Aims Iliopsoas impingement occurs in 4% to 30% of patients after undergoing total hip arthroplasty (THA). Despite a relatively high incidence, there are few attempts at modelling impingement between the iliopsoas and acetabular component, and no attempts at modelling this in a representative cohort of subjects. The purpose of this study was to develop a novel computational model for quantifying the impingement between the iliopsoas and acetabular component and validate its utility in a case-controlled investigation. Methods This was a retrospective cohort study of patients who underwent THA surgery that included 23 symptomatic patients diagnosed with iliopsoas tendonitis, and 23 patients not diagnosed with iliopsoas tendonitis. All patients received postoperative CT imaging, postoperative standing radiography, and had minimum six months’ follow-up. 3D models of each patient’s prosthetic and bony anatomy were generated, landmarked, and simulated in a novel iliopsoas impingement detection model in supine and standing pelvic positions. Logistic regression models were implemented to determine if the probability of pain could be significantly predicted. Receiver operating characteristic curves were generated to determine the model’s sensitivity, specificity, and area under the curve (AUC). Results Highly significant differences between the symptomatic and asymptomatic cohorts were observed for iliopsoas impingement. Logistic regression models determined that the impingement values significantly predicted the probability of groin pain. The simulation had a sensitivity of 74%, specificity of 100%, and an AUC of 0.86. Conclusion We developed a computational model that can quantify iliopsoas impingement and verified its accuracy in a case-controlled investigation. This tool has the potential to be used preoperatively, to guide decisions about optimal cup placement, and postoperatively, to assist in the diagnosis of iliopsoas tendonitis. Cite this article: Bone Jt Open 2023;4(1):3–12.

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Aims Leg length discrepancy (LLD) is a common pre- and postoperative issue in total hip arthroplasty (THA) patients. The conventional technique for measuring LLD has historically been on a non-weightbearing anteroposterior pelvic radiograph; however, this does not capture many potential sources of LLD. The aim of this study was to determine if long-limb EOS radiology can provide a more reproducible and holistic measurement of LLD. Methods In all, 93 patients who underwent a THA received a standardized preoperative EOS scan, anteroposterior (AP) radiograph, and clinical LLD assessment. Overall, 13 measurements were taken along both anatomical and functional axes and measured twice by an orthopaedic fellow and surgical planning engineer to calculate intraoperator reproducibility and correlations between measurements. Results Strong correlations were observed for all EOS measurements (rs > 0.9). The strongest correlation with AP radiograph (inter-teardrop line) was observed for functional-ASIS-to-floor (functional) (rs = 0.57), much weaker than the correlations between EOS measurements. ASIS-to-ankle measurements exhibited a high correlation to other linear measurements and the highest ICC (rs = 0.97). Using anterior superior iliac spine (ASIS)-to-ankle, 33% of patients had an absolute LLD of greater than 10 mm, which was statistically different from the inter-teardrop LLD measurement (p < 0.005). Discussion We found that the conventional measurement of LLD on AP pelvic radiograph does not correlate well with long leg measurements and may not provide a true appreciation of LLD. ASIS-to-ankle demonstrated improved detection of potential LLD than other EOS and radiograph measurements. Full length, functional imaging methods may become the new gold standard to measure LLD. Cite this article: Bone Jt Open 2022;3(12):960–968.

Introduction Total Knee Arthroplasty (TKA) for both patients and the surgical team is a journey spanning many months, rather than purely a hospital episode of care. To improve patient outcomes and reduce costs in TKA, greater emphasis should be placed on the pre- and postoperative periods as, historically, innovation has focused on the intraoperative execution of the surgery. The purpose of this study was to determine if a pre- and postoperative physiotherapy program delivered via a digital application could reduce hospital length of stay (LOS) without compromising patient outcomes. Methods A retrospective series of 294 patients who underwent TKA from a single-surgeon in a single-centre was examined. This included 232 patients who underwent a pre- and postoperative physiotherapist-led program delivered via a digital application and 62 patients who underwent a conventional pre- and postoperative protocol. 2:1 nearest neighbour propensity score matching was performed to establish covariate balance between the cohorts. Data collected included pre- and postoperative Knee Injury and Osteoarthritis Outcome Score (KOOS), KOOS for Joint Replacement (KOOS, JR), and acute, rehabilitation, and total LOS. Results No significant difference in KOOS or KOOS, JR scores was observed at 12-month follow-up. A significantly reduced rehabilitation (P = 0.014) and total LOS (P = 0.015) was observed in the patients who received the digital physiotherapy program. Conclusions There may be significant economic benefits to a pre- and postoperative physiotherapy program delivered via a digital application. Our results suggest that a digital physiotherapist-led patient program may reduce the need for inpatient rehabilitation services without compromising patient outcomes.