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Registries have significant roles in assessing the comparative performance of devices. Ideally, early identification of outliers should use a time-to-event outcome while reducing the confounding effects of other components in the device and patient characteristics. Machine learning (ML), which contains self-learning algorithms, is one approach to consider many variables simultaneously to reduce the impact of confounding. The principal objective of this study was to investigate the effectiveness of using either random survival forest (RSF) or regularised/unregularised Cox regression to account for patient and associated device confounding factors in comparison with current standard techniques. This study evaluated RSF and regularised/unregularised Cox regression using data from the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) to detect outlier devices among 213 individual primary total hip components performed in 163,356 primary procedures from 1 January 2015 to the end of 2019. Device components and patient characteristics were the inputs, and time to first revision surgery was the primary outcome treated as a censored case for death. The effectiveness of the ML approaches was assessed based on the ability to detect the outliers identified by the AOANJRR standard approach. In the study cohort, the standardised AOANJRR approach identified three acetabular components and seven femoral stems as outliers. The ML approaches identified some but not all the outliers detected by the AOANJRR. Both the methods identified three of the same femoral stems, and the RSF identified the other five components, including two of the same acetabular cups and three of the same femoral stems. In addition, both the RSF and Cox techniques detected a number of additional device components that were not previously identified by the standard approach. The results showed that ML may be able to offer a supplementary approach to enhance the early identification of outlier devices. Random survival forest was a more comparable technique to the AOANJRR standard than the Cox regression, but further studies are required to better understand the potential of ML to improve the early identification of outliers. [ABSTRACT FROM AUTHOR]

Background: There are variations in the performance of individual prostheses used in hip replacements. Some of which have unexpectedly higher revision rates – outliers. The Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) has established a standardised multi-stage approach for identifying these devices. This is done by comparing the revision rates of individual prostheses to all other prostheses in class, with the exception of large head metal-on-metal (LHMoM) prostheses. However, improvements in device design and performance over time have required a need to reconsider the comparator group. This study aimed to identify a more specific comparator to better reflect contemporary surgical practice. Methods: The time to first revision was estimated on the data of 413,417 primary total conventional hip replacements undertaken for osteoarthritis (OA) from 01 January 2003 to 31 December 2019. Survivorship analyses with stepwise exclusions were undertaken. The first exclusion was LHMoM, followed by other non-modern bearing surfaces (defined as all the bearing couples except metal or ceramic heads on cross-linked polyethylene and mixed ceramic-on-ceramic), and then devices with modular neck-stem design or used for specific purposes (incl. constrained, dual-mobility, and head size <28 mm). Lastly, all remaining prostheses previously identified as having a higher than anticipated rate of revision (HTARR) were also excluded. Results: These exclusions progressively reduced the cumulative percent revision (CPR) rate. The final comparator, which only includes satisfactory-performed prostheses of contemporary design and use, has a 10-year CPR of 4.30% (95% CI, 4.2–4.41) which is lower than 4.93% (95% CI, 4.84–5.02) for the current comparator used by the AOANJRR (all prostheses excluding LHMOM). Over the study period, 13 additional components were identified utilising the modified comparator. Conclusions: The calculation of the comparator revision rate should be re-evaluated to include only modern prosthesis constructs to ensure that poorly performing prostheses are identified early. [ABSTRACT FROM AUTHOR]

While finite element (FE) models have been used extensively in orthopedic studies, validation of their outcome metrics has been limited to comparison against ex vivo testing. The aim of this study was to validate FE model predictions of the initial cup mechanical environment against patient‐matched in vivo measurements of acetabular cup migration using radiostereometric analysis (RSA). Tailored musculoskeletal and FE models were developed using a combination of three‐dimensional (3D) motion capture data and clinical computerized tomography (CT) scans for a cohort of eight individuals who underwent primary total hip replacement and were prospectively enrolled in an RSA study. FE models were developed to calculate the mean modulus of cancellous bone, composite peak micromotion (CPM), composite peak strain (CPS) and percentage area of bone ingrowth. The RSA cup migration at 3 months was used to corroborate the FE output metrics. Qualitatively, all FE‐predicted metrics followed a similar rank order as the in vivo RSA 3D migration data. The two cases with the lowest predicted CPM (<20 µm), lowest CPS (<0.0041), and high bone modulus (>917 MPa) were confirmed to have the lowest in vivo RSA 3D migration (<0.14 mm). The two cases with the largest predicted CPM (>80 µm), larger CPS (>0.0119) and lowest bone modulus (<472 MPa) were confirmed to have the largest in vivo RSA 3D migration (>0.78 mm). This study enabled the first corroboration between tailored musculoskeletal and FE model predictions with in vivo RSA cup migration. Investigation of additional patient‐matched CT, gait, and RSA examinations may allow further development and validation of FE models. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine the effect of surgical change to the acetabular offset and femoral offset on the abductor muscle and hip contact forces after primary total hip arthroplasty (THA) using computational methods. Thirty‐five patients undergoing primary THA were recruited. Patients underwent a computed tomography scan of their pelvis and hip, and underwent gait analysis pre‐ and 6‐months postoperatively. Surgically induced changes in acetabular and femoral offset were used to inform a musculoskeletal model to estimated abductor muscle and hip joint contact forces. Two experiments were performed: (1) influence of changes in hip geometry on hip biomechanics with preoperative kinematics; and (2) influence of changes in hip geometry on hip biomechanics with postoperative kinematics. Superior and medial placement of the hip centre of rotation during THA was most influential in reducing hip contact forces, predicting 63% of the variance (p < 0.001). When comparing the preoperative geometry and kinematics model, with postoperative geometry and kinematics, hip contact forces increased after surgery (0.68 BW, p = 0.001). Increasing the abductor lever arm reduced abductor muscle force by 28% (p < 0.001) and resultant hip contact force by 17% (0.6 BW, p = 0.003), with both preoperative and postoperative kinematics. Failure to increase abductor lever arm increased resultant hip contact force 11% (0.33 BW, p < 0.001). In conclusion, increasing the abductor lever arm provides a substantial biomechanical benefit to reduce hip abductor and resultant hip joint contact forces. The magnitude of this effect is equivalent to the average increase in hip contact force seen with improved gait from pre‐to post‐surgery. [ABSTRACT FROM AUTHOR]

Metal artifact reduction (MAR) has improved computed tomography (CT) imaging of total hip arthroplasty (THA) but the assessment of osteolysis and implant to bone contact relies on the accurate depiction of bone defects, cancellous bone, and cement. This study evaluates the impact of available single and dual‐energy protocols on periprosthetic tissue characterization in a cadaveric phantom. Bilateral THA was performed on a fresh frozen cadaveric pelvis with simulated osteolytic cavities. CT acquisitions with projection‐based MAR and noise equivalence were performed using single energy 140 kVp, single energy 150 kVp with 0.6 mm tin filtration, and dual‐energy at 100/150 kVp with 0.6 mm tin filtration, from which simulated energies were extracted. Image subtraction, segmentation, region of interest histograms, and line profiles were used to characterize tissue density and separation. Tissue densities were heavily dependent on the energy profile of the protocol. Cancellous bone ranged from 182 to 45 HU and cement from 1012 to 131 HU using 140 kVp compared to dual‐energy with weighted high energy tube, respectively. Spectral separation between cancellous bone, osteolytic defect, and cement was reduced for all protocols compared with 140 kVp. Spectral overlap was most severe using dual‐energy with heavily weighted high‐energy tubes. Dual‐energy algorithms reduced trabecular contrast within the cancellous bone and cortical edge response. Although the dual‐energy acquisition has been proposed as an additive to projection‐based MAR techniques in THA, reduced density and contrast in clinically relevant periprosthetic tissue compared to 140 kVp single energy may limit its use in characterizing periprosthetic tissues. [ABSTRACT FROM AUTHOR]

Background and purpose -- We conducted a systematic review and meta-analysis of RSA studies to investigate the early and long-term migration patterns of acetabular cups and the influence of implant factors on cup migration over time. Methods -- We performed a systematic search of PubMed, Embase, and Scopus databases to identify all RSA studies of cup migration following primary total hip replacement (THR). Proximal migration at 3 and 6 months, 1, 2, 5, and 10 years were considered for analysis. Implant factors investigated included fixation type, head size, bearing surface, uncemented coating design, and the decade of RSA introduction. Results -- 47 studies reported the proximal migration of 83 cohorts (2,328 cups). Besides 1 threaded cup design, no implant factor investigated was found to significantly influence proximal migration. The mean pooled 2-year proximal migration of cemented cups (0.14 mm, 95% confidence interval [CI] 0.08-0.20) was not significantly different from uncemented cups (0.12 mm, CI 0.04-0.19). The mean pooled proximal migration at 6 months was 0.11 mm (CI 0.06-0.16) and there was no significant increase between 6 months and 2 years (0.015 mm, CI 0.000-0.030). 27 of 75 cohorts (36%) reported mean proximal migration greater than 0.2 mm at 2 years, which has previously been identified as a predictor of implants at risk of long-term loosening. Conclusion -- Our meta-analysis demonstrated that the majority of cup migration occurs within the first 6 months. With one exception, no implant factors influenced the 2-year proximal migration of acetabular cups. 36% of studies with 2-year migration were considered at risk of long-term loosening. Further investigation and comparison against longterm survivorship data would validate 6-month and/or 1-year proximal migration measurements as an earlier predictor of long-term loosening than the current 2-year threshold. [ABSTRACT FROM AUTHOR]