

Patient Populations


Summary: The RA-TKA system that utilizes planning with 3D CT images provides a prediction that is more accurate for femoral implants, in contrast with the lower accuracy shown for tibia implants and poly insert sizes


Introduction

The use of appropriately sized implants is critical for achieving
satisfactory outcomes in total knee arthroplasty (TKA). It has been reported that
Robot-assisted TKA (RA-TKA) could achieved a high level of accuracy in
predicting implant sizes.

Objective

To evaluate the concordance between preoperative planning in the size
of implants and its effect on intra operative decision making

Materials And Methods

A retrospective cohort study based on the analysis of 71
patients undergoing RA-TKA at our center, where preoperative imaging based on
CT is used. Concordance was evaluated using Cohen's Kappa test for femoral,
tibial components, and polyethylene inserts. Stratified analysis by sex on the
success, overestimation, and underestimation of implants was performed using
logistic regressions adjusted for age and BMI. Statistical analysis was conducted
using STATA v.18.0.

Results

A total of 71 prostheses were evaluated. 54.9% of the patients were
female, with an average age of 68.7±8.6 years and an average BMI of 29.03±4.40
kg/m². 50.7% of the patients had concordance between predicted and implanted
sizes for femoral, tibial, and insert components together. No significant differences
were found by sex, even after adjusting for age and BMI. Regarding the femoral
component, 94.3% (67/71) of the predicted implants matched the ones placed. The
concordance was almost perfect (k=0.90; p<0.001). In contrast, only 71.8% (51/71)
of the predicted tibial implants matched those placed. The concordance between
predicted and placed was substantial (k=0.66; p<0.001). For the inserts, only
74.6% (53/71) matched the ones placed. The concordance between predicted and
placed was slight (k=0.04; p=0.17). In the analysis stratified by sex, significant
differences were evident in the success of predicting placed implants (59.4% in
men vs. 82.1% in women, p=0.03).

Conclusions

The RA-TKA system that utilizes planning with 3D CT images
provides a prediction that is more accurate for femoral implants, in contrast with the
lower accuracy shown for tibia implants and poly insert sizes.