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Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_19 | Pages 33 - 33
22 Nov 2024
Kristensen N Manning L Lange J Davis J
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Aim. Periprosthetic Joint Infection (PJI) is a devastating complication in hip and knee joint arthroplasty. The “JS BACH” classification system was developed in 2021 to stratify the complexity of PJI, and more importantly, to act as a tool to guide referrals to specialist centers. The “JS BACH” classification has not been validated in an external cohort. This study aimed to do so using a large prospective cohort from Australia and New Zealand. Method. We applied the JS-BACH classification to the Prosthetic Joint Infection in Australia and New Zealand Observational (PIANO) cohort. This prospective study of newly diagnosed PJI collected 2-year outcome data from 653 participants enrolled in 27 hospitals. The definition of PJI treatment failure at 24 months was any of the following: death, clinical or microbiological signs of infection, destination prosthesis removed, or ongoing antibiotic use. Results. Individual cases were classified as per JS-BACH into “1 - uncomplicated” (n = 268), “2 - complex” (n = 330), and “3 - limited options” (n = 55). This cohort was similar to the original JS-BACH population in terms of baseline characteristics. However, there was a difference in complexity, with more DAIR procedures, fewer revision procedures, and a higher proportion of uncomplicated patients in the PIANO cohort. The risk of treatment failure correlated strongly with the JS-BACH category, with odds ratios (95% CI [confidence interval]) for category 2 versus 1 of 1.75 (1.24 to 2.47) and for category 3 versus 1 of 7.12 (3.42 to 16.02). Conclusions. Despite the PIANO study population being less complicated than the original derivation cohort, the JS-BACH classification showed a clear association with treatment failure in this large external cohort


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_19 | Pages 83 - 83
22 Nov 2024
Dudareva M Lama S Miyazaki K Scarborough C Wijendra A Tissingh E Kumin M Scarborough M McNally M
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Aim. The SOLARIO trial is a randomised controlled non-inferiority trial of antibiotic strategy for bone and joint infection. SOLARIO compares short or long post-operative systemic antibiotic duration, for patients with confirmed infections, who had local antibiotics implanted and no infected metalwork retained when undergoing surgery. This analysis compared systemic antibiotic use in the short (intervention) and long (standard of care) arms of the trial, in the 12 months after index surgery. Method. Data was collected prospectively from study randomisation, within 7 days of index surgery. All systemic antibiotics prescribed for the index infection were recorded, from health records and patient recall, at randomisation, 6 weeks, 3-6 months and 12 months after study entry. Start and end dates for each antibiotic were recorded. Results. 251 patients were randomised to short systemic antibiotics (up to 7 post-operative days) and 249 patients, to long systemic antibiotics. 5 participants in the short group and 2 participants in the long group withdrew from study follow-up. Complete data for all systemic antibiotics taken in the 12 months following surgery, were available for 237 participants in the short group and 236 participants in the long group. 80 participants across both groups were noted as having deviated from their assigned treatment strategy. Both groups received empiric antibiotics, predominantly vancomycin and meropenem, for up to 7 days after surgery. Considering each prescribed antibiotic as a separate duration (even when administered concurrently), participants assigned to standard care received a mean of 74.9 antibiotic-days. Participants assigned to short systemic antibiotics received a mean of 27.5 antibiotic-days in the 12 months after surgery. The most commonly prescribed antibiotics in both treatment groups were vancomycin and meropenem: these antibiotics accounted for 7.1 days prescribed per participant in the long group, and 6.3 days in the short group (p=0.37). Reasons for post-randomisation antibiotic prescribing in the short treatment group included later planned surgery, identification of bacteria requiring additional systemic antibiotics, and treatment of superficial wound infections. WHO AWaRe classification ‘watch’ and ‘reserve’ group antibiotics, such as ciprofloxacin, rifampicin, vancomycin and meropenem, accounted for 39.4 antibiotic-days per long group participant, and 16.5 antibiotic-days per short group participant. Conclusions. Considering the combined duration of all systemic antibiotics prescribed over 12 months, including those co-administered, participants in the short arm of the SOLARIO trial received considerably fewer days of all antibiotic classes, and particularly those antibiotics restricted in the WHO AWaRe classification (2021)


Bone & Joint Research
Vol. 13, Issue 11 | Pages 673 - 681
22 Nov 2024
Yue C Xue Z Cheng Y Sun C Liu Y Xu B Guo J

Aims. Pain is the most frequent complaint associated with osteonecrosis of the femoral head (ONFH), but the factors contributing to such pain are poorly understood. This study explored diverse demographic, clinical, radiological, psychological, and neurophysiological factors for their potential contribution to pain in patients with ONFH. Methods. This cross-sectional study was carried out according to the “STrengthening the Reporting of OBservational studies in Epidemiology” statement. Data on 19 variables were collected at a single timepoint from 250 patients with ONFH who were treated at our medical centre between July and December 2023 using validated instruments or, in the case of hip pain, a numerical rating scale. Factors associated with pain severity were identified using hierarchical multifactor linear regression. Results. Regression identified the following characteristics as independently associated with higher pain score, after adjustment for potential confounders: Association Research Circulation Osseous classification stage IIIa or IIIb, bone marrow oedema, grade 3 joint effusion, as well as higher scores on pain catastrophizing, anxiety, and central sensitization. The final model explained 69.7% of observed variance in pain scores, of which clinical and radiological factors explained 37%, while psychological and neurophysiological factors explained 24% and demographic factors explained 8.7%. Conclusion. Multidimensional characteristics jointly contribute to the severity of pain associated with ONFH. These findings highlight the need to comprehensively identify potential contributors to pain, and to personalize management and treatment accordingly. Cite this article: Bone Joint Res 2024;13(11):673–681


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_19 | Pages 38 - 38
22 Nov 2024
Barros BS Costa B Ribau A Vale J Sousa R
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Aim. Accurate diagnosis is key in correctly managing prosthetic joint infection(PJI). Shoulder PJI definition and diagnosis is challenging. Current PJI definitions, based overwhelmingly in hip/knee research, may not accurately diagnose shoulder PJI. Our aim is to compare the preoperative performance of two PJI definitions comparing it to definitive postoperative classification. Method. This is a retrospective study of patients who have undergone total shoulder revision surgery for infection between 2005 and 2022. Cases were classified using two different PJI definitions: a)the European Bone and Joint Infection Society (EBJIS) and; 2)the 2018 International Consensus Meeting(ICM) PJI specific shoulder definition. Preoperative classification was based on clinical features, inflammatory markers and synovial fluid leukocyte count and definitive classification also considered microbiology and histology results. Results. Preoperative and definitive PJI classification status of the 21 patients included were evaluated and is summarized in table 1. The shoulder specific 2018 ICM definition showed the highest agreement between preoperative and definitive classification (76.2%, k=0.153, p=0.006) compared to EBJIS (52.4%, k=0.205, p=0.006). In all cases, the classification was changed because of positive intraoperative microbiology (at least two identical isolates). Microbiology findings showed coagulase negative staphylococci, Staphyloccocus aureus and Cutibacterium acnes to be the most frequent. Four patients had polymicrobial infections. Conclusions. Both the EBJIS 2021 and 2018 ICM definitions have low accuracy in predicting shoulder PJI preoperatively. Clearly further studies with larger cohorts are in dire need focusing specifically on shoulder revision arthroplasty to improve on existing definitions. Caution is advised while extrapolating of criteria/thresholds recommended for hip/knee joints. For any tables or figures, please contact the authors directly


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_19 | Pages 7 - 7
22 Nov 2024
Unsworth A McNally M Young B Scarborough M
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Aims. Bone and joint infections cause significant morbidity, often requiring combination medical and surgical treatment. The presence of foreign material reduces the number of organisms required to cause an infection. The aim of this study was to assess whether there was a difference in the species of organism identified on culture in osteomyelitis compared to prosthetic joint infection. Method. This was a retrospective observational cohort study of patients that had surgical intervention for prosthetic joint infection or osteomyelitis with positive microbial culture between 2019 and 2022. Data including patient demographics, site of injury, BACH score for osteomyelitis and JS-BACH score for prosthetic joint infection, organism classification and antibiotic resistance to vancomycin and gentamicin were extracted from the medical record. Logistic and multiple regressions were used to adjust for potential confounding variables. Results. A total of 445 patients were included in the study; 267 patients with osteomyelitis or fracture-related infection and 177 patients with prosthetic joint infection. The patients with prosthetic joint infection were older (Mean age 70 for PJI; IQR 60-77 vs 56 for OM/FRI; IQR 39-64), more likely to be female (55.6% vs 26.2%) and had a higher BMI and ASA compared to those with osteomyelitis. Symptom duration tended to be longer in osteomyelitis/FRI (p<0.001). Staphylococcus aureus was the most common pathogen isolated in both osteomyelitis (155/267 (58.1%)) and prosthetic joint infection (85/177 (48.9%), followed by other Gram negative pathogens with 77/267 (28.8%) in osteomyelitis and 48/177 (27.1%) in prosthetic joint infection. On multivariate analysis, there was no difference between the rate of Staphylococcus aureus infection between the two groups. The rate of polymicrobial infection was higher in patients with osteomyelitis (92/267 (34.5%)) compared to prosthetic joint infection (38/177 (23.7%), however after adjustment for confounders there was no difference, p = 0.842. There was no difference in the presence of gentamicin resistant organisms or vancomycin resistant Gram positive organisms in osteomyelitis compared to prosthetic joint infection. Conclusion. Causative pathogens are similar in these two common forms of bone and joint infection. There was no significant difference in the identification, presence of polymicrobial infection or gentamicin and vancomycin resistance in organisms isolated in osteomyelitis compared to prosthetic joint infection. This may have implications for empiric antibiotic choice and local antibiotic therapy in the management of bone and joint infection


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_19 | Pages 86 - 86
22 Nov 2024
Lentini A Djoko J Putineanu D Tribak K Coyette M Yombi J Cornu O
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Aim. Bone infections often manifest with soft tissue complications such as severe scarring, fistulas, or ulcerations. Ideally, their management involves thorough debridement of infected bone and associated soft tissues, along with achieving stable bone structure, substantial tissue coverage, and long-term antibiotic therapy. The formation of a multidisciplinary team comprising orthopedic surgeons, plastic surgeons, and infectious disease specialists is essential in addressing the most complex cases. Method. We conducted a retrospective study during six years (2018-2023) at our university center. Focusing on the most challenging cases, we included patients with bone infections in the leg and/or foot requiring free flap reconstruction. Each patient underwent simultaneous bone debridement and reconstruction by the orthopedic team, alongside soft tissue debridement and free flap reconstruction by the plastic surgery team. Targeted antibiotic therapy for either 6 weeks (acute) or 12 weeks (chronic osteitis) was initiated based on intraoperative cultures. Additional procedures such as allografts, arthrodesis, or autografts were performed if necessary. We analyzed the rates of bone union, infection resolution, and limb preservation. Results. Forty-five patients were enrolled. Twenty-four patients (53.3%) had urgent indications (e.g., open infected fractures, osteitis, acute osteoarthritis, or wound dehiscence), while 21 (46.7%) underwent elective surgery (e.g., septic pseudarthrosis or chronic osteitis). Two patients underwent amputation due to flap failure (4.4%), and one patient was lost to follow-up. Follow-up of the remaining 42 patients averaged 28 months (range: 6–60 months). During this period, 35 patients (83.4%) experienced no recurrence of infection. Similarly, 35 patients (83.4%) achieved bone union. Overall, the rate of lower limb preservation was 93.3%. Conclusions. Managing bone infection coupled with soft tissue defects brings significant challenges. Although the majority of patients treated here belong to a complex framework based on the BACH classification, the outcomes achieved here appear to align with those of the simpler cases, thanks to optimal care with a dedicated septic ortho-plastic team. Our study demonstrates a notable success rate in treating infection, achieving bone consolidation, and preserving lower limb function


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_19 | Pages 18 - 18
22 Nov 2024
Gupta V Shahban S Petrie M Kimani P Kozdryk J Riemer B King R Westerman R Foguet P
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Aim. Predicting success of a Debridement, Antibiotics and Implant Retention (DAIR) procedure for Periprosthetic Joint Infection (PJI) remains a challenge. A failed DAIR might adversely affect the outcome of any future revision surgery for PJI. Hence, the ability to identify and optimise factors predictive of DAIR success would help target the procedure to the appropriate patient cohort and avoid unnecessary surgery for patients where a DAIR is unlikely to eradicate infection. Method. A retrospective review of our prospective Bone Infection Group database was performed to identify all patients who underwent a DAIR of their hip or knee arthroplasty. Diagnosis of PJI was confirmed using the Musculoskeletal Infection Society (MSIS) 2013 and the European Bone and Joint Infection Society (EBJIS) 2021 classification systems. DAIR surgery was grouped into “successful” or “unsuccessful” outcomes as per the MSIS working group outcome-reporting tool. Results. Sixty-Four consecutive patients with an acute PJI underwent a DAIR procedure between 2009 and 2020. Treatment was successful in 44 (69%). The chance of a successful DAIR was significantly greater if performed within one week of symptom onset compared to greater than one week duration (adjusted odds ratio (OR 0.11; p=0.027; 95% CI [0.02- 0.78]). The chances of a successful DAIR was not influenced by whether the surgeon was an arthroplasty or non-arthroplasty surgeon (OR 0.28; p=0.13; 95% CI [0.05- 1.48]). Isolated Streptococcus infection had a success rate of 100%; followed by Coagulasenegative Staphylococci 71% and Methicillin-susceptible Staphylococcus Aureus 65%. Polymicrobial infection had the worst outcome with a success rate of 47%. Conclusions. In our experience DAIR surgery performed within one week of symptom onset, significantly increased chances of successful infection eradication. Collaborative work is required to ensure arthroplasty patients access prompt appropriate surgical decision-making, remove barriers to early assessment and minimise delays to surgery


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_19 | Pages 34 - 34
22 Nov 2024
Seixas J Altoé LS Santos AC Ribau A Abreu M Carvalho A Pereira F Soares D Sousa R
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Aim. Determine therapeutic and prognostic value of three different prosthetic joint infections (PJI) staging systems – JS-Bach, McPherson and PJI-TNM. Method. Retrospective analysis of patients who received surgery for PJI between 2011 and 2022 at one single institution, including DAIR, 1-stage revision and 2-stage revision. We applied three staging systems - JS-Bach, McPherson, PJI-TNM – and categorize the results into A (less severe), B (intermediate) and C (most severe). Demographic data and comorbidities, anatomic location, type of treatment, recurrency of infection, final outcome and antibiogram were analyzed. Results. 186 patients were included, 112 (60%) were woman. Median age was 70 years old. 51% were submitted to DAIR, 10% to 1-stage revision and 39% to 2-stage revision. Recurrence of infection was found on 27% of patients after initial treatment. 10% died with complication related to PJI. Final status at last follow-up showed 96% of cases were ultimately free of infection at last follow-up. JS-BACH was associated with recurrence. All three staging systems were associated with final outcome. Conclusions. Despite all existing knowledge around risk factors for treatment failure of PJI, there is still a lack of a generally accepted classification system to accurately predict patient outcome. JS-BACH, McPherson and PJI-TNM are three different proposed classifications developed to predict clinical outcomes. To the best of our knowledge there are no studies directly comparing their performance. We retrospectively evaluated our cohort and found that all three correlated with final patient outcome but JS-BACH was the only who significantly correlated with infection recurrence after initial treatment


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_19 | Pages 74 - 74
22 Nov 2024
Erbeznik A Šturm AC Smrdel KS Triglav T Kocjancic B Pompe B Dolinar D Mavcic B Mercun A Kolar M Avsec K Papst L Vodicar PM
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Aim. To date, no ultimate diagnostic gold standard for prosthetic joint infections (PJI) has been established. In recent years, next generation sequencing (NGS) has emerged as a promising new tool, especially in culture-negative samples. In this prospective study, we performed metagenomic analysis using 16S rRNA V3-V4 amplicon NGS in samples from patients with suspected PJI. Methods. A total of 257 (187 culture-negative (CN) and 70 culture-positive (CP)) prospectively collected tissues and sonication fluid from 32 patients (56 revisions) were included. 16S rRNA V3-V4 amplicons were sequenced using Illumina's MiSeq (California, USA) followed by bioinformatic analysis using nf-core/ampliseq pipeline. Results. We successfully sequenced 255 samples and detected a total of 105 microorganisms. These were mainly environmental microorganisms present in a small number of reads (≤100), indicating possible contamination. Pseudomonas spp. (non-aeruginosa species) was detected most frequently in 73% (187/255) of samples. The test showed limitations in species classification and identified microorganisms mainly at genus level. Significant differences in the number of reads were observed when comparing CN (≤100) and CP (≥1000) samples. In two CP, no bacteria were identified with sequencing, which is probably due to low bacterial load (1 CFU. Haemophilus spp. was detected with a significant number of reads (≥10000) in five samples from a single patient, in whom infection was considered likely according to EBJIS criteria, changing it to confirmed infection. Staphylococcus spp. was identified with ≥10000 reads in two CNs from an individual who was receiving antibiotic treatment at the time, had clinical signs of infection, and had a confirmed infection with S. lugdunensis one month earlier. Cutibacterium spp. with 36% (93/257) and Staphylococcus spp. with 34% (87/257) were detected with a minimal number of reads (≤100) in several CN, indicating possible contamination with normal skin microbiota. In one patient, Facklamia spp., an opportunistic pathogen, was detected in two samples by sequencing, but not by culture. Conclusions. We consider 16S rRNA V3-V4 amplicon sequencing to be a promising tool; however, further studies are needed to clarify uncertainties regarding the interpretation of the results in combination with other criteria. Using this method, we were able to successfully confirm infection in two patients whose microbiological results were initially negative, leading to a change from likely to confirmed infection in one case. The thresholds and interpretation of the results are currently unclear, therefore the method is being used experimentally rather than diagnostically at the time of writing


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_19 | Pages 80 - 80
22 Nov 2024
Simon S Wouthuyzen-Bakker M Mitterer JA Gardete-Hartmann S Frank BJ Hofstaetter J
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Aim. It still remains unclear whether postoperative antibiotic treatment is advantageous in presumed aseptic revision-arthroplasties of the hip (rTHA) and knee (rTKA) with unexpected-positive-intraoperative-cultures (UPIC). The aim of this study was to evaluate if there is a difference in the septic and/or aseptic re-revision rate in patients with or without postoperative antibiotics. Method. In this retrospective propensity-score (PS) matched cohort-study we compared the re-revision rate and the microbiological spectrum in rTHA and rTKA treated with (AB-Group; n=70) and without (non-AB-Group; n=70) antibiotic treatment in patients with UPIC. Baseline covariates for PS-matching were type of revision, sex, Body-Mass-Index, age, Surgical-Site-Infection-Score, American-Society-of-Anesthesiologists-Classification, serum C-reactive-protein. All patients received routine antibiotic prophylaxis, but empiric AB treatment was started only in patients in the AB-Group. Post-operative treatment was decided on an individual basis according to the preference of the surgeon and the infectious disease specialist for a minimum duration of two weeks. In total, 90 rTHA (45 AB-Group, 45 in non-AB-Group) patients with UPICs and 50 rTKA (25 AB-Group, 25 in non-AB-Group) were included in the study. There was no significant variation in patient demographics. Results. After a median follow-up of 4.1 (IQR: 2.9-5.5) years after rTHA and rTKA, there was no higher re-revision rate (p=0.813) between the AB-group 10/70 (14.3%), and the non-AB-group 11/70 (15.7%). In the AB group, 4.3% (3/70) of patients underwent revision due to septic complications compared to 5.7% (4/70) in the non-AB group (survival log-rank: p=0.691). In total, 30/70 (42.9%) of patients in the AB-group and 23/70 (32.9%) of patients in the non-AB group were diagnosed as having an “infection likely” according to the PJI diagnostic criteria of EBJIS (p=0.223). All UPICs comprised low virulent microorganisms and were considered as a contaminant. In total, 68/70 (97.1%) of the patients in the AB-group received a dual antibiotic treatment for a mean duration of 41 (IQR: 23.5-56.5) days. Conclusion. Postoperative antibiotic treatment did not result in a decreased re-revision rate compared to non-antibiotic treatment in patients with UPIC in presumed aseptic rTHA and rTKA. UPICs with pathogens are likely to be a containment and therefore the classification of “infection likely” according to the EBJIS definition can be safely ignored


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_18 | Pages 53 - 53
14 Nov 2024
Fridberg M Rahbek O Husum H Bafor A Duch K Iobst C Kold S
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Introduction. Patients with external fixators are at risk of pin site infection. A more objective assessment of possible pin site infection is warranted, particularly for future home-based monitoring of pin sites. The aim was to determine if thermography can detect signs of inflammation around pin sites by 1) Establishing a maximum temperature cut-off value 2) Investigating the correlation between local temperature and visual signs of inflammation 3) Adjust for anatomical location and ambient room temperature. Method. This was a cross-sectional international multi-center study following STROBE guidelines. All patients with external ring-fixators scheduled for a visit in the out-patient clinic were eligible. Visual signs of inflammation were categorized using the Modified Gordon classification System (MGS, simplified sMGS). Thermographic imaging was done with an infrared camera (FLIR T540) and the maximum temperature within the ROI (MaxTp) was the primary outcome measure. Sample size and reliability were estimated. Cohen-Kappa, ROC-curve/AUC and Poisson regression were used for statistical analysis. Result. Data from 1970 pin sites were included. Inter-rater reliability of MGS was Kappa=0.79 and for MaxTp ICC=0.99 (95%CI: 0.99;0.99). Overall, a tendency of rising temperature with increasing sMGS was seen. The difference between sMGS=0 and sMGS>0 was significant. The performance of MaxTp as a screening tool to detect inflammation was reasonable with an AUC of 0.71 (95% CI: 0.65-0.76). The empirically optimal cut-off value was 34.1°C (Sensitivity=65%, Specificity=72%, Positive predictive value=23%, Negative Predictive value=94%). A 1°C increase in MaxTp increased the RR of visual signs of inflammation by a factor 1.5 (95% CI: 1.3; 1.7). Conclusion. We found a clinical positive association between the temperature at the pin site measured with thermography and visual signs of inflammation. The empirically optimal temperature cut-off value for inflammation screening was 34.1°C. Thermography may be a promising tool for a for a future point of care technology


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_18 | Pages 57 - 57
14 Nov 2024
Birkholtz F Eken M Boyes A Engelbrecht A
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Introduction. With advances in artificial intelligence, the use of computer-aided detection and diagnosis in clinical imaging is gaining traction. Typically, very large datasets are required to train machine-learning models, potentially limiting use of this technology when only small datasets are available. This study investigated whether pretraining of fracture detection models on large, existing datasets could improve the performance of the model when locating and classifying wrist fractures in a small X-ray image dataset. This concept is termed “transfer learning”. Method. Firstly, three detection models, namely, the faster region-based convolutional neural network (faster R-CNN), you only look once version eight (YOLOv8), and RetinaNet, were pretrained using the large, freely available dataset, common objects in context (COCO) (330000 images). Secondly, these models were pretrained using an open-source wrist X-ray dataset called “Graz Paediatric Wrist Digital X-rays” (GRAZPEDWRI-DX) on a (1) fracture detection dataset (20327 images) and (2) fracture location and classification dataset (14390 images). An orthopaedic surgeon classified the small available dataset of 776 distal radius X-rays (Arbeidsgmeischaft für Osteosynthesefragen Foundation / Orthopaedic Trauma Association; AO/OTA), on which the models were tested. Result. Detection models without pre-training on the large datasets were the least precise when tested on the small distal radius dataset. The model with the best accuracy to detect and classify wrist fractures was the YOLOv8 model pretrained on the GRAZPEDWRI-DX fracture detection dataset (mean average precision at intersection over union of 50=59.7%). This model showed up to 33.6% improved detection precision compared to the same models with no pre-training. Conclusion. Optimisation of machine-learning models can be challenging when only relatively small datasets are available. The findings of this study support the potential of transfer learning from large datasets to improve model performance in smaller datasets. This is encouraging for wider application of machine-learning technology in medical imaging evaluation, including less common orthopaedic pathologies


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_18 | Pages 70 - 70
14 Nov 2024
Cicione C Tilotta V Ascione A Giacomo GD Russo F Tryfonidou M Noel D Camus A Maitre CL Vadalà G
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Introduction. Low back pain (LBP) is a worldwide leading cause of disability. This preclinical study evaluated the safety of a combined advanced therapy medicinal product developed during the European iPSpine project (#825925) consisting of mesendoderm progenitor cells (MEPC), derived from human induced pluripotent stem cells, in combination with a synthetic poly(N-isopropylacrylamide) hydrogel (NPgel) in an ovine intervertebral disc degeneration (IDD) model. Method. IDD was induced through nucleotomy in 4 adult sheep, 5 lumbar discs each (n=20). After 5 weeks, 3 alternating discs were treated with NPgel (n=6) or NPgel+MEPC (n=6). Before sacrifice, animals were subjected to: MRI of lumbar spines (disc height and Pfirmann grading); blood sampling (hematological, biochemical, metabolic and lymphocyte/monocytes immunological). After 3 months the sheep were sacrificed. The spines were processed for: macroscopic morphology (Thompson grading), microscopic morphology (Histological grading), and glycosaminoglycan content (GAG, DMMB Assay). Furthermore, at sacrifice biodistribution of human MEPC was assessed by Alu-sequences quantification (qPCR) from three tissue samples of heart, liver, spleen, brain, lungs, and kidneys, and PBMCs collected to assess activation of systemic immune cells. To each evaluation, appropriate statistical analysis was applied. Result. Flow cytometry showed no induction of systemic activation of T cells or monocytes. Alu quantification did not give detection of any cells in any organ. Disc height index was slightly increased in discs treated with NPgel+MEPC. Pfirmann's and Thompson's classification showed that treatment with NPgel or NPgel+MEPC gave no adverse reactions. Histological grading showed similar degeneration in vertebrae treated with NPgel+MEPC or with NPgel alone. The amount of GAG was significantly increased in the nucleus pulposus following treatment with NPgel+MEPC compared to NPgel alone, in which a decrease was observed compared to untreated discs in both nucleus pulposus and annulus fibrosus. Conclusion. This study showed the safety of both NPgel+MEPC and NPgel treatments


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_18 | Pages 63 - 63
14 Nov 2024
Ritter D Bachmaier S Wijdicks C Raiss P
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Introduction. The increased prevalence of osteoporosis in the patient population undergoing reverse shoulder arthroplasty (RSA) results in significantly increased complication rates. Mainly demographic and clinical predictors are currently taken into the preoperative assessment for risk stratification without quantification of preoperative computed tomography (CT) data (e.g. bone density). It was hypothesized that preoperative CT bone density measures would provide objective quantification with subsequent classification of the patients’ humeral bone quality. Methods. Thirteen bone density parameters from 345 preoperative CT scans of a clinical RSA cohort represented the data set in this study. The data set was divided into testing (30%) and training data (70%), latter included an 8-fold cross validation. Variable selection was performed by choosing the variables with the highest descriptive value for each correlation clustered variables. Machine learning models were used to improve the clustering (Hierarchical Ward) and classification (Support Vector Machine (SVM)) of bone densities at risk for complications and were compared to a conventional statistical model (Logistic Regression (LR)). Results. Clustering partitioned this cohort (training data set) into a high bone density subgroup consisting of 96 patients and a low bone density subgroup consisting of 146 patients. The optimal number of clusters (n = 2) was determined based on optimization metrics. Discrimination of the cross validated classification model showed comparable performance for the training (accuracy=91.2%; AUC=0.967) and testing data (accuracy=90.5 %; AUC=0.958) while outperforming the conventional statistical model (Logistic Regression (LR)). Local interpretable model-agnostic explanations (LIME) were created for each patient to explain how the predicted output was achieved. Conclusion. The trained and tested model provides preoperative information for surgeons treating patients with potentially poor bone quality. The use of machine learning and patient-specific calibration showed that multiple 3D bone density scores improved accuracy for objective preoperative bone quality assessment


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_18 | Pages 118 - 118
14 Nov 2024
Schlauch A Shah I Crawford B Martin A Denisov A Tamer P Farrell B
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Introduction. Distal femur fractures around a total knee arthroplasty (TKA) are a growing problem for orthopaedic surgeons. The purpose of this study was to identify risks of reoperation for nonunion following open reduction and internal fixation of TKA periprosthetic distal femur fractures (PDFF). Method. Patients with PDFF (AO 33A-C[VB1, C1, D1], Su types 1-3) managed operatively with open reduction and internal fixation (ORIF) were retrospectively reviewed. Exclusion criteria were acute management with a distal femur replacement, less than 6 months of follow-up, and lack of injury or follow-up radiographs. The primary outcome measure was reoperation to achieve bony union. Comparisons were made between cases that did and did not require a reoperation to achieve union. Univariate analysis was used to identify factors to be analyzed in multivariate analysis to determine independent risk factors for the primary outcome. Result. A total of 77 patients met inclusion criteria. Union rate was 69/77 (89.6%). There were no differences between the groups for age, sex, BMI, comorbidities, Su classification, open injury, or mechanism of injury. Multivariate analysis identified risks for nonunion including post-operative malalignment (OR 1.41; CI 1.20-1.64; p<0.001), notching pre-operatively (OR 1.22; CI 1.04-1.42; p=0.012), presence of screws through fracture line (OR 1.28; CI 1.17-1.39; p<0.001), plate length <12 holes (OR 1.16; CI 1.02-1.33; p=0.024) and screw density greater than 0.4 (OR 2.18; CI 1.25-3.78; p=0.006). Conclusion. The reoperation rate to promote union was 10.4%. The study identified post-operative malalignment, notching pre-operatively, presence of screws through fracture line, plate length <12 holes, and proximal screw density greater than 40% as independent risk factors for nonunion


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_18 | Pages 60 - 60
14 Nov 2024
Asgari A Shaker F Fallahy MTP Soleimani M Shafiei SH Fallah Y
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Introduction. Shoulder arthroplasty (SA) has been performed with different types of implants, each requiring different replacement systems. However, data on previously utilized implant types are not always available before revision surgery, which is paramount to determining the appropriate equipment and procedure. Therefore, this meta-analysis aimed to evaluate the accuracy of the AI models in classifying SA implant types. Methods. This systematic review was conducted in Pubmed, Embase, SCOPUS, and Web of Science from inception to December 2023, according to PRISMA guidelines. Peer-reviewed research evaluating the accuracy of AI-based tools on upper-limb X-rays for recognizing and categorizing SA implants was included. In addition to the overall meta-analysis, subgroup analysis was performed according to the type of AI model applied (CNN (Convolutional neural network), non-CNN, or Combination of both) and the similarity of utilized datasets between studies. Results. 13 articles were eligible for inclusion in this meta-analysis (including 138 different tests assessing models’ efficacy). Our meta-analysis demonstrated an overall sensitivity and specificity of 0.891 (95% CI:0.866-0.912) and 0.549 (95% CI:0.532,0.566) for classifying implants in SA, respectively. The results of our subgroup analyses were as follows: CNN-subgroup: a sensitivity of 0.898 (95% CI:0.873-0.919) and a specificity of 0.554 (95% CI:0.537,0.570), Non-CNN subgroup: a sensitivity of 0.809 (95% CI:0.665-0.900) and specificity of 0.522 (95% CI:0.440,0.603), combined subgroup: a sensitivity of 0.891 (95% CI:0.752-0.957) and a specificity of 0.547 (95% CI:0.463,0.629). Studies using the same dataset demonstrated an overall sensitivity and specificity of 0.881 (95% CI:0.856-0.903) and 0.542 (95% CI:0.53,0.554), respectively. Studies that used other datasets showed an overall sensitivity and specificity of 0.995 (95% CI:969,0.999) and 0.678 (95% CI:0.234, 0.936), respectively. Conclusion. AI-based classification of shoulder implant types can be considered a sensitive method. Our study showed the potential role of using CNN-based models and different datasets to enhance accuracy, which could be investigated in future studies


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_18 | Pages 47 - 47
14 Nov 2024
Daneshvarhashjin N Debeer P Andersen MS Verhaegen F Scheys L
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Introduction. Assessment of the humeral head translation with respect to the glenoid joint, termed humeral head migration (HHM), is crucial in total shoulder arthroplasty pre-operative planning. Its assessment informs current classification systems for shoulder osteoarthritis as well as the evaluation of surgical correction. In current clinical practice, HHM assessment relies on computed-tomography (CT) imaging. However, the associated supine position might undermine its functional relevance as it does not reflect the weight-bearing condition with active muscle engagement associated with the upright standing position of most daily activities. Therefore, we assessed to what extent HHM in a supine position is associated with HHM in a range of functional arm positions. Method. 26 shoulder osteoarthritis patients and 12 healthy volunteers were recruited. 3D shapes of the humerus and scapula were reconstructed from their respective CT scans using an image processing software. 3. , and their CT-scan-based HHMs were measured. Furthermore, all subjects underwent low-dose biplanar radiography . 4. in four quasi-static functional arm positions while standing: relaxed standing, followed by 45 degrees of shoulder extension, flexion, and abduction. Using a previously validated method implemented in the programming platforms. 5. , 3D shapes were registered to the pairs of biplanar images for each arm position and the corresponding functional HHM was measured. Bivariate correlations were assessed between the CT-based HHM and each functional arm position. Result. HHM in 45 degrees of flexion and extension both showed significant and strong correlations (r>0.66 and P<0.01) with HHM assessed in the supine position. However, such a high correlation was not found for relaxed standing and 45 abduction. Conclusion. Although HHM in a supine position correlates with HHM in 45-degree extension and flexion, it is poorly associated with the HHM in abduction and relaxed standing. These results may suggest the inclusion of more functionally-relevant patient positioning toward better-informed shoulder arthroplasty planning. Acknowledgement. Funding from PRosPERos-II Project


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_18 | Pages 48 - 48
14 Nov 2024
Vadalà G Papalia GF Russo F Nardi N Ambrosio L Papalia R Denaro V
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Introduction. Intraoperative navigation systems for lumbar spine surgery allow to perform preoperative planning and visualize the real-time trajectory of pedicle screws. The aim of this study was to evaluate the deviation from preoperative planning and the correlations between screw deviation and accuracy. Method. Patients affected by degenerative spondylolisthesis who underwent posterior lumbar interbody fusion using intraoperative 3D navigation since April 2022 were included. Intraoperative cone-beam computed tomography (CBCT) was performed before screw planning and following implantation. The deviation from planning was calculated as linear, angular, and 3D discrepancies between planned and implanted screws. Accuracy and facet joint violation (FJV) were evaluated using Gertzbein-Robbins system (GRS) and Yson classification, respectively. Statistical analysis was performed using SPSS version28. One-way ANOVA followed by Bonferroni post-hoc tests were performed to evaluate the association between GRS, screw deviation and vertebral level. Statistical significance was set at p<0.05. Result. This study involved 34 patients, for a total of 154 pedicle screws. Mean age was 62.6±8.9 years. The mean two-dimensional screw tip deviation in mediolateral (ML), craniocaudal (CC), and anteroposterior (AP) was 2.6±2.45mm, 1.6±1.7mm, and 3.07±2.9mm, respectively. The mean screw tip 3D deviation was 5±3.3mm. The mean two-dimensional screw head deviation in ML, CC and AP was 1.83±1.8mm, 1.7±1.67mm and 3.6±3.1mm, respectively. The mean screw head 3D deviation was 4.94±3.2mm. 98% of screws were clinically acceptable (grade A+B), and grade 0 for FJV. Significant results were found between GRS and ML (p=0.005), AP (p=0.01) and 3D (p=0.003) tip deviations, and between GRS and AP and 3D head deviations (both p=0). Moreover, a significant correlation was found between GRS and vertebral level (p=0). Conclusion. Our results showed a reasonable rate of discrepancy between planned and positioned screws. However, accuracy was clinically acceptable in almost all cases. Therefore, pedicle screw fixation using intraoperative CBCT, 3D navigation and screw planning is safe and accurate


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_18 | Pages 50 - 50
14 Nov 2024
Birkholtz F Eken M Swanevelder M Engelbrecht A
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Introduction. Inaccurate identification of implants on X-rays may lead to prolonged surgical duration as well as increased complexity and costs during implant removal. Deep learning models may help to address this problem, although they typically require large datasets to effectively train models in detecting and classifying objects, e.g. implants. This can limit applicability for instances when only smaller datasets are available. Transfer learning can be used to overcome this limitation by leveraging large, publicly available datasets to pre-train detection and classification models. The aim of this study was to assess the effectiveness of deep learning models in implant localisation and classification on a lower limb X-ray dataset. Method. Firstly, detection models were evaluated on their ability to localise four categories of implants, e.g. plates, screws, pins, and intramedullary nails. Detection models (Faster R-CNN, YOLOv5, EfficientDet) were pre-trained on the large, freely available COCO dataset (330000 images). Secondly, classification models (DenseNet121, Inception V3, ResNet18, ResNet101) were evaluated on their ability to classify five types of intramedullary nails. Localisation and classification accuracy were evaluated on a smaller image dataset (204 images). Result. The YOLOv5s model showed the best capacity to detect and distinguish between different types of implants (accuracy: plate=82.1%, screw=72.3%, intramedullary nail=86.9%, pin=79.9%). Screw implants were the most difficult implant to detect, likely due to overlapping screw implants visible in the image dataset. The DenseNet121 classification model showed the best performance in classifying different types of intramedullary nails (accuracy=73.7%). Therefore, a deep learning model pipeline with the YOLOv5s and DenseNet121 was proposed for the most optimal performance of automating implants localisation and classification for a relatively small dataset. Conclusion. These findings support the potential of deep learning techniques in enhancing implant detection accuracy. With further development, AI-based implant identification may benefit patients, surgeons and hospitals through improved surgical planning and efficient use of theatre time


Orthopaedic Proceedings
Vol. 106-B, Issue SUPP_18 | Pages 58 - 58
14 Nov 2024
Bulut H Maestre M Tomey D
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Introduction. Unplanned reoperations (UROs) following corrective surgery for adult spinal deformity (ASD) present significant challenges for both patients and surgeons. Understanding the specific UROs types is crucial for improving patient outcomes and refining surgical strategies in ASD correction. Method. This retrospective analysis utilized data from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database spanning from 2017 to 2021. Patient information was extracted using specific CPT codes related to posterior pedicle fixation. Result. In a cohort of 1088 patients undergoing posterior spinal deformity corrections, we examined various preoperative factors to discern their correlation with reoperation prevalence. Our analysis revealed no statistically significant differences in reoperation prevalence concerning gender (male: 4.0%, p=0.131) or ethnicity (Hispanic: 4.2%, p=0.192). Similarly, no notable associations were identified for diabetes mellitus, smoking status, dyspnea, history of severe COPD, hypertension, ASA classification, or functional health status before surgery, with reoperation prevalences ranging from 3.2% to 8.8% and p-values spanning from 0.146 to 0.744. Overall, the reoperation prevalence within the entire cohort stood at 5.2% (55 cases). In terms of the types of reoperations investigated, spinal-related procedures emerged as the most prevalent, accounting for 43.7% (24 cases), followed closely by wound site revisions at 23.6% (13 cases). Additionally, gastrointestinal-related procedures and various other miscellaneous interventions, such as uroscopy, demonstrated reoperation prevalences of 7.2% (4 cases) and 25.5% (14 cases), respectively. Conclusion. our findings highlight the diverse spectrum of reoperation procedures encountered following posterior spinal deformity corrections, with wound site revisions and spinal-related interventions being the most prevalent categories. These results emphasize the complexity of managing UROs in spinal surgery and the need for tailored approaches and infection/incision protocols to address the specific challenges associated with each type of reoperation