What Is the Role of a Periarticular Injection for Knee Arthroplasty Patients Receiving a Multimodal Analgesia Regimen Incorporating Adductor Canal and Infiltration Between the Popliteal Artery and Capsule of the Knee Blocks? A Randomized Blinded Placebo-Controlled Noninferiority Trial.

BACKGROUND: Optimal analgesic protocols for total knee arthroplasty (TKA) patients remain controversial. Multimodal analgesia is advocated, often including peripheral nerve blocks and/or periarticular injections (PAIs). If 2 blocks (adductor canal block [ACB] plus infiltration between the popliteal artery and capsule of the knee [IPACK]) are used, also performing PAI may not be necessary. This noninferiority trial hypothesized that TKA patients with ACB + IPACK + saline PAI (sham infiltration) would have pain scores that were no worse than those of patients with ACB + IPACK + active PAI with local anesthetic. METHODS: A multimodal analgesic protocol of spinal anesthesia, ACB and IPACK blocks, intraoperative ketamine and ketorolac, postoperative ketorolac followed by meloxicam, acetaminophen, duloxetine, and oral opioids was used. Patients undergoing primary unilateral TKA were randomized to receive either active PAI or control PAI. The active PAI included a deep injection, performed before cementation, of bupivacaine 0.25% with epinephrine, 30 mL; morphine; methylprednisolone; cefazolin; with normal saline to bring total volume to 64 mL. A superficial injection of 20 mL bupivacaine, 0.25%, was administered before closure. Control injections were normal saline injected with the same injection technique and volumes. The primary outcome was numeric rating scale pain with ambulation on postoperative day 1. A noninferiority margin of 1.0 was used. RESULTS: Ninety-four patients were randomized. NRS pain with ambulation at POD1 in the ACB + IPACK + saline PAI group was not found to be noninferior to that of the ACB + IPACK + active PAI group (difference = 0.3, 95% confidence interval [CI], [-0.9 to 1.5], P = .120). Pain scores at rest did not differ significantly among groups. No significant difference was observed in opioid consumption between groups. Cumulative oral morphine equivalents through postoperative day 2 were 89 ± 40 mg (mean ± standard deviation), saline PAI, vs 73 ± 52, active PAI, P = .1. No significant differences were observed for worst pain, fraction of time in severe pain, pain interference, side-effects (nausea, drowsiness, itching, dizziness), quality of recovery, satisfaction, length of stay, chronic pain, and orthopedic outcomes. CONCLUSIONS: For TKA patients given a comprehensive analgesic protocol, use of saline PAI did not demonstrate noninferiority compared to active PAI. Neither the primary nor any secondary outcomes demonstrated superiority for active PAI, however. As we cannot claim either technique to be better or worse, there remains flexibility for use of either technique.

No Difference in Limb Alignment Between Kinematic and Mechanical Alignment Robotic-Assisted Total Knee Arthroplasty.

BACKGROUND: Individualized alignment techniques have gained major interest in an effort to increase satisfaction among total knee arthroplasty patients. This study aimed to compare postoperative alignment between kinematic alignment (KA) and mechanical alignment (MA) and assess whether KA significantly deviates from the principle of aligning the limb as close to neutral alignment as possible. METHODS: There were 234 patients who underwent robotic-assisted total knee arthroplasty using an unrestricted KA and a strict MA technique (KA: 145, MA: 89). The lateral distal femoral angle, medial proximal tibia angle, and the resultant arithmetic hip-knee-ankle angle (aHKA) were measured. The aHKA < 0 indicated varus alignment, while the aHKA > 0 indicated valgus knee alignment. The primary outcome was the frequency of cases that resulted in an aHKA of ± 4° of neutral (0°), as assessed on full-leg standing radiographs obtained at 6 weeks postoperatively. The secondary outcome was the change in coronal plane alignment of the knee classification type from preoperative to postoperative between the MA and KA groups. RESULTS: The mean preoperative aHKA was similar between the 2 groups (P = .19). The KA group had a mean postoperative aHKA of -1.4 ± 2.4°, while the MA group had a mean postoperative aHKA of -0.5 ± 2.1°. No significant difference in limb alignment was identified between KA and MA cases that resulted in hip-knee-ankle angle of ± 4° being neutral (91.7 versus 96.6%, P = .14). There were 97.2% of cases in the KA group that fell within the ± 5° range. The MA group was associated with a significantly higher rate of coronal plane alignment of the knee classification type change from preoperatively to postoperatively (P < .001). CONCLUSIONS: Kinematic alignment achieved similar postoperative aHKA compared to MA, and thus did not significantly deviate from the principle of aligning the limb as close to neutral alignment as possible. Surgeons should feel comfortable starting to introduce individualized alignment techniques. Without being restricted by boundaries, postoperative alignment will be within 5 degrees of neutral 97% of the time.

Decreased Instability in High-Risk (Hip-Spine 2B) Patients After Modifications of Surgical Planning and Technique.

BACKGROUND: Patients undergoing primary total hip arthroplasty (THA) who have spinal deformity and a stiff spine are the highest-risk group for instability. Despite the increasing use of dual-mobility cups and large femoral heads, dislocation remains a major complication after THA. Preoperative planning becomes a critical aspect of ensuring precise component positioning within a safe zone. The purpose of this study was to investigate dislocation rates over a 9-year period. METHODS: A retrospective review of 4,731 THAs performed by 3 orthopaedic surgeons between January 2014 and March 2023 was performed. Spinopelvic measurements were conducted to determine the hip-spine classification group for each patient. Only patients classified as 2B (pelvic incidence-lumbar lordosis > 10° and Δsacral slope < 10°) were eligible. Both absolute and relative dislocation frequencies were then analyzed using time-series analysis techniques and Fisher's exact tests. RESULTS: A total of 281 hip-spine 2B patients undergoing primary THA were eligible for analysis (57% women; mean age, range: 66 years, 23 to 87; mean body mass index, range: 28, 16 to 45). The overall dislocation rate was 4.3%. Use of femoral head sizes ≥ 40 mm increased from 4% in 2014 to 2019 to 37% in 2020 to 2023 (P < .001), while the use of dual-mobility cups decreased from 100% in 2014 to 2019 to 37% in 2020 to 2023 (P < .001). Acetabular component planning was changed from the supine plane to the standing plane in February 2020. Those changes in surgical practice were notably correlated with a significant decrease in dislocation rates from 6.8% in 2014 to 2019 to 1.5% in 2020 to 2023 (P = .03). CONCLUSIONS: Our study demonstrates that the introduction of advanced preoperative THA planning to the standing plane, coupled with precise intraoperative technology for implant placement, can significantly reduce the risk of instability in high-risk THA patients. Notably, we observed a significant decrease in dislocation rates, which aligned with the shift in surgical practice. LEVEL OF EVIDENCE: IV.

Deep-Learning Automation of Preoperative Radiographic Parameters Associated With Early Periprosthetic Femur Fracture After Total Hip Arthroplasty.

BACKGROUND: The radiographic assessment of bone morphology impacts implant selection and fixation type in total hip arthroplasty (THA) and is important to minimize the risk of periprosthetic femur fracture (PFF). We utilized a deep-learning algorithm to automate femoral radiographic parameters and determined which automated parameters were associated with early PFF. METHODS: Radiographs from a publicly available database and from patients undergoing primary cementless THA at a high-volume institution (2016 to 2020) were obtained. A U-Net algorithm was trained to segment femoral landmarks for bone morphology parameter automation. Automated parameters were compared against that of a fellowship-trained surgeon and compared in an independent cohort of 100 patients who underwent THA (50 with early PFF and 50 controls matched by femoral component, age, sex, body mass index, and surgical approach). RESULTS: On the independent cohort, the algorithm generated 1,710 unique measurements for 95 images (5% lesser trochanter identification failure) in 22 minutes. Medullary canal width, femoral cortex width, canal flare index, morphological cortical index, canal bone ratio, and canal calcar ratio had good-to-excellent correlation with surgeon measurements (Pearson's correlation coefficient: 0.76 to 0.96). Canal calcar ratios (0.43 ± 0.08 versus 0.40 ± 0.07) and canal bone ratios (0.39 ± 0.06 versus 0.36 ± 0.06) were higher (P < .05) in the PFF cohort when comparing the automated parameters. CONCLUSIONS: Deep-learning automated parameters demonstrated differences in patients who had and did not have early PFF after cementless primary THA. This algorithm has the potential to complement and improve patient-specific PFF risk-prediction tools.

Is Tibial Bone Mineral Density Related to Sex, Age, Preoperative Alignment, or Fixation Method in Primary Total Knee Arthroplasty?

BACKGROUND: Cementless total knee arthroplasty (TKA) has regained interest for its potential for long-term biologic fixation. The density of the bone is related to its ability to resist static and cyclic loading and can affect long-term implant fixation; however, little is known about the density distribution of periarticular bone in TKA patients. Thus, we sought to characterize the bone mineral density (BMD) of the proximal tibia in TKA patients. METHODS: We included 42 women and 50 men (mean age 63 years, range: 50 to 87; mean body mass index 31.6, range: 20.5 to 49.1) who underwent robotic-assisted TKA and had preoperative computed tomography scans with a BMD calibration phantom. Using the robotic surgical plan, we computed the BMD distribution at 1 mm-spaced cross-sections parallel to the tibial cut from 2 mm above the cut to 10 mm below. The BMD was analyzed with respect to patient sex, age, preoperative alignment, and type of fixation. RESULTS: The BMD decreased from proximal to distal. The greatest changes occurred within ± 2 mm of the tibial cut. Age did not affect BMD for men; however, women between 60 and 70 years had higher BMD than women ≥ 70 years for the total cut (P = .03) and the medial half of the cut (P = .03). Cemented implants were used in 1 86-year-old man and 18 women (seven < 60 years, seven 60 to 70 years, and four ≥ 70 year old). We found only BMD differences between cemented or cementless fixation for women < 60 years. CONCLUSIONS: To our knowledge, this is the first study to characterize the preoperative BMD distribution in TKA patients relative to the intraoperative tibial cut. Our results indicate that while sex and age may be useful surrogates of BMD, the clinically relevant thresholds for cementless knees remain unclear, offering an area for future studies.

Impact of Selective Posterior Cruciate Ligament Fiber Release on Femoral Rollback in Cruciate-Retaining Total Knee Arthroplasty: A Computational Study.

BACKGROUND: Partial or total release of the posterior cruciate ligament (PCL) is often performed intraoperatively in cruciate-retaining total knee arthroplasty (CR-TKA) to alleviate excessive femoral rollback. However, the effect of the release of selected fibers of the PCL on femoral rollback in CR-TKA is not well understood. Therefore, we used a computational model to quantify the effect of selective PCL fiber releases on femoral rollback in CR-TKA. METHODS: Computational models of 9 cadaveric knees (age: 63 years, range 47 to 79) were virtually implanted with a CR-TKA. Passive flexion was simulated with the PCL retained and after serially releasing each individual fiber of the PCL, starting with the one located most anteriorly and laterally on the femoral notch and finishing with the one located most posteriorly on the medial femoral condyle. The experiment was repeated after releasing only the central PCL fiber. The femoral rollback of each condyle was defined as the anterior-posterior distance between tibiofemoral contact points at 0° and 90° of flexion. RESULTS: Release of the central PCL fiber in combination with the anterolateral (AL) fibers, reduced femoral rollback a median of 1.5 [0.8, 2.1] mm (P = .01) medially and by 2.0 [1.2, 2.5] mm (P = .04) laterally. Releasing the central fiber alone reduced the rollback by 0.7 [0.4, 1.1] mm (P < .01) medially and by 1.0 [0.5, 1.1] mm (P < .01) laterally, accounting for 47 and 50% of the reduction when released in combination with the AL fibers. CONCLUSIONS: Releasing the central fibers of the PCL had the largest impact on reducing femoral rollback, either alone or in combination with the release of the entire AL bundle. Thus, our findings provide clinical guidance regarding the regions of the PCL that surgeons should target to reduce femoral rollback in CR-TKA.

Hot Topics and Current Controversies in Total Knee Arthroplasty.

Total knee arthroplasty continues to evolve. It is important to review some of the current controversies and hot topics in arthroplasty. Optimal knee alignment strategy is now just a matter of debate. Mechanical, kinematic, and functional alignment and the role of robotics in achieving optimum alignment are important topics, along with fixation and outpatient knee arthroplasty.

High degree of alignment precision associated with total knee arthroplasty performed using a surgical robot or handheld navigation.

PURPOSE: The purpose of this study was to compare the precision of bony resections during total knee arthroplasty (TKA) performed using different computer-assisted technologies. METHODS: Patients who underwent a primary TKA using an imageless accelerometer-based handheld navigation system (KneeAlign2®, OrthAlign Inc.) or computed tomography-based large-console surgical robot (Mako®, Stryker Corp.) from 2017 to 2020 were retrospectively reviewed. Templated alignment targets and demographic data were collected. Coronal plane alignment of the femoral and tibial components and tibial slope were measured on postoperative radiographs. Patients with excessive flexion or rotation preventing accurate measurement were excluded. RESULTS: A total of 240 patients who underwent TKA using either a handheld (n = 120) or robotic (n = 120) system were included. There were no statistically significant differences in age, sex, and BMI between groups. A small but statistically significant difference in the precision of the distal femoral resection was observed between the handheld and robotic cohorts (1.5° vs. 1.1° difference between templated and measured alignments, p = 0.024), though this is likely clinically insignificant. There were no significant differences in the precision of the tibial resection between the handheld and robotic groups (coronal plane 0.9° vs. 1.0°, n.s.; sagittal plane 1.2° vs. 1.1°, n.s.). There were no significant differences in the rate of overall precision between cohorts (n.s.). CONCLUSIONS: A high degree of component alignment precision was observed for both imageless handheld navigation and CT-based robotic cohorts. Surgeons considering options for computer-assisted TKA should take other important factors, including surgical principles, templating software, ligament balancing, intraoperative adjustability, equipment logistics, and cost, into account. LEVEL OF EVIDENCE: III.

Unicompartmental Knee Arthroplasty Patients Have Lower Joint Awareness and Higher Function at 5 Years Compared to Total Knee Arthroplasties: A Matched Comparison.

BACKGROUND: The purpose of this study was to evaluate postoperative outcomes at minimum 5-year follow-up in patients following unicompartmental knee arthroplasty (UKA) compared to a matched cohort of total knee arthroplasty (TKA) patients. METHODS: Patients who had primarily medial compartment osteoarthritis (OA) who met criteria for medial UKA underwent TKA or medial UKA between 2014 and 2015 at a single institution, matched for age, sex, and body mass index. There were 127 UKAs in 120 patients and 118 TKAs in 116 patients included with minimum 5-year follow-up (range, 6 to 8). Mean age was 69 years (range, 59 to 79) and 71 years (range, 62 to 80) in the UKA and TKA groups, respectively (P = .049). RESULTS: Patients who underwent UKA had significantly higher mean (±SD) Forgotten Joint Scores (87 ± 20 versus 59 ± 34, P < .001); higher Knee Society Scores (88 ± 14 versus 75 ± 21, P < .001); and lower Numeric Pain Rating Scores (0.8 ± 1.6 versus 1.9 ± 2.2, P < .001). Survivorship free from all-cause revision was 96% (95% CI = 93%-99%) and 99% (95% CI = 97%-100%) at 5 years for TKA and UKA, respectively (P = .52). There were 8 both component revisions in the TKA group within 5 years from the date of surgery and 2 UKA conversions to TKA after 5-year follow-up. CONCLUSION: Patients who have medial compartment OA and underwent UKA had significantly lower joint awareness, decreased pain, improved function, and higher satisfaction compared to matched TKA patients at minimum 5-year follow-up while maintaining excellent survivorship.

Deep Learning Phenotype Automation and Cohort Analyses of 1,946 Knees Using the Coronal Plane Alignment of the Knee Classification.

BACKGROUND: The Coronal Plane Alignment of the Knee (CPAK) classification allows for knee phenotyping which can be used in preoperative planning prior to total knee arthroplasty. We used deep learning (DL) to automate knee phenotyping and analyzed CPAK distributions in a large patient cohort. METHODS: Patients who had full-limb radiographs from a large arthritis database were retrospectively included. A DL algorithm was developed to automate CPAK knee alignment parameters including the lateral distal femoral, medial proximal tibia, hip-knee-ankle, and joint line obliquity angles. The algorithm was validated against a fellowship-trained arthroplasty surgeon. After applying the algorithm in a large patient cohort (n = 1,946 knees), the distribution of CPAK was compared across patient sex and baseline Kellgren-Lawrence (KL) scores. RESULTS: There was no significant difference in the CPAK angles (n = 140, P = .66-.98, inter-class correlation coefficient = 0.89-0.91) or phenotype classifications made by the algorithm and surgeon (P = .96). The deep learning algorithm measured the entire cohort (n = 1,946 knees, mean age 61 years [range, 46 to 80 years], 51% women) in < 5 hours. Women had more valgus CPAK phenotypes than men (P < .05). Patients who had higher KL grades at baseline (2 to 4) were more varus using the CPAK classification compared to lower KL grades (0 to 1) (P < .05). CONCLUSION: We applied an accurate, automated DL algorithm on a large patient cohort to determine knee phenotypes, helping to validate and strengthen the CPAK classification system. Analyses revealed that sex-specific and major bone loss adjustments may need to be accounted for when using this system.

Significantly Worse Fixation of Cemented Patellar Components on Multiacquisition Variable-Resonance Image Combination Magnetic Resonance Imaging Compared to Femoral and Tibial Components: A Cause for Concern?

BACKGROUND: The etiology of anterior knee pain after total knee arthroplasty (TKA) remains unclear. Few studies have examined patellar fixation quality. The purpose of the present study was to evaluate the patellar cement-bone interface after TKA on magnetic resonance imaging (MRI) and to correlate the patella fixation grade with the incidence of anterior knee pain. METHODS: We retrospectively reviewed 279 knees undergoing metal artifact reduction MRI for either anterior or generalized knee pain at least 6 months after cemented, posterior-stabilized TKA with patellar resurfacing with one implant manufacturer. MRI cement-bone interfaces and percent-integration of the patella, femur, and tibia were assessed by a fellowship-trained senior musculoskeletal radiologist. The grade and character of the patella interface were compared to the femur and tibia. Regression analyses were used to determine the association between patella integration with anterior knee pain. RESULTS: There were more patellar components with ≥75% zones of fibrous tissue (50%) compared to the femur (18%) or tibia (5%) (P < .001). There were a greater number of patellar implants with poor cement integration (18%) compared to the femur (1%) or tibia (1%) (P < .001). MRI findings showed more evidence of patellar component loosening (8%) compared to the femur (1%) or tibia (1%) (P < .001). Anterior knee pain was correlated with worse patella cement integration (P = .01), with women predicted to have better integration (P < .001). CONCLUSION: The quality of the patellar cement-bone interface after TKA is worse compared to the femoral or tibial component interface. Poor patellar cement-bone interface may be a source of anterior knee pain after TKA, but further investigation is required.

Undersizing the Tibial Baseplate in Cementless Total Knee Arthroplasty has Only a Small Impact on Bone-Implant Interaction: A Finite Element Biomechanical Study.

BACKGROUND: The tibial component in total knee arthroplasty (TKA) is often chosen to maximize coverage of the tibial cut, which can result in excessive internal rotation of the component. Optimal rotational alignment may require a smaller baseplate with suboptimal coverage that could threaten fixation. We asked: "does undersizing the tibial component of a cementless TKA to gain external rotation increase the risk of bone failure?" METHODS: We developed computational finite element (FE) analysis models from the computed tomography (CT) scans of 12 patients scheduled for primary TKA. The models were implanted with a cementless tibial baseplate that maximized coverage and one or two sizes smaller and externally rotated by 5°. We calculated the risk of bone collapse under loads representative of stair ascent. RESULTS: Undersizing the implant increased the area at risk of collapse for eight patients. However, the area at risk of collapse for the undersized implant (range, 5.2%-16.4%) was no different (P = .24) to the optimally sized implant (range, 4.5%-17.9%). The bone at risk of collapse was concentrated along the posterior edge of the implant. The area at risk of collapse was not proportional to implant size, and for four subjects undersizing the implant actually decreased the area at risk of collapse. CONCLUSION: While implants should maximize coverage of the tibial cut and seek support on dense bone, undersizing the tibial component to gain external rotation had minimal impact on the load transfer to the underlying bone. This FE analysis model of a cementless tibial baseplate may require further validation and additional studies to investigate the long-term biomechanical effects of undersizing the tibial baseplate. In conclusion, while surgeons should strive to use the appropriate tibial baseplate for each patient, our model identified only minor biomechanical consequences of undersizing the implant for the immediate postoperative bone-implant interaction and implant subsidence.

Leg-Length Discrepancy Variability on Standard Anteroposterior Pelvis Radiographs: An Analysis Using Deep Learning Measurements.

BACKGROUND: Leg-length discrepancy (LLD) is a critical factor in component selection and placement for total hip arthroplasty. However, LLD radiographic measurements are subject to variation based on the femoral/pelvic landmarks chosen. This study leveraged deep learning (DL) to automate LLD measurements on pelvis radiographs and compared LLD based on several anatomically distinct landmarks. METHODS: Patients who had baseline anteroposterior pelvis radiographs from the Osteoarthritis Initiative were included. A DL algorithm was created to identify LLD-relevant landmarks (ie, teardrop (TD), obturator foramen, ischial tuberosity, greater and lesser trochanters) and measure LLD accurately using six landmark combinations. The algorithm was then applied to automate LLD measurements in the entire cohort of patients. Interclass correlation coefficients (ICC) were calculated to assess agreement between different LLD methods. RESULTS: The DL algorithm measurements were first validated in an independent cohort for all six LLD methods (ICC = 0.73-0.98). Images from 3,689 patients (22,134 LLD measurements) were measured in 133 minutes. When using the TD and lesser trochanter landmarks as the standard LLD method, only measuring LLD using the TD and greater trochanter conferred acceptable agreement (ICC = 0.72). When comparing all six LLD methods for agreement, no combination had an ICC>0.90. Only two (13%) combinations had an ICC>0.75 and eight (53%) combinations had a poor ICC (<0.50). CONCLUSION: We leveraged DL to automate LLD measurements in a large patient cohort and found considerable variation in LLD based on the pelvic/femoral landmark selection. This emphasizes the need for the standardization of landmarks for both research and surgical planning.

Complication Rate After Primary Total Hip Arthroplasty Using the Posterior Approach and Enabling Technology: A Consecutive Series of 2,888 Hips.

BACKGROUND: Total hip arthroplasty (THA) is a safe and effective procedure; however, complications such as dislocation, fracture, and infection still occur. It is still unclear whether the dislocation rate via the posterior approach (PA) is better, equal, or worse than the direct anterior approach. Our aim was to report the primary THA dislocation rate via the PA using enabling technology in a large consecutive series of patients. METHODS: A retrospective cohort of 2,888 primary THAs were reviewed at a single, high-volume, academic institution from January 2018 to September 2021. All patients underwent a THA by 4 fellowship-trained orthopaedic surgeons through the PA with enabling technology. Overall dislocation and readmission rates within 90 days and up to 3 years were analyzed. RESULTS: Of the 2,888 procedures, a total of 39 patients had complications related to the surgery during the 3-year follow-up period. There were 10 patients (0.35%) who experienced a dislocation, with half undergoing surgical revision. Of the 39 patients who experienced complications, 37 (1.3%) were readmitted and 2 underwent revision during their hospital stay. Postoperative periprosthetic fractures were the most common cause for readmission and reoperation at a rate of 0.52% and 0.52%, respectively. CONCLUSION: The dislocation rate of 0.35% is one of the lowest reported rates via the PA at a mean follow up of 2.1 years and is comparable to previously published rates using alternate approaches. Using contemporary THA with enabling technology, the PA is a reliable approach with respect to dislocation and complication rates after primary THA.

Novel Arthrometer for Quantifying In Vivo Knee Laxity in Three Planes Following Total Knee Arthroplasty.

BACKGROUND: Knee instability is a leading cause of dissatisfaction following total knee arthroplasty (TKA). Instability can involve abnormal laxity in multiple directions including varus-valgus (VV) angulation, anterior-posterior (AP) translation, and internal-external rotation (IER). No existing arthrometer objectively quantifies knee laxity in all three of these directions. The study objectives were to verify the safety and assess reliability of a novel multiplanar arthrometer. METHODS: The arthrometer utilized a five degree-of-freedom instrumented linkage. Two examiners each conducted two tests on the leg that had received a TKA of 20 patients (mean age 65 years (range, 53-75); 9 men, 11 women), with nine and eleven distinct patients tested at 3-month and 1-year postoperative time points, respectively. AP forces from -10 to 30 Newtons, VV moments of ±3 Newton-meters, and IER moments of ±2.5 Newton-meters were applied to each subject's replaced knee. Severity and location of knee pain during testing were assessed using a visual analog scale. Intraexaminer and interexaminer reliabilities were characterized using intraclass correlation coefficients. RESULTS: All subjects successfully completed testing. Pain during testing averaged 0.7 (out of possible 10; range, 0-2.5). Intraexaminer reliability was >0.77 for all loading directions and examiners. Interexaminer reliability and 95% confidence intervals were 0.85 (0.66-0.94), 0.67 (0.35-0.85), and 0.54 (0.16-0.79) in the VV, IER, and AP directions, respectively. CONCLUSION: The novel arthrometer was safe for evaluating AP, VV, and IER laxities in subjects who had received TKA. This device could be used to examine relationships between laxity and patient perceptions of knee instability.

An Interpretable Machine Learning Model for Predicting 10-Year Total Hip Arthroplasty Risk.

BACKGROUND: As the demand for total hip arthroplasty (THA) rises, a predictive model for THA risk may aid patients and clinicians in augmenting shared decision-making. We aimed to develop and validate a model predicting THA within 10 years in patients using demographic, clinical, and deep learning (DL)-automated radiographic measurements. METHODS: Patients enrolled in the osteoarthritis initiative were included. DL algorithms measuring osteoarthritis- and dysplasia-relevant parameters on baseline pelvis radiographs were developed. Demographic, clinical, and radiographic measurement variables were then used to train generalized additive models to predict THA within 10 years from baseline. A total of 4,796 patients were included [9,592 hips; 58% female; 230 THAs (2.4%)]. Model performance using 1) baseline demographic and clinical variables 2) radiographic variables, and 3) all variables was compared. RESULTS: Using 110 demographic and clinical variables, the model had a baseline area under the receiver operating curve (AUROC) of 0.68 and area under the precision recall curve (AUPRC) of 0.08. Using 26 DL-automated hip measurements, the AUROC was 0.77 and AUPRC was 0.22. Combining all variables, the model improved to an AUROC of 0.81 and AUPRC of 0.28. Three of the top five predictive features in the combined model were radiographic variables, including minimum joint space, along with hip pain and analgesic use. Partial dependency plots revealed predictive discontinuities for radiographic measurements consistent with literature thresholds of osteoarthritis progression and hip dysplasia. CONCLUSION: A machine learning model predicting 10-year THA performed more accurately with DL radiographic measurements. The model weighted predictive variables in concordance with clinical THA pathology assessments.

Arthroplasty Surgeons Differ in Their Intraoperative Soft Tissue Assessments: A Study in Human Cadavers to Quantify Surgical Decision-making in TKA.

BACKGROUND: In TKA, soft tissue balancing is assessed through manual intraoperative trialing. This assessment is a physical examination via manually applied forces at the ankle, generating varus and valgus moments at the knee while the surgeon visualizes the lateral and medial gaps at the joint line. Based on this examination, important surgical decisions are made that influence knee stability, such as choosing the polyethylene insert thickness. Yet, the applied forces and the assessed gaps in this examination represent a qualitative art that relies on each surgeon's intuition, experience, and training. Therefore, the extent of variation among surgeons in conducting this exam, in terms of applied loads and assessed gaps, is unknown. Moreover, whether variability in the applied loads yields different surgical decisions, such as choice of insert thickness, is also unclear. Thus, surgeons and developers have no basis for deciding to what extent the applied loads need to be standardized and controlled during a knee balance exam in TKA. QUESTIONS/PURPOSES: (1) Do the applied moments in soft tissue assessment differ among surgeons? (2) Do the assessed gaps in soft tissue assessment differ among surgeons? (3) Is the choice of insert thickness associated with the applied moments? METHODS: Seven independent human cadaveric nonarthritic lower extremities from pelvis to toe were acquired (including five females and two males with a mean age of 73 ± 7 years and a mean BMI of 25.8 ± 3.8 kg/m 2 ). Posterior cruciate ligament substituting (posterior stabilized) TKA was performed only on the right knees. Five fellowship-trained knee surgeons (with 24, 15, 15, 7, and 6 years of clinical experience) and one chief orthopaedic resident independently examined soft tissue balance in each knee in extension (0° of flexion), midflexion (30° of flexion), and flexion (90° of flexion) and selected a polyethylene insert based on their assessment. Pliable force sensors were wrapped around the leg to measure the loads applied by each surgeon. A three-dimensional (3D) motion capture system was used to measure knee kinematics and a dynamic analysis software was used to estimate the medial and lateral gaps. We assessed (1) whether surgeons applied different moments by comparing the mean applied moment by surgeons in extension, midflexion, and flexion using repeated measures (RM)-ANOVA (p < 0.05 was assumed significantly different); (2) whether surgeons assessed different gaps by comparing the mean medial and lateral gaps in extension, midflexion, and flexion using RM-ANOVA (p < 0.05 was assumed significantly different); and (3) whether the applied moments in extension, midflexion, and flexion were associated with the insert thickness choice using a generalized estimating equation (p < 0.05 was assumed a significant association). RESULTS: The applied moments differed among surgeons, with the largest mean differences occurring in varus in midflexion (16.5 Nm; p = 0.02) and flexion (7.9 Nm; p < 0.001). The measured gaps differed among surgeons at all flexion angles, with the largest mean difference occurring in flexion (1.1 ± 0.4 mm; p < 0.001). In all knees except one, the choice of insert thickness varied by l mm among surgeons. The choice of insert thickness was weakly associated with the applied moments in varus (ß = -0.06 ± 0.02 [95% confidence interval -0.11 to -0.01]; p = 0.03) and valgus (ß = -0.09 ± 0.03 [95% CI -0.18 to -0.01]; p= 0.03) in extension and in varus in flexion (ß = -0.11 ± 0.04 [95% CI -0.22 to 0.00]; p = 0.04). To put our findings in context, the greatest regression coefficient (ß = -0.11) indicates that for every 9-Nm increase in the applied varus moment (that is, 22 N of force applied to the foot assuming a shank length of 0.4 m), the choice of insert thickness decreased by 1 mm. CONCLUSION: In TKA soft tissue assessment in a human cadaver model, five surgeons and one chief resident applied different moments in midflexion and flexion and targeted different gaps in extension, midflexion, and flexion. A weak association between the applied moments in extension and flexion and the insert choice was observed. Our results indicate that in the manual assessment of soft tissue, changes in the applied moments of 9 and 11 Nm (22 to 27 N on the surgeons' hands) in flexion and extension, respectively, yielded at least a 1-mm change in choice of insert thickness. The choice of insert thickness may be more sensitive to the applied moments in in vivo surgery because the surgeon is allowed a greater array of choices beyond insert thickness. CLINICAL RELEVANCE: Among five arthroplasty surgeons with different levels of experience and a chief resident, subjective soft tissue assessment yielded 1 to 2 mm of variation in their choice of insert thickness. Therefore, developers of tools to standardize soft tissue assessment in TKA should consider controlling the force applied by the surgeon to better control for variations in insert selection.

John Charnley Award: Deep Learning Prediction of Hip Joint Center on Standard Pelvis Radiographs.

BACKGROUND: Accurate hip joint center (HJC) determination is critical for preoperative planning, intraoperative execution, clinical outcomes after total hip arthroplasty, and commonly used classification systems in primary and revision hip replacement. However, current methods of preoperative HJC estimation are prone to subjectivity and human error. The purpose of the study was to leverage deep learning (DL) to develop a rapid and objective HJC estimation tool on anteroposterior (AP) pelvis radiographs. METHODS: Radiographs from 3,965 patients (7,930 hips) were included. A DL model workflow was created to detect bony landmarks and estimate HJC based on a pelvic height ratio method. The workflow was utilized to conduct a grid-search for optimal nonspecific, sex-specific, and patient-specific (using contralateral hip) pelvic height ratios on the training/validation cohort (6,344 hips). Algorithm performance was assessed on an independent testing cohort for HJC estimation comparison. RESULTS: The algorithm estimated HJC for the testing cohort at a rate of 0.65 seconds/hip based on features in AP radiographs alone. The model predicted HJC within 5 mm of error for 80% of hips using nonspecific ratios, which increased to 83% with sex-specific and 91% with patient-specific pelvic height ratio models. Mean error decreased utilizing the patient-specific model (3.09 ± 1.69 mm, P < .001). CONCLUSION: Using DL, we developed nonspecific, sex-specific, and patient-specific models capable of estimating native HJC on AP pelvis radiographs. This tool may provide clinical value when considering preoperative component position in patients planned to undergo THA and in reducing the subjective variability in HJC estimation. LEVEL OF EVIDENCE: Diagnostic, level IV.

Robotic Assistance for Posterior Approach Total Hip Arthroplasty Is Associated With Lower Risk of Revision for Dislocation When Compared to Manual Techniques.

BACKGROUND: Robotic-assistance total hip arthroplasty (RA-THA) and computer navigation THA (CN-THA) have been shown to improve accuracy of component positioning compared to manual techniques; however, controversy exists regarding clinical benefit. Moreover, these technologies may expose patients to risks. The purpose of this study is to compare rates of intraoperative fracture and complications requiring reoperation within 1 year for posterior approach RA-THA, CN-THA, and THA with no technology (Manual-THA). METHODS: In total, 13,802 primary, unilateral, elective, posterior approach THAs (1770 RA-THAs, 3155 CN-THAs, and 8877 Manual-THAs) were performed at a single institution between 2016 and 2020. Intraoperative fractures and reoperations within 1 year of the index procedure were identified. Cohorts were balanced using inverse probability of treatment weight based on age, gender, body mass index, femoral cementation, history of spine fusion, and Charlson Comorbidity Index. Logistic regression was performed to create odds ratios for complications. Additional regression analysis for dislocation was performed, adjusting for dual mobility and femoral head size. RESULTS: There were no differences in intraoperative fracture and postoperative complication rates between the groups (P = .521). RA-THA had a 0.3 odds ratio (95% confidence interval 0.1-0.9, P = .046) compared to Manual-THA for reoperation due to dislocation. CN-THA had an odds ratio of 3.0 for reoperation due to dislocation (95% confidence interval 0.8-11.3, P = .114) compared to RA-THA. The remaining complication odds ratios, including those for infection, loosening, dehiscence, and "other" were similar between the groups. CONCLUSION: RA-THA is associated with lower risk of revision for dislocation within 1 year of index surgery, when compared to Manual-THA performed through the posterior approach.

A Mid-Level Constrained Insert Reduces Coupled Axial Rotation but Not Coronal Mid-Flexion Laxity Induced by Joint Line Elevation in Posterior-Stabilized Total Knee Arthroplasty: A Computational Study.

BACKGROUND: Surgeons may resect additional distal femur during primary posterior-stabilized (PS) total knee arthroplasty (TKA) to correct a flexion contracture. However, the resultant joint line elevation (JLE) increases mid-flexion laxity. We determined whether a mid-level constraint (MLC) insert reduced mid-flexion laxity after JLE. METHODS: Six computational knee models were developed using computed tomography scans and average soft tissue properties yielding balanced extension gaps but with a 10° flexion contracture. Distal femoral resections of +2 and +4 mm were simulated with PS and MLC inserts. Varus-valgus ±10 Nm moments were applied at 30°, 45°, and 60° of flexion. Coronal laxity (the sum of varus-valgus angulation) and coupled axial rotation (the sum of internal/external rotation) were measured and compared between insert models. RESULTS: At 30° of flexion, coronal laxities with the PS insert at the +2 and +4 mm resections averaged 7.9° ± 0.6° and 11.3° ± 0.6°, respectively, and decreased by 0.8° (P = .06) and 1.0° (P = .07), respectively, with the MLC insert. PS rotational laxities at the +2 and +4 mm resections averaged 11.1° ± 3.9° and 12.5° ± 4.6°, respectively, and decreased by 5.6° (P = .01) and 7.1° (P = .02), respectively, with the MLC insert. Similar patterns were observed at 45° and 60° of flexion. CONCLUSION: With additional distal femoral resections to alleviate a flexion contracture, utilizing an MLC insert substantially reduced coupled axial rotation but had a minimal impact on coronal laxity compared to a PS insert. Efforts should be taken to avoid JLE in primary total knee arthroplasty as even MLC inserts may not mitigate coronal laxity.