Aims. This Delphi study assessed the challenges of diagnosing soft-tissue knee injuries (STKIs) in acute settings among orthopaedic healthcare stakeholders. Methods. This modified e-Delphi study consisted of three rounds and involved 32 orthopaedic healthcare stakeholders, including physiotherapists, emergency nurse practitioners, sports medicine physicians, radiologists, orthopaedic registrars, and orthopaedic consultants. The perceived importance of diagnostic components relevant to STKIs included patient and external risk factors, clinical signs and symptoms, special clinical tests, and diagnostic imaging methods. Each round required scoring and ranking various items on a ten-point Likert scale. The items were refined as each round progressed. The study produced rankings of perceived importance across the various diagnostic components. Results. In Round 1, the study revealed widespread variability in stakeholder opinions on diagnostic components of STKIs. Round 2 identified patterns in the perceived importance of specific items within each diagnostic component. Round 3 produced rankings of perceived item importance within each diagnostic component. Noteworthy findings include the challenges associated with accurate and readily available diagnostic methods in acute care settings, the consistent acknowledgment of the importance of adopting a patient-centred approach to diagnosis, and the transition from divergent to convergent opinions between Rounds 2 and 3. Conclusion. This study highlights the potential for a paradigm shift in acute STKI diagnosis, where variability in the understanding of STKI diagnostic components may be addressed by establishing a uniform, evidence-based framework for evaluating these injuries. Cite this article: Bone Jt Open 2024;5(11):984–991

Aims. To explore key stakeholder views around feasibility and acceptability of trials seeking to prevent post-traumatic osteoarthritis (PTOA) following knee injury, and provide guidance for next steps in PTOA trial design. Methods. Healthcare professionals, clinicians, and/or researchers (HCP/Rs) were surveyed, and the data were presented at a congress workshop. A second and related survey was then developed for people with joint damage caused by knee injury and/or osteoarthritis (PJDs), who were approached by a UK Charity newsletter or Oxford involvement registry. Anonymized data were collected and analyzed in Qualtrics. Results. Survey responses (n = 19 HCP/Rs, 39 PJDs) supported studies testing pharmacological agents preventing PTOA. All HCP/Rs and 30/31 (97%) PJDs supported the development of new treatments that improved or delayed knee symptoms and damage to knee structure. PJDs thought that improving structural knee damage was more important than knee symptoms. Both groups found studies more acceptable as expected future benefit and risk of PTOA increased. All drug delivery routes were acceptable. Workshop participants (around n = 60) reflected survey views. Discussions suggested that stratifying using molecular testing for likely drug response appeared to be more acceptable than using characteristics such as sex, age, and BMI. Conclusion. Our findings supported PTOA drug intervention studies, including situations where there is low risk of disease, no expected benefit of treatment, and frequent treatment administration. PJDs appeared less risk-averse than HCP/Rs. This work reinforces the benefits of consensus and involvement work in the co-creation of PTOA drug trial design. Involvement of key stakeholders, such as PJDs with different risks of OA and regulatory representatives, are critical for trial design success. Cite this article: Bone Joint Res 2024;13(9):513–524

Anterior cruciate ligament (ACL) injuries are among the most common and debilitating knee injuries in professional athletes with an incidence in females up to eight-times higher than their male counterparts. ACL injuries can be career-threatening and are associated with increased risk of developing knee osteoarthritis in future life. The increased risk of ACL injury in females has been attributed to various anatomical, developmental, neuromuscular, and hormonal factors. Anatomical and hormonal factors have been identified and investigated as significant contributors including osseous anatomy, ligament laxity, and hamstring muscular recruitment. Postural stability and impact absorption are associated with the stabilizing effort and stress on the ACL during sport activity, increasing the risk of noncontact pivot injury. Female patients have smaller diameter hamstring autografts than males, which may predispose to increased risk of re-rupture following ACL reconstruction and to an increased risk of chondral and meniscal injuries. The addition of an extra-articular tenodesis can reduce the risk of failure; therefore, it should routinely be considered in young elite athletes. Prevention programs target key aspects of training including plyometrics, strengthening, balance, endurance and stability, and neuromuscular training, reducing the risk of ACL injuries in female athletes by up to 90%. Sex disparities in access to training facilities may also play an important role in the risk of ACL injuries between males and females. Similarly, football boots, pitches quality, and football size and weight should be considered and tailored around females’ characteristics. Finally, high levels of personal and sport-related stress have been shown to increase the risk of ACL injury which may be related to alterations in attention and coordination, together with increased muscular tension, and compromise the return to sport after ACL injury. Further investigations are still necessary to better understand and address the risk factors involved in ACL injuries in female athletes. Cite this article: Bone Jt Open 2024;5(2):94–100

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Multiligament knee injuries (MLKI) are devastating injuries that can result in significant morbidity and time away from sport. There remains considerable variation in strategies employed for investigation, indications for operative intervention, outcome reporting, and rehabilitation following these injuries. At present no study has yet provided a comprehensive overview evaluating the extent, range, and overall summary of the published literature pertaining to MLKI. Our aim is to perform a methodologically rigorous scoping review, mapping the literature evaluating the diagnosis and management of MLKI.

Aims. The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA). Methods. Synovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA. Results. PLS-DA produced a streamlined biomarker model with excellent sensitivity (95%), specificity (98.4%), and reliability (97.4%). The eight-biomarker model produced a fingerprint for esOA comprising type IIA procollagen N-terminal propeptide (PIIANP), tissue inhibitor of metalloproteinase (TIMP)-1, a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS-4), monocyte chemoattractant protein (MCP)-1, interferon-γ-inducible protein-10 (IP-10), and transforming growth factor (TGF)-β3. Receiver operating characteristic (ROC) analysis demonstrated excellent discriminatory accuracy: area under the curve (AUC) being 0.970 for esOA, 0.957 for knee injury, and 1 for inflammatory arthritis. All ten validation test patients were classified correctly as esOA (accuracy 100%; reliability 100%) by the biomarker model. Conclusion. SF analysis coupled with machine learning produced a partially validated biomarker model with cohort-specific fingerprints that accurately and reliably discriminated esOA from knee injury and inflammatory arthritis with almost 100% efficacy. The presented findings and approach represent a new biomarker concept and potential diagnostic tool to stage disease in therapy trials and monitor the efficacy of such interventions. Cite this article: Bone Joint Res 2020;9(9):623–632

Aims. A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty (HA) do not achieve an improvement as high as the minimal clinically important difference (MCID), i.e. do not achieve a meaningful improvement. Using three patient-reported outcome measures (PROMs), our aim was: 1) to assess machine learning (ML), the simple pre-surgery PROM score, and logistic-regression (LR)-derived performance in their prediction of whether patients undergoing HA or KA achieve an improvement as high or higher than a calculated MCID; and 2) to test whether ML is able to outperform LR or pre-surgery PROM scores in predictive performance. Methods. MCIDs were derived using the change difference method in a sample of 1,843 HA and 1,546 KA patients. An artificial neural network, a gradient boosting machine, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic net, random forest, LR, and pre-surgery PROM scores were applied to predict MCID for the following PROMs: EuroQol five-dimension, five-level questionnaire (EQ-5D-5L), EQ visual analogue scale (EQ-VAS), Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), and Knee injury and Osteoarthritis Outcome Score-Physical Function Short-form (KOOS-PS). Results. Predictive performance of the best models per outcome ranged from 0.71 for HOOS-PS to 0.84 for EQ-VAS (HA sample). ML statistically significantly outperformed LR and pre-surgery PROM scores in two out of six cases. Conclusion. MCIDs can be predicted with reasonable performance. ML was able to outperform traditional methods, although only in a minority of cases. Cite this article: Bone Joint Res 2023;12(9):512–521

Aims. The Coronal Plane Alignment of the Knee (CPAK) classification has been developed to predict individual variations in inherent knee alignment. The impact of preoperative and postoperative CPAK classification phenotype on the postoperative clinical outcomes of total knee arthroplasty (TKA) remains elusive. This study aimed to examine the effect of postoperative CPAK classification phenotypes (I to IX), and their pre- to postoperative changes on patient-reported outcome measures (PROMs). Methods. A questionnaire was administered to 340 patients (422 knees) who underwent primary TKA for osteoarthritis (OA) between September 2013 and June 2019. A total of 231 patients (284 knees) responded. The ­Knee Society Score 2011 (KSS 2011), Knee injury and Osteoarthritis Outcome Score-12 (KOOS-12), and Forgotten Joint Score-12 (FJS-12) were used to assess clinical outcomes. Using preoperative and postoperative anteroposterior full-leg radiographs, the arithmetic hip-knee-ankle angle (aHKA) and joint line obliquity (JLO) were calculated and classified based on the CPAK classification. To investigate the impact on PROMs, multivariable regression analyses using stepwise selection were conducted, considering factors such as age at surgery, time since surgery, BMI, sex, implant use, postoperative aHKA classification, JLO classification, and changes in aHKA and JLO classifications from preoperative to postoperative. Results. The preoperative and postoperative CPAK classifications were predominantly phenotype I (155 knees; 55%) and phenotype V (73 knees; 26%), respectively. The change in the preoperative to postoperative aHKA classification was a significant negative predictive factor for KOOS-12 and FJS-12, while postoperative apex proximal JLO was a significant negative predictive factor for KSS 2011 and KOOS-12. Conclusion. In primary TKA for OA, preoperative and postoperative CPAK phenotypes were associated with PROMs. Alteration in varus/valgus alignment from preoperative to postoperative was recognized as a negative predictive factor for both KOOS-12 and FJS-12. Moreover, the postoperative apex proximal JLO was identified as a negative factor for KSS 2011 and KOOS-12. Determining the target alignment for each preoperative phenotype with reproducibility could improve PROMs. Cite this article: Bone Joint J 2024;106-B(10):1059–1066

Aims. Tibial plateau fractures (TPFs) are complex injuries around the knee caused by high- or low-energy trauma. In the present study, we aimed to define the distribution and frequency of TPF lines using a 3D mapping technique and analyze the rationalization of divisions employed by frequently used classifications. Methods. In total, 759 adult patients with 766 affected knees were retrospectively reviewed. The TPF fragments on CT were multiplanar reconstructed, and virtually reduced to match a 3D model of the proximal tibia. 3D heat mapping was subsequently created by graphically superimposing all fracture lines onto a tibia template. Results. The cohort included 405 (53.4%) cases with left knee injuries, 347 (45.7%) cases with right knee injuries, and seven (0.9%) cases with bilateral injuries. On mapping, the hot zones of the fracture lines were mainly concentrated around the anterior cruciate ligament insertion, posterior cruciate ligament insertion, and the inner part of the lateral condyle that extended to the junctional zone between Gerdy’s tubercle and the tibial tubercle. Moreover, the cold zones were scattered in the posteromedial fragment, superior tibiofibular syndesmosis, Gerdy’s tubercle, and tibial tubercle. TPFs with different Orthopaedic Trauma Association/AO Foundation (OTA/AO) subtypes showed peculiar characteristics. Conclusion. TPFs occurred more frequently in the lateral and intermedial column than in the medial column. Fracture lines of tibial plateau occur frequently in the transition zone with marked changes in cortical thickness. According to 3D mapping, the four-column and nine-segment classification had a high degree of matching as compared to the frequently used classifications. Cite this article: Bone Joint Res 2020;9(6):258–267

Aims. The aim of this study was to compare patient-reported outcomes (PROMs) following isolated anterior cruciate ligament reconstruction (ACLR), with those following ACLR and concomitant meniscal resection or repair. Methods. We reviewed prospectively collected data from the UK National Ligament Registry for patients who underwent primary ACLR between January 2013 and December 2022. Patients were categorized into five groups: isolated ACLR, ACLR with medial meniscus (MM) repair, ACLR with MM resection, ACLR with lateral meniscus (LM) repair, and ACLR with LM resection. Linear regression analysis, with isolated ACLR as the reference, was performed after adjusting for confounders. Results. From 14,895 ACLR patients, 4,400 had two- or five-year Knee injury and Osteoarthritis Outcome Scores (KOOS) available. At two years postoperatively, the MM repair group demonstrated inferior scores in KOOS pain (β = −3.63, p < 0.001), symptoms (β = − 4.88, p < 0.001), ADL (β = − 2.43, p = 0.002), sport and recreation (β = − 5.23, p < 0.001), quality of life (QoL) (β = − 5.73, p < 0.001), and International Knee Documentation Committee (β = − 4.1, p < 0.001) compared with the isolated ACLR group. The LM repair group was associated with worse KOOS sports and recreation scores at two years (β = − 4.264, p < 0.001). At five years, PROMs were comparable between the groups. At five years, PROMs were comparable between the groups. Participants undergoing ACLR surgery within 12 weeks from index injury demonstrated superior PROMs at two and five years. Conclusion. Our study showed that MM repair, and to a lesser extent LM repairs in combination with ACLR, were associated with inferior patient-reported outcome measures (PROMs) compared to isolated ACLR at two years postoperatively, while meniscal resection groups exhibited comparable outcomes. However, by five years postoperation, no significant differences in PROMs were evident. Further longer-term, cross-sectional studies are warranted to investigate the outcomes of ACLR and concomitant meniscal surgery

Aims. The aim of this study was to report patient and clinical outcomes following robotic-assisted total knee arthroplasty (RA-TKA) at multiple institutions with a minimum two-year follow-up. Methods. This was a multicentre registry study from October 2016 to June 2021 that included 861 primary RA-TKA patients who completed at least one pre- and postoperative patient-reported outcome measure (PROM) questionnaire, including Forgotten Joint Score (FJS), Knee Injury and Osteoarthritis Outcomes Score for Joint Replacement (KOOS JR), and pain out of 100 points. The mean age was 67 years (35 to 86), 452 were male (53%), mean BMI was 31.5 kg/m. 2. (19 to 58), and 553 (64%) cemented and 308 (36%) cementless implants. Results. There were significant improvements in PROMs over time between preoperative, one- to two-year, and > two-year follow-up, with a mean FJS of 17.5 (SD 18.2), 70.2 (SD 27.8), and 76.7 (SD 25.8; p < 0.001); mean KOOS JR of 51.6 (SD 11.5), 85.1 (SD 13.8), and 87.9 (SD 13.0; p < 0.001); and mean pain scores of 65.7 (SD 20.4), 13.0 (SD 19.1), and 11.3 (SD 19.9; p < 0.001), respectively. There were eight superficial infections (0.9%) and four revisions (0.5%). Conclusion. RA-TKA demonstrated consistent clinical results across multiple institutions with excellent PROMs that continued to improve over time. With the ability to achieve target alignment in the coronal, axial, and sagittal planes and provide intraoperative real-time data to obtain balanced gaps, RA-TKA demonstrated excellent clinical outcomes and PROMs in this patient population. Cite this article: Bone Jt Open 2022;3(7):589–595

Patient-reported outcome measures (PROMs) are being used increasingly in total knee arthroplasty (TKA). We conducted a systematic review aimed at identifying psychometrically sound PROMs by appraising their measurement properties. Studies concerning the development and/or evaluation of the measurement properties of PROMs used in a TKA population were systematically retrieved via PubMed, Web of Science, Embase, and Scopus. Ratings for methodological quality and measurement properties were conducted according to updated COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology. Of the 155 articles on 34 instruments included, nine PROMs met the minimum requirements for psychometric validation and can be recommended to use as measures of TKA outcome: Oxford Knee Score (OKS); OKS–Activity and Participation Questionnaire (OKS-APQ); 12-item short form Knee Injury and Osteoarthritis Outcome (KOOS-12); KOOS Physical function Short form (KOOS-PS); Western Ontario and McMaster Universities Arthritis Index-Total Knee Replacement function short form (WOMAC-TKR); Lower Extremity Functional Scale (LEFS); Forgotten Joint Score (FJS); Patient’s Knee Implant Performance (PKIP); and University of California Los Angeles (UCLA) activity score. The pain and function subscales in WOMAC, as well as the pain, function, and quality of life subscales in KOOS, were validated psychometrically as standalone subscales instead of as whole instruments. However, none of the included PROMs have been validated for all measurement properties. Thus, further studies are still warranted to evaluate those PROMs. Use of the other 25 scales and subscales should be tempered until further studies validate their measurement properties. Cite this article: Bone Joint Res 2021;10(3):203–217

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The aim of this study was to compare the preinjury functional scores with the postinjury preoperative score and postoperative outcome scores following anterior cruciate ligament (ACL) reconstruction surgery (ACLR).

The October 2014 Research Roundup. 360 . looks at: unpicking syndesmotic injuries: CT scans evaluated; surgical scrub suits and sterility in theatre; continuous passive motion and knee injuries; whether pain at night is melatonin related;venous thromboembolic disease following spinal surgery; clots in lower limb plasters; immune-competent cells in Achilles tendinopathy; and infection in orthopaedics

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The aim of this study was to evaluate the cost-effectiveness of arthroscopic partial meniscectomy versus physical therapy plus optional delayed arthroscopic partial meniscectomy in young patients aged under 45 years with traumatic meniscal tears.

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The Single Assessment Numerical Evalution (SANE) score is a pragmatic alternative to longer patient-reported outcome measures (PROMs). The purpose of this study was to investigate the concurrent validity of the SANE and hip-specific PROMs in a generalized population of patients with hip pain at a single timepoint upon initial visit with an orthopaedic surgeon who is a hip preservation specialist. We hypothesized that SANE would have a strong correlation with the 12-question International Hip Outcome Tool (iHOT)-12, the Hip Outcome Score (HOS), and the Hip disability and Osteoarthritis Outcome Score (HOOS), providing evidence for concurrent validity of the SANE and hip-specific outcome measures in patients with hip pain.

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Focal knee arthroplasty is an attractive alternative to knee arthroplasty for young patients because it allows preservation of a large amount of bone for potential revisions. However, the mechanical behaviour of cartilage has not yet been investigated because it is challenging to evaluate in vivo contact areas, pressure, and deformations from metal implants. Therefore, this study aimed to determine the contact pressure in the tibiofemoral joint with a focal knee arthroplasty using a finite element model.

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Implantation of ultra-purified alginate (UPAL) gel is safe and effective in animal osteochondral defect models. This study aimed to examine the applicability of UPAL gel implantation to acellular therapy in humans with cartilage injury.

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction.

Cite this article: Bone Joint Res 2023;12(7):447–454.

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This study compared patient-reported outcomes of three total knee arthroplasty (TKA) designs from one manufacturer: one cruciate-retaining (CR) design, and two cruciate-sacrificing designs, anterior-stabilized (AS) and posterior-stabilized (PS).

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This study aimed to investigate the role and mechanism of meniscal cell lysate (MCL) in fibroblast-like synoviocytes (FLSs) and osteoarthritis (OA).