Aims. Glenoid bone loss can be a challenging problem when revising a shoulder arthroplasty. Precise pre-operative planning based on plain radiographs or CT scans is essential. We have investigated a new radiological classification system to describe the degree of medialisation of the bony glenoid and that will indicate the amount of bone potentially available for supporting a glenoid component. It depends on the relationship between the most medial part of the articular surface of the glenoid with the base of the coracoid process and the spinoglenoid notch: it classifies the degree of bone loss into three types. It also attempts to predict the type of glenoid reconstruction that may be possible (impaction bone grafting, structural grafting or simple non-augmented arthroplasty) and gives guidance about whether a pre-operative CT scan is indicated. Patients and Methods. Inter-method reliability between plain radiographs and CT scans was assessed retrospectively by three independent observers using data from 39 randomly selected patients. . Inter-observer reliability and test-retest reliability was tested on the same cohort using Cohen's kappa statistics. Correlation of the type of glenoid with the Constant score and its pain component was analysed using the Kruskal-Wallis method on data from 128 patients. Anatomical studies of the scapula were reviewed to explain the findings. Results. Excellent inter-method reliability, inter-observer and test-retest reliability were seen. The system did not correlate with the Constant score, but correlated well with its pain component. . Take home message: Our system of classification is a helpful guide to the degree of glenoid bone loss when embarking on revision shoulder arthroplasty. Cite this article: Bone Joint J 2016;98-B:374–80

Aims. Classifying trochlear dysplasia (TD) is useful to determine the treatment options for patients suffering from patellofemoral instability (PFI). There is no consensus on which classification system is more reliable and reproducible for the purpose of guiding clinicians’ management of PFI. There are also concerns about the validity of the Dejour Classification (DJC), which is the most widely used classification for TD, having only a fair reliability score. The Oswestry-Bristol Classification (OBC) is a recently proposed system of classification of TD, and the authors report a fair-to-good interobserver agreement and good-to-excellent intraobserver agreement in the assessment of TD. The aim of this study was to compare the reliability and reproducibility of these two classifications. Methods. In all, six assessors (four consultants and two registrars) independently evaluated 100 axial MRIs of the patellofemoral joint (PFJ) for TD and classified them according to OBC and DJC. These assessments were again repeated by all raters after four weeks. The inter- and intraobserver reliability scores were calculated using Cohen’s kappa and Cronbach’s α. Results. Both classifications showed good to excellent interobserver reliability with high α scores. The OBC classification showed a substantial intraobserver agreement (mean kappa 0.628; p < 0.005) whereas the DJC showed a moderate agreement (mean kappa 0.572; p < 0.005). There was no significant difference in the kappa values when comparing the assessments by consultants with those by registrars, in either classification system. Conclusion. This large study from a non-founding institute shows both classification systems to be reliable for classifying TD based on axial MRIs of the PFJ, with the simple-to-use OBC having a higher intraobserver reliability score than that of the DJC. Cite this article: Bone Jt Open 2023;4(7):532–538

Abstract. Purpose. Intracanal rib head penetration is a well-known entity in dystrophic scoliotic curves in neurofibromatosis type 1. There is potential for spinal cord injury if this is not recognised and managed appropriately. No current CT-based classification system is currently in use to quantify rib head penetration. This study aims to propose and evaluate a novel CT-based classification for rib head penetration primarily for neurofibromatosis but which can also be utilised in other conditions of rib head penetration. Materials and methods. The grading was developed as four grades: normal rib head (RH) position—Grade 0, subluxed ext-racanal RH position—Grade 1, RH at pedicle—Grade 2, intracanal RH—Grade 3. Grade 3 was further classified depending on the head position in the canal divided into thirds. Rib head penetration into proximal third (from ipsilateral side)—Grade 3A, into the middle third—Grade 3B and into the distal third—Grade 3C. Seventy-five axial CT images of Neurofibromatosis Type 1 patients in the paediatric age group were reviewed by a radiologist and a spinal surgeon independently to assess interobserver and intraobserver agreement of the novel CT classification. Agreement analysis was performed using the weighted Kappa statistic. Results. There was substantial interobserver correlation with mean Kappa score (k = 0.8, 95% CI 0.7–0.9) and near perfect intraobserver Kappa of 1.0 (95% CI 0.9–1.0) and 0.9 (95% CI 0.9–1.0) for the two readers. Conclusion. The novel CT-based classification quantifies rib head penetration which aids in management planning

Classifying trochlear dysplasia (TD) is useful to determine the treatment options for patients suffering from patellofemoral instability (PFI). There is no consensus on which classification system is more reliable and reproducible for this purpose to guide clinicians in order to treat PFI. There are also concerns about validity of the Dejour classification (DJC), which is the most widely used classification for TD, having only a fair reliability score. The Oswestry-Bristol classification (OBC) is a recently proposed system of classification of TD and the authors report a fair-to-good interobserver agreement and good-to-excellent intra-observer agreement in the assessment of TD. The aim of this study was to compare the reliability and reproducibility of these two classifications. 6 assessors (4 consultants and 2 registrars) independently evaluated 100 magnetic resonance axial images of the patella-femoral joint for TD and classified them according to OBC and DJC. These assessments were again repeated by all raters after 4 weeks. The inter and intra-observer reliability scores were calculated using Cohen's kappa and Cronbach's alpha. Both classifications showed good to excellent interobserver reliability with high alpha scores. The OBC classification showed a substantial intra-observer agreement (mean kappa 0.628)[p<0.005] whereas the DJC showed a moderate agreement (mean kappa 0.572) [p<0.005]. There was no significant difference in the kappa values when comparing the assessments by consultants to those by registrars, in either classification systems. This large study from a non-founding institute shows both classification systems to be reliable for classifying TD based on magnetic resonance axial images of the patella-femoral joint, with the simple to use OBC having a higher intra-observer reliability score compared to the DJC

Abstract. Purpose. No clinical CT based classification system is currently in use for Lumbar Foraminal Stenosis. MRI scanners are not easily available, are expensive and may be contraindicated in an increasing number of patients. This study aims to propose and evaluate the reproducibility of a novel CT based classification for lumbar foraminal stenosis. Materials and Methods. The grading was developed as 4 grades. Normal foramen – Grade 0, Anteroposterior(AP)/Superoinferior (SI)(single plane) fat compression – Grade 1, Both AP/SI compression (two planes) – Grade 2 (both AP and SI) without distortion of nerve root, Grade 2 with distortion of nerve root – Grade 3. 800 lumbar foramen of a cohort of 100 random patients over the age of 60 who had undergone both CT and MRI scans were reviewed by two radiologists independently to assess agreement of the novel CT classification against the MRI based grading system of Lee et al. Interobserver(n=400) and intraobserver agreement(n=160) was also evaluated. Agreement analysis was performed using the Weighted Kappa statistic. Results. 100 patients (M:F = 45:55) with a mean age of 68.5 years (range 60 – 83 years were included in the study. The duration between CT and MRI scans was 98 days(range 0 – 540, SD – 108). There was good correlation between CT and MRI with Kappa scores (k=0.81) and intraobserver Kappa of 0.89 and 0.98 for the two readers. Conclusion. The novel CT based classification correlates well with the MRI grading system and can safely and accurately replace it where required

Aims. This study aimed to evaluate the clinical application of the PJI-TNM classification for periprosthetic joint infection (PJI) by determining intraobserver and interobserver reliability. To facilitate its use in clinical practice, an educational app was subsequently developed and evaluated. Methods. A total of ten orthopaedic surgeons classified 20 cases of PJI based on the PJI-TNM classification. Subsequently, the classification was re-evaluated using the PJI-TNM app. Classification accuracy was calculated separately for each subcategory (reinfection, tissue and implant condition, non-human cells, and morbidity of the patient). Fleiss’ kappa and Cohen’s kappa were calculated for interobserver and intraobserver reliability, respectively. Results. Overall, interobserver and intraobserver agreements were substantial across the 20 classified cases. Analyses for the variable ‘reinfection’ revealed an almost perfect interobserver and intraobserver agreement with a classification accuracy of 94.8%. The category 'tissue and implant conditions' showed moderate interobserver and substantial intraobserver reliability, while the classification accuracy was 70.8%. For 'non-human cells,' accuracy was 81.0% and interobserver agreement was moderate with an almost perfect intraobserver reliability. The classification accuracy of the variable 'morbidity of the patient' reached 73.5% with a moderate interobserver agreement, whereas the intraobserver agreement was substantial. The application of the app yielded comparable results across all subgroups. Conclusion. The PJI-TNM classification system captures the heterogeneity of PJI and can be applied with substantial inter- and intraobserver reliability. The PJI-TNM educational app aims to facilitate application in clinical practice. A major limitation was the correct assessment of the implant situation. To eliminate this, a re-evaluation according to intraoperative findings is strongly recommended. Cite this article: Bone Joint Res 2024;13(1):19–27

Aim. To classify Fracture-related Infection (FRI) allowing comparison of clinical studies and to guide decision-making around the main surgical treatment concepts. Method. An international group of FRI experts met in Lisbon, June 2022 and proposed a new FRI classification. A core group met during the EBJIS Meeting in Graz, 2022 and on-line, to determine the preconditions, purpose, primary factors for inclusion, format and the detailed description of the elements of an FRI Classification. Results. Historically, FRI was classified by time from injury alone (early, delayed or late). Time produces pathophysiological changes which affect the bone, the soft-tissues and the patient general health, over a continuum. No definitive cut-off is therefore possible. Also, in several studies, time was not identified as an independent predictor of outcome. The most important primary factors were characteristics of the fracture (F), relevant systemic co-morbidities of the patient (R) and impairment of the soft-tissue envelope (I). These factors determine FRI severity, choice of treatment method and are predictors of outcome. For the fracture (F), the state of healing, the potential for bone healing and the presence or absence of a bone defect are critical factors. Co-morbidities are listed and the degree of end-organ damage is important (R). The ability to close the wound directly or the need for soft tissue reconstruction determines the impairment of the soft tissue component (I). Hence the FRI Classification was designed. The final proposal of the FRI Classification is presented here. The new classification has five stages; from simple cases of infected healed fractures, in healthy individuals with good soft tissues (Stage 1), through unhealed fractures with variable potential for bone healing (Stages 2, 3 or 4) to Stage 5, with no limb-sparing or reconstructive options. For instance, the need for a free flap (I4), over a well-healed fracture (F1), in a patient with 2 co-morbidities (R2) gives a classification of F1R2I4 for that patient. Conclusions. This novel approach to FRI classification builds on previous work in osteomyelitis, PJI and chronic medical conditions. It focusses attention on the elements of the disease which need treatment. It now requires validation in large patient cohorts. On behalf of the FRI Classification Consensus Group

Aims. The purpose of this study was to develop a convolutional neural network (CNN) for fracture detection, classification, and identification of greater tuberosity displacement ≥ 1 cm, neck-shaft angle (NSA) ≤ 100°, shaft translation, and articular fracture involvement, on plain radiographs. Methods. The CNN was trained and tested on radiographs sourced from 11 hospitals in Australia and externally validated on radiographs from the Netherlands. Each radiograph was paired with corresponding CT scans to serve as the reference standard based on dual independent evaluation by trained researchers and attending orthopaedic surgeons. Presence of a fracture, classification (non- to minimally displaced; two-part, multipart, and glenohumeral dislocation), and four characteristics were determined on 2D and 3D CT scans and subsequently allocated to each series of radiographs. Fracture characteristics included greater tuberosity displacement ≥ 1 cm, NSA ≤ 100°, shaft translation (0% to < 75%, 75% to 95%, > 95%), and the extent of articular involvement (0% to < 15%, 15% to 35%, or > 35%). Results. For detection and classification, the algorithm was trained on 1,709 radiographs (n = 803), tested on 567 radiographs (n = 244), and subsequently externally validated on 535 radiographs (n = 227). For characterization, healthy shoulders and glenohumeral dislocation were excluded. The overall accuracy for fracture detection was 94% (area under the receiver operating characteristic curve (AUC) = 0.98) and for classification 78% (AUC 0.68 to 0.93). Accuracy to detect greater tuberosity fracture displacement ≥ 1 cm was 35.0% (AUC 0.57). The CNN did not recognize NSAs ≤ 100° (AUC 0.42), nor fractures with ≥ 75% shaft translation (AUC 0.51 to 0.53), or with ≥ 15% articular involvement (AUC 0.48 to 0.49). For all objectives, the model’s performance on the external dataset showed similar accuracy levels. Conclusion. CNNs proficiently rule out proximal humerus fractures on plain radiographs. Despite rigorous training methodology based on CT imaging with multi-rater consensus to serve as the reference standard, artificial intelligence-driven classification is insufficient for clinical implementation. The CNN exhibited poor diagnostic ability to detect greater tuberosity displacement ≥ 1 cm and failed to identify NSAs ≤ 100°, shaft translations, or articular fractures. Cite this article: Bone Joint J 2024;106-B(11):1348–1360

Aims. The primary objective of this study was to develop a validated classification system for assessing iatrogenic bone trauma and soft-tissue injury during total hip arthroplasty (THA). The secondary objective was to compare macroscopic bone trauma and soft-tissues injury in conventional THA (CO THA) versus robotic arm-assisted THA (RO THA) using this classification system. Methods. This study included 30 CO THAs versus 30 RO THAs performed by a single surgeon. Intraoperative photographs of the osseous acetabulum and periacetabular soft-tissues were obtained prior to implantation of the acetabular component, which were used to develop the proposed classification system. Interobserver and intraobserver variabilities of the proposed classification system were assessed. Results. The BOne trauma and Soft-Tissue Injury classification system in total Hip arthroplasty (BOSTI Hip) grades osseous acetabular trauma and periarticular muscle damage during THA. The classification system has an interclass correlation coefficient of 0.90 (95% CI 0.86 to 0.93) for interobserver agreement and 0.89 (95% CI 0.84 to 0.93) for intraobserver agreement. RO THA was associated with improved BOSTI Hip scores (p = 0.002) and more pristine osseous surfaces in the anterior superior (p = 0.001) and posterior superior (p < 0.001) acetabular quadrants compared with CO THA. There were no differences between the groups in relation to injury to the gluteus medius (p = 0.084), obturator internus (p = 0.241), piriformis (p = 0.081), superior gamellus (p = 0.116), inferior gamellus (p = 0.132), quadratus femoris (p = 0.208), and vastus lateralis (p = 0.135), but overall combined muscle injury was reduced in RO THA compared with CO THA (p = 0.023). Discussion. The proposed BOSTI Hip classification provides a reproducible grading system for stratifying iatrogenic bone trauma and soft-tissue injury during THA. RO THA was associated with improved BOSTI Hip scores, more pristine osseous acetabular surfaces, and reduced combined periarticular muscle injury compared with CO THA. Further research is required to understand if these intraoperative findings translate to differences in clinical outcomes between the treatment groups. Cite this article: Bone Joint J 2024;106-B(9):898–906

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

Dysmorphic pelves are a known risk factor for malpositioned iliosacral screws. Improved understanding of pelvic morphology will minimise the risk of screw misplacement, neurovascular injuries and failed fixation. Existing classifications for sacral anatomy are complex and impractical for clinical use. We propose a CT-based classification using variations in pelvic anatomy to predict the availability of transosseous corridors across the sacrum. The classification aims to refine surgical planning which may reduce the risk of surgical complications. The authors postulated 4 types of pelves. The “superior most point of the sacroiliac joint” (sSIJ) typically corresponds with the mid-lower half of the L5 vertebral body. Hence, “the anterior cortex of L5” (L5. a. ) was divided to reference 3 distinct pelvic groups. A 4. th. group is required to represent pelves with a lumbosacral transitional vertebra. The proposed classification:. A – sSIJ is above the midpoint of L5. a. B – sSIJ is between the midpoint and the lowest point of L5. a. C – sSIJ is below the lowest point of L5. a. D – pelves with a lumbosacral transitional vertebra. Specific measures such as the width of the S1 and S2 axial and coronal corridors and the S1 lateral mass angles were used to differentiate between pelvic types. Three-hundred pelvic CT scans were classified into their respective types. Analysis of the specific measures mentioned above illustrated the significant difference between each pelvic type. Changes in the size of S1 and S2 axial corridors formed a pattern that was unique for each pelvic type. The intra- and inter-observer ratings were 0.97 and 0.95 respectively. Distinct relationships between the sizes of S1 and S2 axial corridors informed our recommendations on trans-sacral or iliosacral fixation, number and orientation of screws for each pelvic type. This classification utilises variations in the posterior pelvic ring to offer a planning guide for the insertion of iliosacral screws

Aims. The Coronal Plane Alignment of the Knee (CPAK) classification is a simple and comprehensive system for predicting pre-arthritic knee alignment. However, when the CPAK classification is applied in the Asian population, which is characterized by more varus and wider distribution in lower limb alignment, modifications in the boundaries of arithmetic hip-knee-ankle angle (aHKA) and joint line obliquity (JLO) should be considered. The purposes of this study were as follows: first, to propose a modified CPAK classification based on the actual joint line obliquity (aJLO) and wider range of aHKA in the Asian population; second, to test this classification in a cohort of Asians with healthy knees; third, to propose individualized alignment targets for different CPAK types in kinematically aligned (KA) total knee arthroplasty (TKA). Methods. The CPAK classification was modified by changing the neutral boundaries of aHKA to 0° ± 3° and using aJLO as a new variable. Radiological analysis of 214 healthy knees in 214 Asian individuals was used to assess the distribution and mean value of alignment angles of each phenotype among different classifications based on the coronal plane. Individualized alignment targets were set according to the mean lateral distal femoral angle (LDFA) and medial proximal tibial angle (MPTA) of different knee types. Results. A very high concentration, 191 from 214 individuals (89.3%), were found in knee types with apex distal JLO when the CPAK classification was applied in the Asian population. By using aJLO as a new variable, the high distribution percentage in knee types with apex distal JLO decreased to 125 from 214 individuals (58.4%). The most common types in order were Type II (n = 70; 32.7%), Type V (n = 55; 25.7%), and Type I (n = 46; 21.5%) in the modified CPAK classification. Conclusion. The modified CPAK classification corrected the uneven distribution when applying the CPAK classification in the Asian population. Setting individualized TKA alignment targets according to CPAK type may be a practical method to recreate optimal LDFA and MPTA in KA-TKA. Cite this article: Bone Jt Open 2022;3(3):211–217

Aims. The aim of this modified Delphi process was to create a structured Revision Hip Complexity Classification (RHCC) which can be used as a tool to help direct multidisciplinary team (MDT) discussions of complex cases in local or regional revision networks. Methods. The RHCC was developed with the help of a steering group and an invitation through the British Hip Society (BHS) to members to apply, forming an expert panel of 35. We ran a mixed-method modified Delphi process (three rounds of questionnaires and one virtual meeting). Round 1 consisted of identifying the factors that govern the decision-making and complexities, with weighting given to factors considered most important by experts. Participants were asked to identify classification systems where relevant. Rounds 2 and 3 focused on grouping each factor into H1, H2, or H3, creating a hierarchy of complexity. This was followed by a virtual meeting in an attempt to achieve consensus on the factors which had not achieved consensus in preceding rounds. Results. The expert group achieved strong consensus in 32 out of 36 factors following the Delphi process. The RHCC used the existing Paprosky (acetabulum and femur), Unified Classification System, and American Society of Anesthesiologists (ASA) classification systems. Patients with ASA grade III/IV are recognized with a qualifier of an asterisk added to the final classification. The classification has good intraobserver and interobserver reliability with Kappa values of 0.88 to 0.92 and 0.77 to 0.85, respectively. Conclusion. The RHCC has been developed through a modified Delphi technique. RHCC will provide a framework to allow discussion of complex cases as part of a local or regional hip revision MDT. We believe that adoption of the RHCC will provide a comprehensive and reproducible method to describe each patient’s case with regard to surgical complexity, in addition to medical comorbidities that may influence their management. Cite this article: Bone Jt Open 2022;3(5):423–431

Distal radius fractures (DRFs) are one of the most common types of fracture and one which is often treated surgically. Standard X-rays are obtained for DRFs, and in most cases that have an intra-articular component, a routine CT is also performed. However, it is estimated that CT is only required in 20% of cases and therefore routine CT's results in the overutilisation of resources burdening radiology and emergency departments. In this study, we explore the feasibility of using deep learning to differentiate intra- and extra-articular DRFs automatically and help streamline which fractures require a CT. Retrospectively x-ray images were retrieved from 615 DRF patients who were treated with an ORIF at the Royal Brisbane and Women's Hospital. The images were classified into AO Type A, B or C fractures by three training registrars supervised by a consultant. Deep learning was utilised in a two-stage process: 1) localise and focus the region of interest around the wrist using the YOLOv5 object detection network and 2) classify the fracture using a EfficientNet-B3 network to differentiate intra- and extra-articular fractures. The distal radius region of interest (ROI) detection stage using the ensemble model of YOLO networks detected all ROIs on the test set with no false positives. The average intersection over union between the YOLO detections and the ROI ground truth was Error! Digit expected.. The DRF classification stage using the EfficientNet-B3 ensemble achieved an area under the receiver operating characteristic curve of 0.82 for differentiating intra-articular fractures. The proposed DRF classification framework using ensemble models of YOLO and EfficientNet achieved satisfactory performance in intra- and extra-articular fracture classification. This work demonstrates the potential in automatic fracture characterization using deep learning and can serve to streamline decision making for axial imaging helping to reduce unnecessary CT scans

The Revision Hip Complexity Classification (RHCC) was developed by modified Delphi system in 2022 to provide a comprehensive, reproducible framework for the multidisciplinary discussion of complex revision hip surgery. The aim of this study was to assess the validity, intra-relater and inter-relater reliability of the RHCC. Radiographs and clinical vignettes of 20 consecutive patients who had undergone revision of Total Hip Arthroplasty (THA) at our unit during the previous 12-month period were provided to observers. Five observers, comprising 3 revision hip consultants, 1 hip fellow and 1 ST3-8 registrar were familiarised with the RHCC. Each revision THA case was classified on two separate occasions by each observer, with a mean time between assessments of 42.6 days (24–57). Inter-observer reliability was assessed using the Fleiss™ Kappa statistic and percentage agreement. Intra-observer reliability was assessed using the Cohen Kappa statistic. Validity was assessed using percentage agreement and Cohen Kappa comparing observers to the RHCC web-based application result. All observers were blinded to patient notes, operation notes and post-operative radiographs throughout the process. Inter-observer reliability showed fair agreement in both rounds 1 and 2 of the survey (0.296 and 0.353 respectively), with a percentage agreement of 69% and 75%. Inter-observer reliability was highest in H3-type revisions with kappa values of 0.577 and 0.441. Mean intra-observer reliability showed moderate agreement with a kappa value of 0.446 (0.369 to 0.773). Validity percentage agreement was 44% and 39% respectively, with mean kappa values of 0.125 and 0.046 representing only slight agreement. This study demonstrates that classification using the RHCC without utilisation of the web-based application is unsatisfactory, showing low validity and reliability. Reliability was higher for more complex H3-type cases. The use of the RHCC web app is recommended to ensure the accurate and reliable classification of revision THA cases

Variations in pelvic anatomy are a major risk factor for misplaced percutaneous sacroiliac screws used to treat unstable posterior pelvic ring injuries. A better understanding of pelvic morphology improves preoperative planning and therefore minimises the risk of malpositioned screws, neurological or vascular injuries, failed fixation or malreduction. Hence a classification system which identifies the clinically important anatomical variations of the sacrum would improve communication among pelvic surgeons and inform treatment strategy. 300 Pelvic CT scans from skeletally mature trauma patients that did not have pre-existing posterior pelvic pathology were identified. Axial and coronal transosseous corridor widths at both S1 and S2 were recorded. Additionally, the S1 lateral mass angle were also calculated. Pelvises were classified based upon the sacroiliac joint (SIJ) height using the midpoint of the anterior cortex of L5 as a reference point. Four distinct types could be identified:. Type-A – SIJ height is above the midpoint of the anterior cortex of the L5 vertebra. Type-B – SIJ height is between the midpoint and the lowest point of the anterior cortex of the L5 vertebra. Type-C – SIJ height is below the lowest point of the anterior cortex of the L5 vertebra. Type-D – a subgroup for those with a lumbosacral transitional vertebra, in particular a sacralised L5. Differences in transosseous corridor widths and lateral mass angles between classification types were assessed using two-way ANOVAs. Type-B was the most common pelvic type followed by Type-A, Type-C, and Type-D. Significant differences in the axial and coronal corridors was observed for all pelvic types at each level. Lateral mass angles increased from Types-A to C, but were smaller in Type-D. This classification system offers a guide to surgeons navigating variable pelvic anatomy and understanding how it is associated with the differences in transosseous sacral corridors. It can assist surgeons’ preoperative planning of screw position, choice of fixation or the need for technological assistance

A number of classification systems exist for posterior malleolus fractures of the ankle. The reliability of these classification systems remains unclear. The primary aim of this study was to evaluate the reliability of three commonly utilised fracture classification systems of the posterior malleolus. 60 patients across 2 hospitals sustaining an unstable ankle fracture with a posterior malleolus fragment were identified. All patients underwent radiographs and computed tomography of their injured ankle. 9 surgeons including pre-ST3 level, ST3-8 level, and consultant level applied the Haraguchi, Rammelt, and Mason & Molloy classifications to these patients, at two timepoints, at least 4 weeks apart. The order was randomised between assessments. Inter-rater reliability was assessed using Fleiss’ kappa and 95% confidence intervals (CI). Intra-rater reliability was assessed using Cohen's Kappa and standard error (SE). Inter-rater reliability (Fleiss’ Kappa) was calculated for the Haraguchi classification as 0.522 (95% CI 0.490 – 0.553), for the Rammelt classification as 0.626 (95% CI 0.600 – 0.652), and the Mason & Molloy classification as 0.541 (95% CI 0.514 – 0.569). Intra-rater reliability (Cohen's Kappa) was 0.764 (SE 0.034) for the Haraguchi, 0.763 (SE 0.031) for the Rammelt, 0.688 (SE 0.035) for the Mason & Molloy classification. This study reports the inter-rater and intra-rater reliability for three classification systems for posterior malleolus fractures. Based on definitions by Landis & Koch (1977), inter-rater reliability was rated as ‘moderate’ for the Haraguchi and Mason & Molloy classifications; and ‘substantial’ for the Rammelt classification. Similarly, the intra-rater reliability was rated as ‘substantial’ for all three classifications

Aims. Trochlear dysplasia is a significant risk factor for patellofemoral instability. The Dejour classification is currently considered the standard for classifying trochlear dysplasia, but numerous studies have reported poor reliability on both plain radiography and MRI. The severity of trochlear dysplasia is important to establish in order to guide surgical management. We have developed an MRI-specific classification system to assess the severity of trochlear dysplasia, the Oswestry-Bristol Classification (OBC). This is a four-part classification system comprising normal, mild, moderate, and severe to represent a normal, shallow, flat, and convex trochlear, respectively. The purpose of this study was to assess the inter- and intraobserver reliability of the OBC and compare it with that of the Dejour classification. Methods. Four observers (two senior and two junior orthopaedic surgeons) independently assessed 32 CT and axial MRI scans for trochlear dysplasia and classified each according to the OBC and the Dejour classification systems. Assessments were repeated following a four-week interval. The inter- and intraobserver agreement was determined by using Fleiss’ generalization of Cohen’s kappa statistic and S-statistic nominal and linear weights. Results. The OBC showed fair-to-good interobserver agreement and good-to-excellent intraobserver agreement (mean kappa 0.68). The Dejour classification showed poor interobserver agreement and fair-to-good intraobserver agreement (mean kappa 0.52). Conclusion. The OBC can be used to assess the severity of trochlear dysplasia. It can be applied in clinical practice to simplify and standardize surgical decision-making in patients with recurrent patella instability. Cite this article: Bone Joint J 2020;102-B(1):102–107

Aims. The evidence demonstrating the superiority of early MRI has led to increased use of MRI in clinical pathways for acute wrist trauma. The aim of this study was to describe the radiological characteristics and the inter-observer reliability of a new MRI based classification system for scaphoid injuries in a consecutive series of patients. Methods. We identified 80 consecutive patients with acute scaphoid injuries at one centre who had presented within four weeks of injury. The radiographs and MRI scans were assessed by four observers, two radiologists, and two hand surgeons, using both pre-existing classifications and a new MRI based classification tool, the Oxford Scaphoid MRI Assessment Rating Tool (OxSMART). The OxSMART was used to categorize scaphoid injuries into three grades: contusion (grade 1); unicortical fracture (grade 2); and complete bicortical fracture (grade 3). Results. In total there were 13 grade 1 injuries, 11 grade 2 injuries, and 56 grade 3 injuries in the 80 consecutive patients. The inter-observer reliability of the OxSMART was substantial (Kappa = 0.711). The inter-observer reliability of detecting an obvious fracture was moderate for radiographs (Kappa = 0.436) and MRI (Kappa = 0.543). Only 52% (29 of 56) of the grade 3 injuries were detected on plain radiographs. There were two complications of delayed union, both of which occurred in patients with grade 3 injuries, who were promptly treated with cast immobilization. There were no complications in the patients with grade 1 and 2 injuries and the majority of these patients were treated with early mobilization as pain allowed. Conclusion. This MRI based classification tool, the OxSMART, is reliable and clinically useful in managing patients with acute scaphoid injuries. Cite this article: Bone Jt Open 2022;3(11):913–920

Trochanteric femur fractures can be classified using the Jensen modification of the Evans’ classification or the AO/ASIF classification. This study compares the reproducibility of both classifications. Furthermore we evaluated the agreement on fracture stability, choice of osteosynthesis, fracture reduction and the accuracy of implant positioning. We used pre- and postoperative lateral and AP radiographs of 50 trochanteric femur fractures. The fractures were classified using both classifications with a three-month interval by five trauma surgeons and five residents. Inter-, and intra-observer variability was analysed using the multi-rater Fleiss’ kappa and the Cohen’ kappa tests. The AO/ASIF classification showed a kappa coefficient for the intra-observer agreement of 0.40 (SE 0.01). After leaving out classification-subgroups, AO/ASIF classification showed a coefficient of 0.68 (SE 0.02) and the Jensen classification a coefficient of 0.48 (SE 0.02). The kappa values of the intra-observer reliability of the AO/ASIF classification with and without subgroups were: 0.43 (SE 0.08) and 0.71 (SE 0.08) respectively. For the Jensen classification the kappa value was 0.56 (SE 0.09). Preoperative agreement on fracture stability and type of implant to be chosen showed kappa values of 0.39 (SE 0.05) and 0.65 (SE 0.04). Postoperative disagreement on the choice of implant was 15% (kappa 0.17, SE 0.08). Kappa values for postoperative fracture reduction and position of the implant were 0.29 (SE 0.09) and 0.22 (SE 0.05), respectively. Both the Jensen classification and the AO/ASIF classification showed poor reproducibility. However, without subgroups the AO/ASIF classification seemed more reliable. This study suggests that the definition of stability of trochanteric fractures remains controversial, which possibly complicates the choice of osteosynthesis. Refinement of the classifications or renewed definition of trochanteric fractures seems to be required