Irradiation Behavior of Analgesic and Nonsteroidal Anti-Inflammatory Drug-Loaded UHMWPE for Joint Replacement.

Local delivery of pain medication can be a beneficial strategy to address pain management after joint replacement, as it can decrease systemic opioid usage, leading to less side and long-term effects. In this study, we used ultrahigh molecular weight polyethylene (UHMWPE), commonly employed as a bearing material for joint implants, to deliver a wide set of analgesics and the nonsteroidal anti-inflammatory drug tolfenamic acid. We blended the drugs with UHMWPE and processed the blend by compression molding and sterilization by low-dose gamma irradiation. We studied the chemical stability of the eluted drugs, drug elution, tensile properties, and wear resistance of the polymer blends before and after sterilization. The incorporation of bupivacaine hydrochloride and tolfenamic acid in UHMWPE resulted in either single- or dual-drug loaded materials that can be sterilized by gamma irradiation. These compositions were found to be promising for the development of clinically relevant drug-eluting implants for joint replacement.

Synergistic use of anti-inflammatory ketorolac and gentamicin to target staphylococcal biofilms.

BACKGROUND: While antibiotics remain our primary tools against microbial infection, increasing antibiotic resistance (inherent and acquired) is a major detriment to their efficacy. A practical approach to maintaining or reversing the efficacy of antibiotics is the use of other commonly used therapeutics, which show synergistic antibacterial action with antibiotics. Here, we investigated the extent of antibacterial synergy between the antibiotic gentamicin and the anti-inflammatory ketorolac regarding the dynamics of biofilm growth, the rate of acquired resistance, and the possible mechanism of synergy. METHODS: Control (ATCC 12600, ATCC 35984) and clinical strains (L1101, L1116) of Staphylococcus aureus and Staphylococcus epidermidis with varying antibiotic susceptibility profiles were used in this study to simulate implant-material associated low-risk and high-risk biofilms in vitro. The synergistic action of gentamicin sulfate (GS) and ketorolac tromethamine (KT), against planktonic staphylococcal strains were determined using the fractional inhibitory concentration measurement assay. Nascent (6 h) and established (24 h) biofilms were grown on 316L stainless steel plates and the synergistic biofilm eradication activity was determined and characterized using adherent bacteria count, minimum biofilm eradication concentration (MBEC) measurement for GS, visualization by live/dead imaging, scanning electron microscopy, gene expression of biofilm-associated genes, and bacterial membrane fluidity assessment. RESULTS: Gentamicin-ketorolac (GS-KT) combination demonstrated synergistic antibacterial action against planktonic Staphylococci. Control and clinical strains showed distinct biofilm growth dynamics and an increase in biofilm maturity was shown to confer further resistance to gentamicin for both 'low-risk' and 'high-risk' biofilms. The addition of ketorolac enhanced the antibiofilm activity of gentamicin against acquired resistance in staphylococcal biofilms. Mechanistic studies revealed that the synergistic action of gentamicin-ketorolac interferes with biofilm morphology and subverts bacterial stress response altering bacterial physiology, membrane dynamics, and biofilm properties. CONCLUSION: The results of this study have a significant impact on the local administration of antibiotics and other therapeutic agents commonly used in the prevention and treatment of orthopaedic infections. Further, these results warrant the study of synergy for the concurrent or sequential administration of non-antibiotic drugs for antimicrobial effect.

The efficacy of antibiotic-eluting material in a two-stage model of periprosthetic joint infection.

Periprosthetic joint infections occur in about 2% of patients who undergo primary total joint arthroplasty, a procedure performed over 1 million times in the United States. The gold standard of treatment is a two-stage revision. This study aimed to establish a two-stage procedure in a preclinical small animal model (rat) to test and compare the efficacy of an antibiotic-eluting material in managing infection. Joint replacement was simulated by transchondylarly implanting a polyethylene (PE) plug into the distal femur and a titanium screw in the proximal tibia. Methicillin-sensitive Staphylococcus aureus (MSSA) 108 CFU/mL was injected into the tibial canal and the joint space before wound closure. The control groups were killed on postoperative day (POD) 18 (n = 12) and on POD 42 (n = 4) to assess both early and later-stage outcomes in the control group. The test group underwent revision surgery on POD 18 for treatment using gentamicin-eluting polyethylene (GPE, n = 4) and was observed until POD 42 to evaluate the efficacy of treatment. Our results showed that the bone loss for the treatment group receiving GPE was significantly less than that of the control (p < 0.05), which was supported by the histology images and an AI-tool assisted infection rate evaluation. Gait metrics duty factor imbalance and hindlimb temporal symmetry were significantly different between the treatment and control groups on Day 42. This animal model was feasible for evaluating treatments for peri-prosthetic joint infections (PJI) with a revision surgery and specifically that revision surgery and local antibiotic treatment largely hindered the peri-prosthetic bone loss. Statement of clinical significance: This revision model of peri-prosthetic infection has the potential of comparatively evaluating prophylaxis and treatment strategies and devices. Antibiotic-eluting UHMWPE is devised as at tool in treating PJI while providing weight bearing and joint space preservation.

Di-cumyl peroxide cross-linked UHMWPE/vitamin-E blend for total joint arthroplasty implants.

Majority of ultrahigh molecular weight polyethylene (UHMWPE) medical devices used in total joint arthroplasty are cross-linked using gamma radiation to improve wear resistance. Alternative methods of cross-linking are urgently needed to replace gamma radiation due to rapid decline in its supply. Peroxide cross-linking is a candidate method with widespread industrial applications. Oxidative stability and biocompatibility, which are critical requirements for medical device applications, can be achieved using vitamin-E as an additive and by removing peroxide by-products through high-temperature melting, respectively. We investigated compression molded UHMWPE/vitamin-E/di-cumyl peroxide blends followed by high-temperature melting in inert gas as a material candidate for tibial knee inserts. Wear resistance increased and mechanical properties remained largely unchanged. Oxidation induction time was higher than most of the other clinically available formulations. The material passed the local-end point biocompatibility tests per ISO 10993. Compounds found in exhaustive extraction were of no concern with margin-of-safety values well above the accepted level, indicating a desirable toxicological risk profile. Statement of Clinical Significance: Peroxide cross-linked, vitamin-E stabilized, and high-temperature melted UHMWPE has recently been cleared for clinical use in tibial knee inserts. With all the salient characteristics needed in a material that can provide superior long-term performance in total joint patients, peroxide cross-linking can replace the gamma radiation cross-linking of UHMWPE.

Antibiotic-Loaded Ultrahigh Molecular Weight Polyethylenes.

The occurrence of periprosthetic joint infections (PJI) after total joint replacement constitutes a great burden for the patients and the healthcare system. Antibiotic-loaded polymethylmethacrylate (PMMA) bone cement is often used in temporary spacers during antibiotic treatment. PMMA is not a load-bearing solution and needs to be replaced by a functional implant. Elution from the ultrahigh molecular weight polyethylene (UHMWPE) bearing surface for drug delivery can combine functionality with the release of clinically relevant doses of antibiotics. In this study, the feasibility of incorporating a range of antibiotics into UHMWPE is investigated. Drug stability is assessed by thermo-gravimetric analysis and nuclear magnetic resonance spectroscopy. Drug-loaded UHMWPEs are prepared by compression molding, using eight antibiotics at different loading. The predicted intra-articular concentrations of drugs eluted from UHMWPE are above minimum inhibitory concentration for at least 3 weeks against Staphylococci, which are the major causative bacteria for PJI. The antibacterial efficacy is confirmed for samples covering 2% of a representative knee implant in vitro over 72 h, showing that a small fraction of the implant surface loaded with antibiotics may be sufficient against Staphylococci.

Synergistic use of anti-inflammatory ketorolac and gentamicin to target staphylococcal biofilms.

Background: While antibiotics remain our primary tools against microbial infection, increasing antibiotic resistance (inherent and acquired) is a major detriment to their efficacy. A practical approach to maintaining or reversing the efficacy of antibiotics is the use of other commonly used therapeutics, which show synergistic antibacterial action with antibiotics. Here, we investigated the extent of antibacterial synergy between the antibiotic gentamicin and the anti-inflammatory ketorolac regarding the dynamics of biofilm growth, the rate of acquired resistance, and the possible mechanism of synergy. Methods: Control (ATCC 12600, ATCC 35984) and clinical strains (L1101, L1116) of S. aureus and S. epidermidis with varying antibiotic susceptibility profiles were used in this study to simulate implant-material associated low-risk and high-risk biofilms in vitro. The synergistic action of gentamicin sulfate (GS) and ketorolac tromethamine (KT), against planktonic staphylococcal strains were determined using the fractional inhibitory concentration measurement assay. Nascent (6hr) and established (24hr) biofilms were grown on 316 stainless steel plates and the synergistic biofilm eradication activity was determined and characterized using adherent bacteria count, MBEC measurement for GS, gene expression of biofilm-associated genes, visualization by live/dead imaging, scanning electron microscopy, and bacterial membrane fluidity assessment. Results: Gentamicin-ketorolac combination demonstrated synergistic antibacterial action against planktonic Staphylococci. Control and clinical strains showed distinct biofilm growth dynamics and an increase in biofilm maturity was shown to confer further resistance to gentamicin for both 'low-risk' and 'high-risk' biofilms. The addition of ketorolac enhanced the antibiofilm activity of gentamicin against acquired resistance in staphylococcal biofilms. Mechanistic studies revealed that the synergistic action of gentamicin-ketorolac interferes with biofilm morphology and subverts bacterial stress response altering bacterial physiology, membrane dynamics, and biofilm properties. Conclusion: The results of this study have a significant impact on the local administration of antibiotics and other therapeutic agents commonly used in the prevention and treatment of orthopaedic infections. Further, these results warrant the study of synergy for the concurrent or sequential administration of non-antibiotic drugs for antimicrobial effect.

The use of deep learning enables high diagnostic accuracy in detecting syndesmotic instability on weight-bearing CT scanning.

PURPOSE: Delayed diagnosis of syndesmosis instability can lead to significant morbidity and accelerated arthritic change in the ankle joint. Weight-bearing computed tomography (WBCT) has shown promising potential for early and reliable detection of isolated syndesmotic instability using 3D volumetric measurements. While these measurements have been reported to be highly accurate, they are also experience-dependent, time-consuming, and need a particular 3D measurement software tool that leads the clinicians to still show more interest in the conventional diagnostic methods for syndesmotic instability. The purpose of this study was to increase accuracy, accelerate analysis time, and reduce interobserver bias by automating 3D volume assessment of syndesmosis anatomy using WBCT scans. METHODS: A retrospective study was conducted using previously collected WBCT scans of patients with unilateral syndesmotic instability. One-hundred and forty-four bilateral ankle WBCT scans were evaluated (48 unstable, 96 control). We developed three deep learning models for analyzing WBCT scans to recognize syndesmosis instability. These three models included two state-of-the-art models (Model 1-3D Convolutional Neural Network [CNN], and Model 2-CNN with long short-term memory [LSTM]), and a new model (Model 3-differential CNN LSTM) that we introduced in this study. RESULTS: Model 1 failed to analyze the WBCT scans (F1 score = 0). Model 2 only misclassified two cases (F1 score = 0.80). Model 3 outperformed Model 2 and achieved a nearly perfect performance, misclassifying only one case (F1 score = 0.91) in the control group as unstable while being faster than Model 2. CONCLUSIONS: In this study, a deep learning model for 3D WBCT syndesmosis assessment was developed that achieved very high accuracy and accelerated analytics. This deep learning model shows promise for use by clinicians to improve diagnostic accuracy, reduce measurement bias, and save both time and expenditure for the healthcare system. LEVEL OF EVIDENCE: II.

Dual-analgesic loaded UHMWPE exhibits synergistic antibacterial effects against Staphylococci.

Total joint arthroplasty is one of the most common surgeries in the United States, with almost a million procedures performed annually. Periprosthetic joint infections (PJI) remain the most devastating complications associated with total joint replacement. Effective antibacterial prophylaxis after primary arthroplasty could substantially reduce incidence rate of PJI. In the present study we propose to provide post-arthroplasty prophylaxis via dual-analgesic loaded ultra-high molecular weight polyethylene (UHMWPE). Our approach is based on previous studies that showed pronounced antibacterial activity of analgesic- and NSAID-loaded UHMWPE against Staphylococci. Here, we prepared bupivacaine/tolfenamic acid-loaded UHMWPE and assessed its antibacterial activity against Staphylococcus aureus and Staphylococcus epidermidis. Dual-drug loaded UHMWPE yielded an additional 1-2 log reduction of bacteria, when compared with single-drug loaded UHMWPE. Analysis of the drug elution kinetics suggested that the observed increase in antibacterial activity is due to the increased tolfenamic acid elution from dual-drug loaded UHMWPE. We showed that the increased fractal dimension of the drug domains in UHMWPE could be associated with increased drug elution, leading to higher antibacterial activity. Dual-analgesic loaded UHMWPE proposed here can be used as part of multi-modal antibacterial prophylaxis and promises substantial reduction in post-arthroplasty mortality and morbidity.

Does bone penetration of cement differ by cement type and application time-point?

Intrusion of cement into bone is often considered an indirect indicator for implant stability in cemented joint replacement procedures. However, the influence of cement type (different viscosities/manufacturers) and application time-point on penetration of cements continues to be debated. This study aimed to quantify the effect of cement type and application time-point on the depth of penetration using porcine tibial specimens. Four different bone cements were applied to 60 resected porcine cadaveric tibias at three time-points within the working window (1, 2, and 3 min after dough time). Penetration was measured using computed tomography, utilizing two rigorous methods from the literature and a newly proposed volumetric method. Application time-point had a strong influence on the thickness of the cement layer above the resected tibia (0.25, 0.49, 0.73 mm at the three time-points). No significant variation in penetration depth metrics with cement type or application time-point was found, except percentage area covered by cement at 2 mm depth. This metric was significantly different between 1 and 3-minute time-points (12% and 6% respectively). Time-point of application had a significant influence on thickness of pure cement layer over resected bone. However, penetration depth was not significantly affected by cement type or application time-point. The clinical significance of these findings is that it may be better to apply cement relatively soon after dough time to avoid excessively thick cement mantle between implant and bone. Further, the choice of cement type may have minimal impact on cement penetration, indicating that long standing principles of good cement application maybe more important.

Defining and predicting radiographic knee osteoarthritis progression: a systematic review of findings from the osteoarthritis initiative.

PURPOSE: The purposes of this systematic review were to (1) identify the commonly used definitions of radiographic KOA progression, (2) summarize the important associative risk factors for disease progression based on findings from the OAI study and (3) summarize findings from radiographic KOA progression prediction modeling studies regarding the characterization of progression and outcomes. METHODS: A systematic review was performed by conducting a literature search of definitions, risk factors and predictive models for radiographic KOA progression that utilized data from the OAI database. Radiographic progression was further characterized into "accelerated KOA" and "typical progression," as defined by included studies. RESULTS: Of 314 studies identified, 41 studies were included in the present review. Twenty-eight (28) studies analyzed risk factors associated with KOA progression, and 13 studies created or validated prediction models or risk calculators for progression. Kellgren-Lawrence (KL) grade based on radiographs was most commonly used to characterize KOA progression (50%), followed by joint space width (JSW) narrowing (32%) generally over 48 months. Risk factors with the highest odds ratios (OR) for progression included periarticular bone mineral density (OR 10.40), any knee injury within 1 year (OR 9.22) and baseline bone mineral lesions (OR 7.92). Nine prediction modeling studies utilized both clinical and structural risk factors to inform their models, and combined models outperformed purely clinical or structural models. CONCLUSION: The cumulative evidence suggests that combinations of structural and clinical risk factors may be able to predict radiographic KOA progression, particularly in patients with accelerated progression. Clinically relevant and feasible prediction models and risk calculators may provide valuable decision-making support when caring for patients at risk of KOA progression, although standardization in modeling and variable identification does not yet exist.

Do total hip arthroplasty polyethylene liners without free radicals oxidize in vivo or ex vivo?

Crosslinking substantially reduces the wear of ultra-high molecular weight polyethylene (UHMWPE) used in total hip arthroplasty (THA) but some reports have indicated that first generation liners manufactured without antioxidants may be vulnerable to in vivo oxidation. This study evaluated maximum oxidation using Fourier transform infrared spectroscopy per ASTM F2102-06ε1 and linear head penetration using a coordinate measuring machine among 66 revision-retrieved THA components with in vivo durations ranging from 0.02 to 24.6 years. These included 30 liners crosslinked with 5 Mrad of gamma radiation and then melted, 13 non-crosslinked, never-irradiated liners sterilized with gas plasma and 23 non-crosslinked, never-irradiated liners sterilized with ethylene oxide. All liners were vacuum-sealed and stored at -20°C prior to analysis with the exception of three retrievals of each material type that were stored in air for 9.9 to 21.5 years. All 57 vacuum-sealed and frozen retrievals demonstrated good oxidative stability with maximum oxidation indices (OIs) less than 1.0 and 75% (43/57) of these liners had maximum OIs less than 0.1. Linear penetration measurements were lower in the crosslinked liners compared to non-crosslinked retrievals. Although instances of oxidation and embrittlement were found after ex vivo storage in air among liners that did not have free radicals at the time of implantation, in vivo oxidation does not appear to be a clinical concern through the first decade of service for crosslinked liners and at up to 25 years after surgery for non-crosslinked liners.

Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study.

BACKGROUND: Early detection of postoperative complications, including organ failure, is pivotal in the initiation of targeted treatment strategies aimed at attenuating organ damage. In an era of increasing health-care costs and limited financial resources, identifying surgical patients at a high risk of postoperative complications and providing personalised precision medicine-based treatment strategies provides an obvious pathway for reducing patient morbidity and mortality. We aimed to leverage deep learning to create, through training on structured electronic health-care data, a multilabel deep neural network to predict surgical postoperative complications that would outperform available models in surgical risk prediction. METHODS: In this retrospective study, we used data on 58 input features, including demographics, laboratory values, and 30-day postoperative complications, from the American College of Surgeons (ACS) National Surgical Quality Improvement Program database, which collects data from 722 hospitals from around 15 countries. We queried the entire adult (≥18 years) database for patients who had surgery between Jan 1, 2012, and Dec 31, 2018. We then identified all patients who were treated at a large midwestern US academic medical centre, excluded them from the base dataset, and reserved this independent group for final model testing. We then randomly created a training set and a validation set from the remaining cases. We developed three deep neural network models with increasing numbers of input variables and so increasing levels of complexity. Output variables comprised mortality and 18 different postoperative complications. Overall morbidity was defined as any of 16 postoperative complications. Model performance was evaluated on the test set using the area under the receiver operating characteristic curve (AUC) and compared with previous metrics from the ACS-Surgical Risk Calculator (ACS-SRC). We evaluated resistance to changes in the underlying patient population on a subset of the test set, comprising only patients who had emergency surgery. Results were also compared with the Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) calculator. FINDINGS: 5 881 881 surgical patients, with 2941 unique Current Procedural Terminology codes, were included in this study, with 4 694 488 in the training set, 1 173 622 in the validation set, and 13 771 in the test set. The mean AUCs for the validation set were 0·864 (SD 0·053) for model 1, 0·871 (0·055) for model 2, and 0·882 (0·053) for model 3. The mean AUCs for the test set were 0·859 (SD 0·063) for model 1, 0·863 (0·064) for model 2, and 0·874 (0·061) for model 3. The mean AUCs of each model outperformed previously published performance metrics from the ACS-SRC, with a direct correlation between increasing model complexity and performance. Additionally, when tested on a subgroup of patients who had emergency surgery, our models outperformed previously published POTTER metrics. INTERPRETATION: We have developed unified prediction models, based on deep neural networks, for predicting surgical postoperative complications. The models were generally superior to previously published surgical risk prediction tools and appeared robust to changes in the underlying patient population. Deep learning could offer superior approaches to surgical risk prediction in clinical practice. FUNDING: The Novo Nordisk Foundation.

Patient-specific musculoskeletal models as a framework for comparing ACL function in unicompartmental versus bicruciate retaining arthroplasty.

Unicompartmental knee arthroplasty has been shown to provide superior functional outcomes compared to total knee arthroplasty and have motivated development of advanced implant designs including bicruciate retaining knee arthroplasty. However, few validated frameworks are available to directly compare the effect of implant design and surgical techniques on ligament function and joint kinematics. In the present study, the subject-specific lower extremity models were developed based on musculoskeletal modeling framework using force-dependent kinematics method, and validated against in vivo telemetric data. The experiment data of two subjects who underwent TKA were obtained from the SimTK "Grand Challenge Competition" repository, and integrated into the subject-specific lower extremity model. Five walking gait trials and three different knee implant models for each subject were used as partial inputs for the model to predict knee biomechanics for unicompartmental, bicruciate retaining, and total knee arthroplasty. The results showed no significant differences in the tibiofemoral contact forces or angular kinematic parameters between three groups. However, unicompartmental knee arthroplasty demonstrated significantly more posterior tibial location between 0% and 40% of the gait cycle (p < 0.017). Significant differences in range of tibiofemoral anterior/posterior translation and medial/lateral translation were also observed between unicompartmental and bicruciate retaining arthroplasty (p < 0.017). Peak values of anterior cruciate ligament forces differed between unicompartmental and bicruciate retaining arthroplasty from 10% to 30% of the gait cycle. Findings of this study indicate that unicompartmental and bicruciate retaining arthroplasty do not have identical biomechanics and point to the complementary role of anterior cruciate ligament and articular geometry in guiding knee function. Further, the patient-specific musculoskeletal model developed provides a reliable framework for assessing new implant designs, and effect of surgical techniques on knee biomechanics following arthroplasty.

Comparing the performance of a deep convolutional neural network with orthopedic surgeons on the identification of total hip prosthesis design from plain radiographs.

PURPOSE: A crucial step in the preoperative planning for a revision total hip replacement (THR) surgery is the accurate identification of the failed implant design, especially if one or more well-fixed/functioning components are to be retained. Manual identification of the implant design from preoperative radiographic images can be time-consuming and inaccurate, which can ultimately lead to increased operating room time, more complex surgery, and increased healthcare costs. METHOD: In this study, we present a novel approach to identifying THR femoral implants' design from plain radiographs using a convolutional neural network (CNN). We evaluated a total of 402 radiographs of nine different THR implant designs including, Accolade II (130 radiographs), Corail (89 radiographs), M/L Taper (31 radiographs), Summit (31 radiographs), Anthology (26 radiographs), Versys (26 radiographs), S-ROM (24 radiographs), Taperloc Standard Offset (24 radiographs), and Taperloc High Offset (21 radiographs). We implemented a transfer learning approach and adopted a DenseNet-201 CNN architecture by replacing the final classifier with nine fully connected neurons. Furthermore, we used saliency maps to explain the CNN decision-making process by visualizing the most important pixels in a given radiograph on the CNN's outcome. We also compared the CNN's performance with three board-certified and fellowship-trained orthopedic surgeons. RESULTS: The CNN achieved the same or higher performance than at least one of the surgeons in identifying eight of nine THR implant designs and underperformed all of the surgeons in identifying one THR implant design (Anthology). Overall, the CNN achieved a lower Cohen's kappa (0.78) than surgeon 1 (1.00), the same Cohen's kappa as surgeon 2 (0.78), and a slightly higher Cohen's kappa than surgeon 3 (0.76) in identifying all the nine THR implant designs. Furthermore, the saliency maps showed that the CNN generally focused on each implant's unique design features to make a decision. Regarding the time spent performing the implant identification, the CNN accomplished this task in ~0.06 s per radiograph. The surgeon's identification time varied based on the method they utilized. When using their personal experience to identify the THR implant design, they spent negligible time. However, the identification time increased to an average of 8.4 min (standard deviation 6.1 min) per radiograph when they used another identification method (online search, consulting with the orthopedic company representative, and using image atlas), which occurred in about 17% of cases in the test subset (40 radiographs). CONCLUSIONS: CNNs such as the one developed in this study can be used to automatically identify the design of a failed THR femoral implant preoperatively in just a fraction of a second, saving time and in some cases improving identification accuracy.

Natural language processing with deep learning for medical adverse event detection from free-text medical narratives: A case study of detecting total hip replacement dislocation.

BACKGROUND: Accurate and timely detection of medical adverse events (AEs) from free-text medical narratives can be challenging. Natural language processing (NLP) with deep learning has already shown great potential for analyzing free-text data, but its application for medical AE detection has been limited. METHOD: In this study, we developed deep learning based NLP (DL-NLP) models for efficient and accurate hip dislocation AE detection following primary total hip replacement from standard (radiology notes) and non-standard (follow-up telephone notes) free-text medical narratives. We benchmarked these proposed models with traditional machine learning based NLP (ML-NLP) models, and also assessed the accuracy of International Classification of Diseases (ICD) and Current Procedural Terminology (CPT) codes in capturing these hip dislocation AEs in a multi-center orthopaedic registry. RESULTS: All DL-NLP models outperformed all of the ML-NLP models, with a convolutional neural network (CNN) model achieving the best overall performance (Kappa = 0.97 for radiology notes, and Kappa = 1.00 for follow-up telephone notes). On the other hand, the ICD/CPT codes of the patients who sustained a hip dislocation AE were only 75.24% accurate. CONCLUSIONS: We demonstrated that a DL-NLP model can be used in largescale orthopaedic registries for accurate and efficient detection of hip dislocation AEs. The NLP model in this study was developed with data from the most frequently used electronic medical record (EMR) system in the U.S., Epic. This NLP model could potentially be implemented in other Epic-based EMR systems to improve AE detection, and consequently, quality of care and patient outcomes.

Leveraging subject-specific musculoskeletal modeling to assess effect of anterior cruciate ligament retaining total knee arthroplasty during walking gait.

Bi-cruciate retaining total knee arthroplasty has several potential advantages including improved anteroposterior knee stability compared to contemporary posterior cruciate-retaining total knee arthroplasty. However, few studies have explored whether there is significant differences of knee biomechanics following bi-cruciate retaining total knee arthroplasty compared to posterior cruciate-retaining total knee arthroplasty. In the present study, subject-specific lower extremity musculoskeletal multi-body dynamics models for bi-cruciate retaining, bi-cruciate retaining without anterior cruciate ligament, and posterior cruciate-retaining total knee arthroplasty were developed based on the musculoskeletal modeling framework using force-dependent kinematics method and validated against in vivo telemetric data. The experiment data of two subjects who underwent total knee arthroplasty were obtained for the SimTK "Grand Challenge Competition" repository, and integrated into the musculoskeletal model. Five walking gait trials for each subject were used as partial inputs for the model to predict the knee biomechanics for bi-cruciate retaining, bi-cruciate retaining without anterior cruciate ligament, and posterior cruciate-retaining total knee arthroplasty. The results revealed significantly greater range of anterior/posterior tibiofemoral translation, and significantly more posterior tibial location during the early phase of gait and more anterior tibial location during the late phase of gait were found in bi-cruciate retaining total knee arthroplasty without anterior cruciate ligament when compared to the bi-cruciate retaining total knee arthroplasty. No significant differences in tibiofemoral contact forces, rotations, translations, and ligament forces between bi-cruciate retaining and posterior cruciate-retaining total knee arthroplasty during normal walking gait, albeit slight differences in range of tibiofemoral internal/external rotation and anterior/posterior translation were observed. The present study revealed that anterior cruciate ligament retention has a positive effect on restoring normal knee kinematics in bi-cruciate retaining total knee arthroplasty. Preservation of anterior cruciate ligament in total knee arthroplasty and knee implant designs interplay each other and both contribute to restoring normal knee kinematics in different types of total knee arthroplasty. Further evaluation of more demanding activities and subject data from patients with bi-cruciate retaining and posterior cruciate-retaining total knee arthroplasty via musculoskeletal modeling may better highlight the role of the anterior cruciate ligament and its stabilizing influence.

Addressing prosthetic joint infections via gentamicin-eluting UHMWPE spacer.

AIMS: We propose a state-of-the-art temporary spacer, consisting of a cobalt-chrome (CoCr) femoral component and a gentamicin-eluting ultra-high molecular weight polyethylene (UHMWPE) tibial insert, which can provide therapeutic delivery of gentamicin, while retaining excellent mechanical properties. The proposed implant is designed to replace conventional spacers made from bone cement. METHODS: Gentamicin-loaded UHMWPE was prepared using phase-separated compression moulding, and its drug elution kinetics, antibacterial, mechanical, and wear properties were compared with those of conventional gentamicin-loaded bone cement. RESULTS: Gentamicin-loaded UHMWPE tibial components not only eradicated planktonic Staphylococcus aureus, but also prevented colonization of both femoral and tibial components. The proposed spacer possesses far superior mechanical and wear properties when compared with conventional bone cement spacers. CONCLUSION: The proposed gentamicin-eluting UHMWPE spacer can provide antibacterial efficacy comparable with currently used bone cement spacers, while overcoming their drawbacks. The novel spacer proposed here has the potential to drastically reduce complications associated with currently used bone cement spacers and substantially improve patients' quality of life during the treatment. Cite this article: Bone Joint J 2020;102-B(6 Supple A):151-157.

Synergistic antibacterial effects of analgesics and antibiotics against Staphylococcus aureus.

The local use of analgesics and antibiotics is common during the treatment of periprosthetic joint infection (PJI). The effect of nonantimicrobial drugs on antibacterial activity is underappreciated in clinical practice. This study focuses on the novel assessment of the combined antibacterial effects of commonly used analgesics and antibiotics against methicillin-sensitive Staphylococcus aureus (MSSA)-pathogen associated with most PJIs. We identified that bupivacaine/lidocaine and ketorolac/gentamicin combinations yielded fractional inhibitory concentration indices below 0.4, indicative of synergistic antibacterial effect. Time-kill curves were used for in-depth characterization of the synergy, and the obtained results demonstrated pronounced synergistic effects of bupivacaine/lidocaine and ketorolac/gentamicin combinations against MSSA.

Detecting total hip replacement prosthesis design on plain radiographs using deep convolutional neural network.

Identifying the design of a failed implant is a key step in the preoperative planning of revision total joint arthroplasty. Manual identification of the implant design from radiographic images is time-consuming and prone to error. Failure to identify the implant design preoperatively can lead to increased operating room time, more complex surgery, increased blood loss, increased bone loss, increased recovery time, and overall increased healthcare costs. In this study, we present a novel, fully automatic and interpretable approach to identify the design of total hip replacement (THR) implants from plain radiographs using deep convolutional neural network (CNN). CNN achieved 100% accuracy in the identification of three commonly used THR implant designs. Such CNN can be used to automatically identify the design of a failed THR implant preoperatively in just a few seconds, saving time and improving the identification accuracy. This can potentially improve patient outcomes, free practitioners' time, and reduce healthcare costs.

Radioprotection and cross-linking of allograft bone in the presence of vitamin E.

Bone allografts are the preferred method for bone augmentation in over 500,000 orthopedic surgical procedures in the US. Sterilization by ionizing radiation is the most effective method of minimizing the bioburden of bone allografts; however, radiation causes chain scission of collagen, resulting in the reduction of the allografts' mechanical strength. In this study, we doped bone allografts with vitamin E as radioprotectant using a novel two-step process to protect the collagen architecture against radiation damage and to preserve the mechanical strength of the construct. In addition, combining the radioprotectant with a cross-linking agent further minimized collagen degradation and further preserved the mechanical strength of the allografts. Both vitamin E and combined vitamin E/genipin-treated allograft were less cytotoxic to both osteoblasts and osteoclasts when compared to irradiated-only allografts. Host bone-allograft unionization was faster in a rat calvaria defect model with vitamin E-treated and combined vitamin E and genipin-treated allograft when compare to irradiated-only allografts. This method can enable the efficient and uniform radioprotective treatment of bone allograft of desired shapes for sterilization with improved mechanical strength and biointegration.