Aims. The Coronal Plane Alignment of the Knee (CPAK) classification has been developed to predict individual variations in inherent knee alignment. The impact of preoperative and postoperative CPAK classification phenotype on the postoperative clinical outcomes of total knee arthroplasty (TKA) remains elusive. This study aimed to examine the effect of postoperative CPAK classification phenotypes (I to IX), and their pre- to postoperative changes on patient-reported outcome measures (PROMs). Methods. A questionnaire was administered to 340 patients (422 knees) who underwent primary TKA for osteoarthritis (OA) between September 2013 and June 2019. A total of 231 patients (284 knees) responded. The Knee Society Score 2011 (KSS 2011), Knee injury and Osteoarthritis Outcome Score-12 (KOOS-12), and Forgotten Joint Score-12 (FJS-12) were used to assess clinical outcomes. Using preoperative and postoperative anteroposterior full-leg radiographs, the arithmetic hip-knee-ankle angle (aHKA) and
Aims. A comprehensive classification for coronal lower limb alignment with predictive capabilities for knee balance would be beneficial in total knee arthroplasty (TKA). This paper describes the Coronal Plane Alignment of the Knee (CPAK) classification and examines its utility in preoperative soft tissue balance prediction, comparing kinematic alignment (KA) to mechanical alignment (MA). Methods. A radiological analysis of 500 healthy and 500 osteoarthritic (OA) knees was used to assess the applicability of the CPAK classification. CPAK comprises nine phenotypes based on the arithmetic HKA (aHKA) that estimates constitutional limb alignment and
Aims. The aim of this study was to compare robotic arm-assisted bi-unicompartmental knee arthroplasty (bi-UKA) with conventional mechanically aligned total knee arthroplasty (TKA) in order to determine the changes in the anatomy of the knee and alignment of the lower limb following surgery. Methods. An analysis of 38 patients who underwent TKA and 32 who underwent bi-UKA was performed as a secondary study from a prospective, single-centre, randomized controlled trial. CT imaging was used to measure coronal, sagittal, and axial alignment of the knee preoperatively and at three months postoperatively to determine changes in anatomy that had occurred as a result of the surgery. The hip-knee-ankle angle (HKAA) was also measured to identify any differences between the two groups. Results. The pre- to postoperative changes in joint anatomy were significantly less in patients undergoing bi-UKA in all three planes in both the femur and tibia, except for femoral sagittal component orientation in which there was no difference. Overall, for the six parameters of alignment (three femoral and three tibial), 47% of bi-UKAs and 24% TKAs had a change of < 2° (p = 0.045). The change in HKAA towards neutral in varus and valgus knees was significantly less in patients undergoing bi-UKA compared with those undergoing TKA (p < 0.001). Alignment was neutral in those undergoing TKA (mean 179.5° (SD 3.2°)) while those undergoing bi-UKA had mild residual varus or valgus alignment (mean 177.8° (SD 3.4°)) (p < 0.001). Conclusion. Robotic-assisted, cruciate-sparing bi-UKA maintains the natural anatomy of the knee in the coronal, sagittal, and axial planes better, and may therefore preserve normal joint kinematics, compared with a mechanically aligned TKA. This includes preservation of coronal
The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee’s functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population. We used an active appearance model-based approach to segment the preoperative CT of 21 osteoarthritic patients, which identified the osteophyte-free surfaces and estimated cartilage from the segmented bones; these geometries were used to construct patient-specific musculoskeletal models of the pre-diseased knee. Subsequently, implantations were simulated using the MA method, and a previously developed optimization technique was employed to find the optimal implant position that minimized the root mean square deviation between pre-diseased and postoperative ligament strains and kinematics.Aims
Methods
Many aspects of total knee arthroplasty have
changed since its inception. Modern prosthetic design, better fixation techniques,
improved polyethylene wear characteristics and rehabilitation, have
all contributed to a large change in revision rates. Arthroplasty
patients now expect longevity of their prostheses and demand functional
improvement to match. This has led to a re-examination of the long-held
belief that mechanical alignment is instrumental to a successful
outcome and a focus on restoring healthy joint kinematics. A combination
of kinematic restoration and uncemented, adaptable fixation may
hold the key to future advances. Cite this article: