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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Image-based robotic-assisted total knee arthroplasty (RA-TKA) allows three-dimensional surgical planning informed by osseous anatomy, with intraoperative adjustment based on a dynamic assessment of ligament laxity and gap balance. The aim of this study was to identify ranges of implant alignment and bone resections with RA-TKA. We retrospectively reviewed 484 primary RA-TKA cases, stratified by preoperative coronal alignment. Demographics and intraoperative data were collected and compared using Chi-square and ANOVA tests. Planned limb, femoral, and tibial alignment became increasingly varus in a progressive order from valgus to neutral to the highest in varus knees (p < 0.001). Planned external transverse rotation relative to the TEA was lowest in the valgus cohort; relative to the PCA, whereas the varus cohort was highest (p < 0.001, both). Planned resections of the lateral distal femur and of the medial posterior femur were greater in the varus group compared to neutral and valgus (p < 0.001). There were significant differences between cohorts in planned tibia resections, laterally and medially. Varus knees demonstrated higher variability, while valgus and neutral had more metrics with low variability. This study demonstrated trends in intraoperative planned alignment and resection metrics across various preoperative coronal knee alignments. These findings contribute to the understanding of RA-TKA and may inform surgical decision-making.

Details

Title
Variability in Alignment and Bone Resections in Robotically Balanced Total Knee Arthroplasties
Author
Hepinstall, Matthew S; Catherine Di Gangi; Oakley, Christian; Sybert, Michael; Meere, Patrick A; Meftah, Morteza
First page
845
Publication year
2024
Publication date
2024
Publisher
MDPI AG
e-ISSN
23065354
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3097834348
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.