Preoperative ligament laxity can be characterized intraoperatively using digital robotic tensioners. Understanding how preoperative knee joint laxity affects preoperative and early post-operative patient reported outcomes (PROMs) may aid surgeons in tailoring intra-operative balance and laxity to optimize outcomes for specific patients. This study aims to determine if preoperative ligament laxity is associated with PROMs, and if laxity thresholds impact PROMs during early post-operative recovery. 106 patients were retrospectively reviewed. BMI was 31±7kg/m2. Mean age was 67±8 years. 69% were female. Medial and lateral knee joint laxity was measured intraoperatively using a digital robotic ligament tensioning device after a preliminary tibial resection. Linear regressions between laxity and KOOS12-function were performed in extension (10°), midflexion (45°), and flexion (90°) at preoperative, 6-week, and 3-month time points. Patients were separated into two laxity groups: ≥7 mm laxity and <7 mm laxity. Student's Correlations were found between preoperative KOOS12-function and medial laxity in midflexion (p<0.001) and flexion (p<0.01). Patients with <7 mm of medial laxity had greater preoperative KOOS12-function scores compared to patients with ≥7 mm of medial laxity in extension (46.8±18.2 vs. 29.5±15.6, p<0.05), midflexion (48.4±17.8 vs. 32±16.1, p<0.001), and flexion (47.7±18.3 vs. 32.6±14.7, p<0.01). No differences in KOOS12-function scores were observed between medial laxity groups at 6-weeks or 3-months. All knees had <5 mm of medial laxity postoperatively. No correlations were found between lateral laxity and KOOS12-function. Patients with preoperative medial laxity ≥7 mm had lower preoperative PROMs scores compared to patients with <7 mm of medial laxity. No differences in PROMs were observed between laxity groups at 6 weeks or 3 months. Patients with excessive preoperative joint laxity achieve similar PROMs scores to those without excessive laxity after undergoing gap balancing TKA.
Passive smartphone-based apps are becoming more common for measuring patient progress after total knee arthroplasty (TKA). Optimum activity levels during early TKA recovery haven't been well documented. This study investigated correlations between step-count and patient reported outcome measures (PROMs) and how demographics impact step-count preoperatively and during early post-operative recovery. Smartphone capture step-count data from 357 TKA patients was retrospectively reviewed. Mean age was 68±8years. 61% were female. Mean BMI was 31±6kg/m2. Mean daily step count was calculated over three time-windows: 60 days prior to surgery (preop), 5-6 weeks postop (6wk), and 11-12 weeks postop (12wk). Linear correlations between step-count and KOOS12-function and UCLA activity scores were performed. Patients were separated into three step-count levels: low (<1500steps/day), medium (1500-4000steps/day), and high (>4000steps/day). Age >65years, BMI >30kg/m2, and sex were used for demographic comparisons. Student's t-tests determined significant differences in mean step-counts between demographic groups, and in mean PROMs between step-count groups. UCLA correlated with step-count at all time-windows (p<0.01). KOOS12-Function correlated with step-count at 6wk and 12wk (p<0.05). High step-count individuals had improved PROMs compared to low step-count individuals preoperatively (UCLA: ∆1.4 [p<0.001], KOOS12-Function: ∆7.3 [p<0.05]), at 6wk (UCLA: ∆1 [p<0.01], KOOS12-Function: ∆7 [p<0.05]), and at 12wk (UCLA: ∆0.8 [p<0.05], KOOS12-Function: ∆6.5 [p<0.05]). Younger patients had greater step-count preoperatively (3.8±3.0k vs. 2.5±2.3k, p<0.01), at 6wk (3.1±2.9k vs. 2.2±2.3k, p<0.05) and at 12wk (3.9±2.6k vs. 2.8±2.6k, p<0.01). Males had greater step-count preoperatively (3.7±2.6k vs. 2.5±2.6k, p<0.001), at 6wk (3.6±2.6k vs. 1.9±2.4k, p<0.001), and at 12wk (3.9±2.3 vs. 2.8±2.8k, p<0.01). No differences in step-count were observed between low and high BMI patients at any timepoint. High step count led to improved PROMs scores compared to low step-count. Early post-operative step-count was significantly impacted by age and sex. Generic recovery profiles may not be appropriate across a diverse population.
Joint kinematics following total knee replacement (TKR) is important as it affects joint loading, joint functionality, implant wear and ultimately patient comfort and satisfaction. It is believed that restoring the natural motion of the joint (such as the screw-home mechanism) with a medial pivot knee implant will improve clinical outcomes. Daily activities such as stair climbing and stair descent are among the most difficult tasks for these patients. This study analysed dynamic knee joint motion after implantation of a medial pivot knee implant using fluoroscopy during stair ascent and descent activity. Ethics approval was granted by Macquarie University to undertake fluoroscopic testing. Four patients who had undergone a TKR were asked to participate in the study. All patients were operated by a single surgeon (JS) and were implanted with a medial pivot knee prosthesis (Sphere, Medacta International). Participants were tested at the 12 month post-operative time- point. Participants were asked to step up or down a short stair-case at a comfortable self-selected speed. Fluroscopic images were taken using a flat panel Artis Zeego (Siemens Healthcare GmbH, Erlangen) angiography system during the dynamic activity. Images were processed using Joint Track Auto (Banks, University of Florida), whereby the specific femoral and tibial component CAD files were superimposed onto the fluoroscopic images, ensuring an optimised match to the outlined components. Joint kinematics were calculated using custom written code in Matlab 2017a.Introduction
Methods
The advantages of unicompartmental knee arthroplasty (UKA) include its bone preserving nature, lower relative cost and superior functional results. Some temporary pain has been reported clinically following this procedure. Could this be related to bone remodeling? A validated bone remodeling algorithm may have the answers… A 3D geometry of an intact human cadaveric tibia was generated using CT images. An all poly unicompartmental implant geometry was positioned in an inlay and onlay configuration on the tibia and the post-operative models created. An adaptive bone remodeling algorithm was used with finite element modeling to predict the bone remodeling behavior surrounding the implant in both scenarios. Virtual DEXA images were generated from the model and bone mineral density (BMD) was measured in regions of interest in the AP and ML planes. BMD results were compared to clinical results. The bone remodelling algorithm predicted BMD growth in the proximal anterior regions of the tibia, with an inward tendency for both inlay and onlay models. Looking in the AP plane, a maximum of up to 7% BMD growth was predicted and in the ML plane this was as high as 16%. Minimal BMD loss was observed, which suggests minimal disturbance to the natural bone growth following UKA. Positron emission tomography (PET) scans showed active hot spots in the antero- medial regions of the tibia. These results were consistent with the finite element modeling results. Bone remodeling behavior was found to be sensitive to sizing and positioning of the implant. The adaptive bone remodeling algorithm predicted minimal BMD loss and some BMD growth in the anterior region of the tibia following UKA. This is consistent with patient complaint and PET scans.
Femoral bone preservation is an important consideration in total hip replacement for those patients expected to outlive the success of their primary procedure. A clinical study was initiated to assess the performance of a new, ultra-short, cementless femoral implant that is sited in the region of the femoral neck. This two-centre study, conducted in Australia and Germany, was approved by the ethics committees and regulatory authorities in both countries. Patients aged between 25 and 65 with non-inflammatory arthritis were included subject to review against the detailed study selection criteria and the provision of written informed consent. Patients were assessed pre-operatively using the Harris Hip Score and Oxford Hip Score. These scores were repeated and standard radiographs taken at 3, 6, 12 and 24 months follow-up. Radiostereometric analysis (RSA) was employed to monitor the in-vivo femoral implant stability. The Oxford Hip was additionally collected at 36 and 48 months. Forty-one patients, 23 males and 18 females, received the SILENT™ femoral implant in primary total hip replacement surgery between January and November 2003. The mean age was 50.4 years (range 26–65) with an average BMI of 26.6 (Range 19–37). The diagnoses included osteoarthritis (68%), AVN (15%), DDH (7%), post-infection osteoarthritis (5%) and others (5%). The average Harris Hip Score increased from 54.3 (Range 26–80) pre-operatively to 95.0 (Range 46–100) at 24 months. This improvement was supported by the patient’s view with the mean Oxford Hip Score data changing from a pre-operative level of 38.9 (Range 19–52) to a 4-year average of 13.2 (Range 12–27). The radiographic performance is also positive with only one patient having evidence of a radiolucent line on the latest x-rays at 24 months however this is non-progressive and has been present since 6 months post-op. RSA data shows the mean values for the translations of the implant and distal tip in any of the three axes to be low out to 2 years follow-up indicating a high degree of stability in this critical post-operative period. No revisions of the SILENT™ implant have been undertaken to date. Early prosthetic stability is acknowledged as a critical success criterion for any new femoral implant being introduced into clinical practice. This has been demonstrated for a new, ultra-short, femoral implant thereby presenting a new solution for patients who could benefit from healthy bone preservation at the time of primary surgery.
