Aims. Current diagnostic tools are not always able to effectively identify periprosthetic joint infections (PJIs). Recent studies suggest that circulating microRNAs (miRNAs) undergo changes under pathological conditions such as infection. The aim of this study was to analyze miRNA expression in hip arthroplasty PJI patients. Methods. This was a prospective pilot study, including 24 patients divided into three groups, with eight patients each undergoing revision of their hip arthroplasty due to aseptic reasons, and low- and high-grade PJI, respectively. The number of intraoperative samples and the incidence of positive cultures were recorded for each patient. Additionally, venous blood samples and periarticular tissue samples were collected from each patient to determine miRNA expressions between the groups. MiRNA screening was performed by small RNA-sequencing using the miRNA next generation sequencing (NGS)
Although the Fitmore Hip Stem has been on the market for almost 15 years, it is still not well documented in randomized controlled trials. This study compares the Fitmore stem with the CementLeSs (CLS) in several different clinical and radiological aspects. The hypothesis is that there will be no difference in outcome between stems. In total, 44 patients with bilateral hip osteoarthritis were recruited from the outpatient clinic at a single tertiary orthopaedic centre. The patients were operated with bilateral one-stage total hip arthroplasty. The most painful hip was randomized to either Fitmore or CLS femoral component; the second hip was operated with the femoral component not used on the first side. Patients were evaluated at three and six months and at one, two, and five years postoperatively with patient-reported outcome measures, radiostereometric analysis, dual-energy X-ray absorptiometry, and conventional radiography. A total of 39 patients attended the follow-up visit at two years (primary outcome) and 35 patients at five years. The primary outcome was which hip the patient considered to have the best function at two years.Aims
Methods
This study aims to answer the following questions in patients with hip osteoarthritis (OA) who underwent total hip arthroplasty (THA): are patient-reported outcome measures (PROMs) affected by the location of the maximum severity of pain?; are PROMs affected by the presence of non-groin pain?; are PROMs affected by the severity of pain?; and are PROMs affected by the number of pain locations? We reviewed 336 hips (305 patients) treated with THA for hip OA from December 2016 to November 2019 using pain location/severity questionnaires, modified Harris Hip Score (mHHS), Hip Outcome Score (HOS), international Hip Outcome Tool (iHOT-12) score, and radiological analysis. Descriptive statistics, analysis of covariance (ANCOVA), and Spearman partial correlation coefficients were used.Aims
Methods
Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy.Aims
Methods
Total hip arthroplasty (THA) is a common procedure to address pain and enhance function in hip disorders such as osteoarthritis. Despite its success, postoperative patient recovery exhibits considerable heterogeneity. This study aimed to investigate whether patients follow distinct pain trajectories following THA and identify the patient characteristics linked to suboptimal trajectories. This retrospective cohort study analyzed THA patients at a large academic centre (NYU Langone Orthopedic Hospital, New York, USA) from January 2018 to January 2023, who completed the Patient-Reported Outcomes Measurement Information System (PROMIS) pain intensity questionnaires, collected preoperatively at one-, three-, six-, 12-, and 24-month follow-up times. Growth mixture modelling (GMM) was used to model the trajectories. Optimal model fit was determined by Bayesian information criterion (BIC), Vuong-Lo-Mendell-Rubin likelihood ratio test (VLMR-LRT), posterior probabilities, and entropy values. Association between trajectory groups and patient characteristics were measured by multinomial logistic regression using the three-step approach.Aims
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