Improved patient reported outcomes with the direct anterior approach versus the posterior approach for total hip arthroplasty in the early post-operative period.

BACKGROUND: Patients undergoing total hip arthroplasty (THA) with the direct anterior approach (DAA) may experience faster recovery but may also have better baseline health than those who undergo THA with the posterior approach (PA). This study aimed to compare patient-reported outcome measures (PROMs) between the DAA and PA while controlling for baseline factors. METHODS: This is a secondary data analysis from a prospective cohort study of patients utilizing a smartphone-based care management platform following THA. The primary outcomes were HOOS JR and EQ-5D-5L through 1 year and change from baseline. Longitudinal regression models were created to control for baseline characteristics and investigate the impact of surgical approach on PROMs. RESULTS: Of 1364 THAs evaluated, 731 (53.6%) were female, and 840 (61.6%) used the PA. Patients in the PA group were of similar age but had higher body mass index and comorbidity scores. Pre-operative HOOS JR and EQ-5D-5L were comparable, but higher post-operatively in the DAA group through 6 months (p = 0.03 and p = 0.005). At 1 year post-operatively, HOOS JR and EQ-5D-5L did not vary between groups (p = 0.48 and p = 0.56), nor did changes from baseline (p = 0.47 and p = 0.11). After controlling baseline characteristics, DAA was significantly associated with higher average HOOS JR through 6 months (p = 0.03) and EQ-5D-5L through 3 months (p = 0.005), but not at 12 months (p = 0.89 and p = 0.56). CONCLUSION: THA patients undergoing DAA demonstrate earlier improvements in HOOS JR and EQ-5D-5L. However, these differences may not be clinically significant and are not evident at 1-year post-operative. Patient selection and surgeon training may continue to affect outcomes by surgical approach.

Multicenter, prospective cohort study: immediate postoperative gains in active range of motion following robotic-assisted total knee replacement compared to a propensity-matched control using manual instrumentation.

BACKGROUND: Range of motion (ROM) following total knee replacement (TKR) has been associated with patient satisfaction and knee function, and is also an early indicator of a successful procedure. Robotic-assisted TKR (raTKR) is considered to reproduce more precise resections, and, as a result, may be associated with improved early patient satisfaction compared to manual TKR (mTKR). The purpose of this study was to evaluate the early postoperative active ROM (aROM) between raTKR and mTKR. METHODS: A total of 216 mTKR patients were propensity-matched, in terms of age, gender, comorbidities, and BMI, to 216 raTKR cases. Intraoperative and immediate postoperative adverse events were collected. Knee flexion and extension aROM were measured preoperatively and at one- and three months after operation. RESULTS: Changes in flexion aROM were significantly greater in raTKR vs. mTKR at one- (6.9°, 95% CI: 3.5, 10.4°) and three months (4.9°, 95% CI: 2.1, 7.7°). Flexion aROM was greater at three postoperative months compared to preoperative aROM only in the raTKR group, and raTKR patients had higher odds of achieving ≥ 90° of flexion at one month after operation (OR: 2.15, 95% CI: 1.16, 3.99). There were no significant differences between groups in intraoperative (P > 0.999) or postoperative adverse events. CONCLUSIONS: Compared with mTKR, raTKR resulted  in less loss of aROM immediately after operation and a faster recovery of aROM within three months after operation. TRIAL REGISTRATION: Clinicaltrials.gov (NCT# 03737149).

Using Patient Demographics and Statistical Modeling to Predict Knee Tibia Component Sizing in Total Knee Arthroplasty.

BACKGROUND: Preoperative planning is important to achieve successful implantation in primary total knee arthroplasty (TKA). However, traditional TKA templating techniques are not accurate enough to predict the component size to a very close range. METHODS: With the goal of developing a general predictive statistical model using patient demographic information, ordinal logistic regression was applied to build a proportional odds model to predict the tibia component size. The study retrospectively collected the data of 1992 primary Persona Knee System TKA procedures. Of them, 199 procedures were randomly selected as testing data and the rest of the data were randomly partitioned between model training data and model evaluation data with a ratio of 7:3. Different models were trained and evaluated on the training and validation data sets after data exploration. RESULTS: The final model had patient gender, age, weight, and height as independent variables and predicted the tibia size within 1 size difference 96% of the time on the validation data, 94% of the time on the testing data, and 92% on a prospective cadaver data set. CONCLUSION: The study results indicated the statistical model built by ordinal logistic regression can increase the accuracy of tibia sizing information for Persona Knee preoperative templating. This research shows statistical modeling may be used with radiographs to dramatically enhance the templating accuracy, efficiency, and quality. In general, this methodology can be applied to other TKA products when the data are applicable.