Publications
46 results found
Hashim S, Jones G, 2024, Revision ACL reconstruction and medial unicompartmental knee replacement, Journal of Orthopaedic Case Reports, ISSN: 2250-0685
Failure of anterior cruciate ligament (ACL) reconstructive surgery often presents alongside progressive mono-compartment tibiofemoral arthrosis. A total knee arthroplasty (TKA) is the conventional treatment option for this scenario but is associated with high levels of dissatisfaction amongst this younger cohort. This case report outlines a 39-year-old male patient, who underwent revision anterior cruciate ligament reconstruction plus a medial unicompartmental knee replacement (UKA) as a single stage procedure. This is the first reported ACL revision with a simultaneous medial UKA and provides an alternative solution to a total knee arthroplasty in this younger cohort of patients.
Wang J, Hall TAG, Musbahi O, et al., 2023, Predicting hip-knee-ankle and femorotibial angles from knee radiographs with deep learning, Knee, Vol: 42, Pages: 281-288, ISSN: 0968-0160
BACKGROUND: Knee alignment affects the development and surgical treatment of knee osteoarthritis. Automating femorotibial angle (FTA) and hip-knee-ankle angle (HKA) measurement from radiographs could improve reliability and save time. Further, if HKA could be predicted from knee-only radiographs then radiation exposure could be reduced and the need for specialist equipment and personnel avoided. The aim of this research was to assess if deep learning methods could predict FTA and HKA angle from posteroanterior (PA) knee radiographs. METHODS: Convolutional neural networks with densely connected final layers were trained to analyse PA knee radiographs from the Osteoarthritis Initiative (OAI) database. The FTA dataset with 6149 radiographs and HKA dataset with 2351 radiographs were split into training, validation, and test datasets in a 70:15:15 ratio. Separate models were developed for the prediction of FTA and HKA and their accuracy was quantified using mean squared error as loss function. Heat maps were used to identify the anatomical features within each image that most contributed to the predicted angles. RESULTS: High accuracy was achieved for both FTA (mean absolute error 0.8°) and HKA (mean absolute error 1.7°). Heat maps for both models were concentrated on the knee anatomy and could prove a valuable tool for assessing prediction reliability in clinical application. CONCLUSION: Deep learning techniques enable fast, reliable and accurate predictions of both FTA and HKA from plain knee radiographs and could lead to cost savings for healthcare providers and reduced radiation exposure for patients.
Patil A, Kulkarni K, Xie S, et al., 2023, The accuracy of statistical shape models in predicting bone shape: a systematic review, International Journal of Medical Robotics and Computer Assisted Surgery, Vol: 19, Pages: 1-13, ISSN: 1478-5951
BackgroundThis systematic review aims to ascertain how accurately 3D models can be predicted from two-dimensional (2D) imaging utilising statistical shape modelling.MethodsA systematic search of published literature was conducted in September 2022. All papers which assessed the accuracy of 3D models predicted from 2D imaging utilising statistical shape models and which validated the models against the ground truth were eligible.Results2127 papers were screened and a total of 34 studies were included for final data extraction. The best overall achievable accuracy was 0.45 mm (root mean square error) and 0.16 mm (average error).ConclusionStatistical shape modelling can predict detailed 3D anatomical models from minimal 2D imaging. Future studies should report the intended application domain of the model, the level of accuracy required, the underlying demographics of subjects, and the method in which accuracy was calculated, with root mean square error recommended if appropriate.
Patel A, Edwards T, Jones G, et al., 2023, Metabolic equivalent of task (MET) scores avoid the ceiling effect observed with conventional patient reported outcome scores following knee arthroplasty, Bone & Joint Open, Vol: 4, Pages: 129-137, ISSN: 2633-1462
Aims : The metabolic equivalent of task (MET) score examines patient performance in relation toenergy expenditure before and after knee arthroplasty. This study assesses it’s use in a kneearthroplasty population in comparison with the widely used Oxford Knee Score (OKS) and EuroQol5d Index (EQ-5D) which are reported to be limited by ceiling effects.Method: One-hundred and sixteen patients with OKS, EQ-5D and MET scores before, and at least sixmonths following unilateral primary knee arthroplasty were identified from a database. Procedureswere performed by a single surgeon between 2014 & 2019 consecutively. Scores were analysed fornormality, skewness, kurtosis and the presence of ceiling/floor effects. Concurrent validity betweenthe MET score, OKS and EQ-5D was assessed using Spearman’s rank.Results: Post-operatively the OKS and EQ-5D demonstrated negative skews in distribution, with highkurtosis at six months and one year. The OKS demonstrated a ceiling effect at one year (15.7%) postoperatively. The EQ-5D demonstrated a ceiling effect at six months (30.2%) and one year (39.8%)post-operatively. The MET score did not demonstrate a skewed distribution or ceiling effect either atsix months or one year post-operatively. Weak-moderate correlations were noted between the METscore and conventional scores at six-months and one-year post-operatively.Conclusion: In contrast to the OKS and EQ-5D, the MET score was normally distributed postoperatively with no ceiling effect. It is worth consideration as an arthroplasty outcome measure,particularly for patients with high expectations.
Mahmoud K, Alagha MA, Nowinka Z, et al., 2023, Predicting total knee replacement at 2 and 5 years in osteoarthritis patients using machine learning, BMJ Surgery, Interventions, & Health Technologies, Vol: 5, Pages: 1-9, ISSN: 2631-4940
Objectives Knee osteoarthritis is a major cause of physical disability and reduced quality of life, with end-stage disease often treated by total knee replacement (TKR). We set out to develop and externally validate a machine learning model capable of predicting the need for a TKR in 2 and 5 years time using routinely collected health data.Design A prospective study using datasets Osteoarthritis Initiative (OAI) and the Multicentre Osteoarthritis Study (MOST). OAI data were used to train the models while MOST data formed the external test set. The data were preprocessed using feature selection to curate 45 candidate features including demographics, medical history, imaging assessments, history of intervention and outcome.Setting The study was conducted using two multicentre USA-based datasets of participants with or at high risk of knee OA.Participants The study excluded participants with at least one existing TKR. OAI dataset included participants aged 45–79 years of which 3234 were used for training and 809 for internal testing, while MOST involved participants aged 50–79 and 2248 were used for external testing.Main outcome measures The primary outcome of this study was prediction of TKR onset at 2 and 5 years. Performance was evaluated using area under the curve (AUC) and F1-score and key predictors identified.Results For the best performing model (gradient boosting machine), the AUC at 2 years was 0.913 (95% CI 0.876 to 0.951), and at 5 years 0.873 (95% CI 0.839 to 0.907). Radiographic-derived features, questionnaire-based assessments alongside the patient’s educational attainment were key predictors for these models.Conclusions Our approach suggests that routinely collected patient data are sufficient to drive a predictive model with a clinically acceptable level of accuracy (AUC>0.7) and is the first such tool to be externally validated. This level of accuracy is higher than previously published models utilising MRI data, whi
Stanley A, Edwards T, Jaere M, et al., 2023, An automated, web-based triage tool may optimise referral pathways in elective orthopaedic surgery: a proof-of-concept study, Digital Health, Vol: 9, Pages: 1-9, ISSN: 2055-2076
IntroductionKnee pain is caused by various pathologies, making evaluation in primary-care challenging. Subsequently, an over-reliance on imaging, such as radiographs and MRI exists. Electronic-triage tools represent an innovative solution to this problem. The aims of this study were to establish the magnitude of unnecessary knee imaging prior to orthopaedic surgeon referral, and ascertain whether an e-triage tool outperforms existing clinical pathways to recommend correct imaging.MethodsPatients ≥18 years presenting with knee pain treated with arthroscopy or arthroplasty at a single academic hospital between 2015 and 2020 were retrospectively identified. The timing and appropriateness of imaging were assessed according to national guidelines, and classified as ‘necessary’, ‘unnecessary’ or ‘required MRI’. Based on an eDelphi consensus study, a symptom-based e-triage tool was developed and piloted to preliminarily diagnose five common knee pathologies and suggest appropriate imaging.Results1462 patients were identified. 17.2% (n = 132) of arthroplasty patients received an ‘unnecessary MRI’, 27.6% (n = 192) of arthroscopy patients did not have a ‘necessary MRI’, requiring follow-up. Forty-one patients trialled the e-triage pilot (mean age: 58.4 years, 58.5% female). Preliminary diagnoses were available for 33 patients. The e-triage tool correctly identified three of the four knee pathologies (one pathology did not present). 79.2% (n = 19) of participants would use the tool again.ConclusionA substantial number of knee pain patients receive incorrect imaging, incurring delays and unnecessary costs. A symptom-based e-triage tool was developed, with promising performance and user feedback. With refinement using larger datasets, this tool has the potential to improve wait-times, referral quality and reduce cost.
York T, Raj S, Ashdown T, et al., 2023, Clinician and computer: a study on doctors’ perceptions of artificial intelligence in skeletal radiography, BMC Medical Education, Vol: 23, Pages: 1-10, ISSN: 1472-6920
BackgroundTraumatic musculoskeletal injuries are a common presentation to emergency care, the first-line investigation often being plain radiography. The interpretation of this imaging frequently falls to less experienced clinicians despite well-established challenges in reporting. This study presents novel data of clinicians’ confidence in interpreting trauma radiographs, their perception of AI in healthcare, and their support for the development of systems applied to skeletal radiography.MethodsA novel questionnaire was distributed through a network of collaborators to clinicians across the Southeast of England. Over a three-month period, responses were compiled into a database before undergoing statistical review.ResultsThe responses of 297 participants were included. The mean self-assessed knowledge of AI in healthcare was 3.68 out of ten, with significantly higher knowledge reported by the most senior doctors (Specialty Trainee/Specialty Registrar or above = 4.88). 13.8% of participants reported an awareness of AI in their clinical practice.Overall, participants indicated substantial favourability towards AI in healthcare (7.87) and in AI applied to skeletal radiography (7.75). There was a preference for a hypothetical system indicating positive findings rather than ruling as negative (7.26 vs 6.20).ConclusionsThis study identifies clear support, amongst a cross section of student and qualified doctors, for both the general use of AI technology in healthcare and in its application to skeletal radiography for trauma. The development of systems to address this demand appear well founded and popular. The engagement of a small but reticent minority should be sought, along with improving the wider education of doctors on AI.
Burge T, Jones G, Jordan C, et al., 2022, A computational tool for automatic selection of total knee replacementimplant size using x-ray images, Frontiers in Bioengineering and Biotechnology, Vol: 10, Pages: 1-11, ISSN: 2296-4185
Purpose: The aim of this study was to outline a fully automatic tool capable of reliably predicting the most suitable total kneereplacement implant sizes for patients, using bi-planar X-ray images. By eliminating the need for manual templating or guidingsoftware tools via the adoption of convolutional neural networks, time and resource requirements for pre-operative assessmentand surgery could be reduced, the risk of human error minimized, and patients could see improved outcomes.Methods: The tool utilizes a machine learning-based 2D – 3D pipeline to generate accurate predictions of subjects’ distal femur andproximal tibia bones from X-ray images. It then virtually fits different implant models and sizes to the 3D predictions, calculatesthe implant to bone root-mean-squared error and maximum over/under hang for each, and advises the best option for thepatient. The tool was tested on 78, predominantly White subjects (45 female/33 male), using generic femur component and tibiaplate designs scaled to sizes obtained for five commercially available products. The predictions were then compared to the groundtruth best options, determined using subjects’ MRI data.Results: The tool achieved average femur component size prediction accuracies across the five implant models of 77.95% in termsof global fit (root-mean-squared error), and 71.79% for minimizing over/underhang. These increased to 99.74% and 99.49% with ±1size permitted. For tibia plates, the average prediction accuracies were 80.51% and 72.82% respectively. These increased to99.74% and 98.98% for ±1 size. Better prediction accuracies were obtained for implant models with fewer size options, howeversuch models more frequently resulted in a poor fit.Conclusion: A fully automatic tool was developed and found to enable higher prediction accuracies than generally reported formanual templating techniques, as well as similar computational methods.
Nowinka Z, Alagha MA, Mahmoud K, et al., 2022, Predicting Depression in Patients With Knee Osteoarthritis Using Machine Learning: Model Development and Validation Study, JMIR FORMATIVE RESEARCH, Vol: 6
Musbahi O, Syed L, Le Feuvre P, et al., 2021, Public patient views of artificial intelligence in healthcare: A nominal group technique study, Digital Health, Vol: 7, Pages: 1-11, ISSN: 2055-2076
Objectives: The beliefs of laypeople and medical professionals often diverge with regards to disease, and technology has had a positive impact on how research is conducted. Surprisingly, given the expanding worldwide funding and research into Artificial Intelligence (AI) applications in healthcare, there is a paucity of research exploring the public patient perspective on this technology. Our study sets out to address this knowledge gap, by applying the Nominal Group Technique (NGT) to explore patient public views on AI. Methods: A Nominal Group Technique (NGT) was used involving four study groups with seven participants in each group. This started with a silent generation of ideas regarding the benefits and concerns of AI in Healthcare. This was followed by a group discussion. Then a round-robin process was conducted until no new ideas were generated. Participants then ranked their top five benefits and top five concerns regarding the use of AI in healthcare. A final group consensus was reached. Results: Twenty-Eight participants were recruited with the mean age of 47 years. The top five benefits were: Faster health services, Greater accuracy in management, AI systems available 24/7, reducing workforce burden, and equality in healthcare decision making. The top five concerns were: Data cybersecurity, bias and quality of AI data, less human interaction, algorithm errors and responsibility, and limitation in technology. Conclusion: This is the first formal qualitative study exploring patient public views on the use of AI in healthcare, and highlights that there is a clear understanding of the potential benefits delivered by this technology. Greater patient public group involvement, and a strong regulatory framework is recommended.
Federer SJ, Jones GG, 2021, Artificial intelligence in orthopaedics: A scoping review, PLOS ONE, Vol: 16, ISSN: 1932-6203
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Garner AJ, Edwards TC, Liddle AD, et al., 2021, The revision partial knee classification system: understanding the causative pathology and magnitude of further surgery following partial knee arthroplasty., Bone & Joint Open, Vol: 2, Pages: 638-645, ISSN: 2633-1462
AIMS: Joint registries classify all further arthroplasty procedures to a knee with an existing partial arthroplasty as revision surgery, regardless of the actual procedure performed. Relatively minor procedures, including bearing exchanges, are classified in the same way as major operations requiring augments and stems. A new classification system is proposed to acknowledge and describe the detail of these procedures, which has implications for risk, recovery, and health economics. METHODS: Classification categories were proposed by a surgical consensus group, then ranked by patients, according to perceived invasiveness and implications for recovery. In round one, 26 revision cases were classified by the consensus group. Results were tested for inter-rater reliability. In round two, four additional cases were added for clarity. Round three repeated the survey one month later, subject to inter- and intrarater reliability testing. In round four, five additional expert partial knee arthroplasty surgeons were asked to classify the 30 cases according to the proposed revision partial knee classification (RPKC) system. RESULTS: Four classes were proposed: PR1, where no bone-implant interfaces are affected; PR2, where surgery does not include conversion to total knee arthroplasty, for example, a second partial arthroplasty to a native compartment; PR3, when a standard primary total knee prosthesis is used; and PR4 when revision components are necessary. Round one resulted in 92% inter-rater agreement (Kendall's W 0.97; p < 0.005), rising to 93% in round two (Kendall's W 0.98; p < 0.001). Round three demonstrated 97% agreement (Kendall's W 0.98; p < 0.001), with high intra-rater reliability (interclass correlation coefficient (ICC) 0.99; 95% confidence interval 0.98 to 0.99). Round four resulted in 80% agreement (Kendall's W 0.92; p < 0.001). CONCLUSION: The RPKC system accounts for all procedures which may be appropriate following partial knee arthroplasty. It h
Lex JR, Edwards TC, Packer T, et al., 2021, Response to letter to the editor on "Perioperative Systemic Dexamethasone Reduces Length of Stay in Total Joint Arthroplasty: A Systematic Review and Meta-Analysis of Randomized Controlled Trials" reply, Journal of Arthroplasty, Vol: 36, Pages: E42-E43, ISSN: 0883-5403
Lex JR, Edwards TC, Packer TW, et al., 2021, Perioperative Systemic Dexamethasone Reduces Length of Stay in Total Joint Arthroplasty: A Systematic Review and Meta-Analysis of Randomized Controlled Trials, JOURNAL OF ARTHROPLASTY, Vol: 36, Pages: 1168-1186, ISSN: 0883-5403
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York T, Jenney H, Jones G, 2020, Clinician and computer: a study on patient perceptions of artificial intelligence in skeletal radiography, BMJ Health & Care Informatics, Vol: 27, ISSN: 2632-1009
Background Up to half of all musculoskeletal injuries are investigated with plain radiographs. However, high rates of image interpretation error mean that novel solutions such as artificial intelligence (AI) are being explored.Objectives To determine patient confidence in clinician-led radiograph interpretation, the perception of AI-assisted interpretation and management, and to identify factors which might influence these views.Methods A novel questionnaire was distributed to patients attending fracture clinic in a large inner-city teaching hospital. Categorical and Likert scale questions were used to assess participant demographics, daily electronics use, pain score and perceptions towards AI used to assist in interpretation of their radiographs, and guide management.Results 216 questionnaires were included (M=126, F=90). Significantly higher confidence in clinician rather than AI-assisted interpretation was observed (clinician=9.20, SD=1.27 vs AI=7.06, SD=2.13), 95.4% reported favouring clinician over AI-performed interpretation in the event of disagreement.Small positive correlations were observed between younger age/educational achievement and confidence in AI-assistance. Students demonstrated similarly increased confidence (8.43, SD 1.80), and were over-represented in the minority who indicated a preference for AI-assessment over their clinicians (50%).Conclusions Participant’s held the clinician’s assessment in the highest regard and expressed a clear preference for it over the hypothetical AI assessment. However, robust confidence scores for the role of AI-assistance in interpreting skeletal imaging suggest patients view the technology favourably.Findings indicate that younger, more educated patients are potentially more comfortable with a role for AI-assistance however further research is needed to overcome the small number of responses on which these observations are based.
Jones G, Clarke S, Harris S, et al., 2019, A novel patient-specific instrument design can deliver robotic level accuracy in unicompartmental knee arthroplasty, The Knee, Vol: 26, Pages: 1421-1428, ISSN: 0968-0160
BackgroundA previous randomised controlled trial (RCT) by our group found that robotic assisted unicompartmental knee arthroplasty (UKA) surgery was significantly more accurate than conventional instrumentation. The aim of this study was to determine whether a low-cost novel PSI design could deliver the same level of accuracy as the robot in the same time efficient manner as conventional instruments.MethodsThirty patients undergoing medial UKA took part. Tibial component position was planned using a low dose CT-scan, and compared to a day 1 postoperative CT-scan to determine the difference between the planned and achieved positions. Operations were performed by one expert surgeon using PSI (Embody, London, UK).ResultsThe mean absolute difference between planned and achieved tibial implant positions using PSI was 2.0° (SD 1.0°) in the coronal plane, 1.8° (SD 1.5) in the sagittal plane, and 4.5° (SD 3.3) in the axial plane. These results were not significantly different to the 13 historical robotic cases (mean difference 0.5°, 0.5°, and 1.7°, p = 0.1907, 0.2867 and 0.1049 respectively). PSI mean operating time was on average 62 min shorter than the robotic group (p < 0.0001) and 40 min shorter than the conventional instrument group (p < 0.0001). No complications were reported.ConclusionsIn conclusion, this clinical trial demonstrates that for tibial component positioning in UKA, a novel design PSI guide in the hands of an expert surgeon, can safely deliver comparable accuracy to a robotic system, whilst being significantly faster than conventional instruments.NIHR Clinical Research Network Reference: 16100.
Oosthuizen CR, Takahashi T, Rogan DM, et al., 2019, The Knee Osteoarthritis Grading System (KOGS) for arthroplasty, The Journal of Arthroplasty, Vol: 34, Pages: 450-455, ISSN: 0883-5403
BackgroundThe aim of this study is to validate the Knee Osteoarthritis Grading system (KOGS) of progressive osteoarthritic (OA) degeneration for the Tri-compartmental knee. This system defines the site and severity of OA to determine a specific knee replacement.MethodsThe radiographic sequence for KOGS includes standing coronal (antero-posterior), lateral, 30° skyline patella, 15° and 45° Rosenberg and stress views in 20° of flexion.Cohen’s Kappa and related agreement statistical methods were used to assess the level of concordance of the seven evaluators between A and B cohorts for each evaluator and also against the actual arthroplasty used. Sensitivity and specificity was also assessed for the KOGS in identifying true partial knee replacements (PKR) and total knee replacements (TKR) as decided from the cohort A evaluations.ResultsFrom a cohort of 330 patients who were included in the study, 71 (22.5%) underwent a TKR procedure, 258 (78.2%) a PKR and 1 (0.3%) was neither a TKR nor PKR. KOGS was able to identify true PKRs (sensitivity) in the range of 92.2% to 98.5% across all the different evaluators. The KOGS method was able to identify a PKR or a TKR with an accuracy ranging from 92% to 98.8% across all different evaluators.The surgical results after 20 months are at least comparable with the expected average in the academic literature.ConclusionThe KOGS classification provides a reliable and accurate tool to assess suitability of an individual patient for undergoing partial or total knee replacement.
Jones GG, Clarke S, Jaere M, et al., 2019, Prothèse unicompartimentaire et désostéotomie pour échec d’ostéotomie tibiale : une alternative chirurgicale à l’arthroplastie totale de genouFailed high tibial osteotomy: A joint preserving alternative to total knee arthroplasty, Revue de Chirurgie Orthopedique et Traumatologique, Vol: 105, Pages: 41-41, ISSN: 1877-0517
High tibial osteotomy is an attractive treatment option for young active patients wishing to return to high level activities. However, it is not considered a long-term solution, with 30% revised at ten years. Currently, the only revision option is a total knee arthroplasty, a procedure that might not deliver the functional level expected by these highly active patients. This paper describes a novel joint preserving approach to HTO revision, using assistive technology, in the form of 3D printed guides, to reverse the osteotomy and simultaneously perform a unicompartmental knee replacement. The indications and planning aims for this procedure are discussed, and the preliminary results in four patients presented. Level of evidence: IV.
Jones GG, Clarke S, Jaere M, et al., 2019, Failed high tibial osteotomy: A joint preserving alternative to total knee arthroplasty, Orthopaedics and Traumatology: Surgery and Research, Vol: 105, Pages: 85-88, ISSN: 1877-0568
High tibial osteotomy is an attractive treatment option for young active patients wishing to return to high-level activities. However, it is not considered a long-term solution, with 30% revised at ten years. Currently, the only revision option is a total knee arthroplasty, a procedure that might not deliver the functional level expected by these highly active patients. This paper describes a novel joint preserving approach to HTO revision, using assistive technology, in the form of 3D printed guides, to reverse the osteotomy and simultaneously perform a unicompartmental knee replacement. The indications and planning aims for this procedure are discussed, and the preliminary results in four patients presented.
Wang H, Sugand K, Newman S, et al., 2019, Are multiple views superior to a single view when teaching hip surgery? A single-blinded randomized controlled trial of technical skill acquisition, PLoS ONE, Vol: 14, ISSN: 1932-6203
s Metrics Comments Media Coverage Abstract Introduction Materials and methods Results Discussion Conclusion Supporting information References Reader Comments (0) Media Coverage (0) FiguresAbstractPurposeSurgical education videos currently all use a single point of view (POV) with the trainee locked onto a fixed viewpoint, which may not deliver sufficient information for complex procedures. We developed a novel multiple POV video system and evaluated its training outcome compared with traditional single POV.MethodsWe filmed a hip resurfacing procedure performed by an expert attending using 8 cameras in theatre. 30 medical students were randomly and equally allocated to learn the procedure using the multiple POV (experiment group [EG]) versus single POV system (control group [CG]). Participants advanced a pin into the femoral head as demonstrated in the video. We measured the drilling trajectories and compared it with pre-operative plan to evaluate distance of the pin insertion and angular deviations. Two orthopedic attendings expertly evaluated the participants’ performance using a modified global rating scale (GRS). There was a pre-video knowledge test that was repeated post-simulation alongside a Likert-scale questionnaire.ResultsThe angular deviation of the pin in EG was significantly less by 29% compared to CG (p = 0.037), with no significant difference in the entry point’s distance between groups (p = 0.204). The GRS scores for EG were 3.5% higher than CG (p = 0.046). There was a 32% higher overall knowledge test score (p<0.001) and 21% improved Likert-scale questionnaire score (p = 0.002) after video-learning in EG than CG, albeit no significant difference in the knowledge test score before video-learning (p = 0.721).ConclusionThe novel multiple POV provided significant objective and subjective advantages over single POV for acquisition of technical skills in hip surgery.
Goh EL, Chidambaram S, Eigenmann D, et al., 2018, Minimally invasive percutaneous plate osteosynthesis versus intramedullary nail fixation for closed distal tibial fractures: a meta-analysis of the clinical outcomes, SICOT-J, Vol: 4, ISSN: 2426-8887
Introduction: Minimally invasive percutaneous plate osteosynthesis (MIPPO) has emerged as a viable alternative for the treatment of distal tibial fractures. However, the clinical outcomes of this procedure compared to intramedullary (IM) nail fixation have yet to be established. The present meta-analysis aims to compare the clinical outcomes following MIPPO and IM nail fixation for closed distal tibial fractures.Methods: MEDLINE and EMBASE databases were searched from date of inception to 10th April 2017. Randomized controlled trials (RCTs) comparing MIPPO with IM nail fixation for closed and Gustilo Grade I distal tibial fractures were included. Outcomes assessed included time to union, complications and functional outcomes. Quality and risk of bias of the RCTs were assessed using the Cochrane Collaboration Tool.Results: Five RCTs comprising 497 patients were included. MIPPO was associated with a longer time to union (MD: 1.08, 95% CI: 0.26, 1.90, p = 0.010, I 2 = 84%) and increased risk of wound complications (RR: 1.58, 95% CI: 1.01, 2.46, p = 0.04, I 2 = 0%). Both MIPPO and IM nail fixation had comparable risks of malunion, delayed union, non-union and deep infections, with similar functional outcomes.Discussion: Compared to IM nail fixation, a MIPPO fixation technique for distal tibial fractures is associated with a longer time to fracture union and an increased risk of wound complications. Neither technique demonstrates a clear advantage with regard to risk of malunion/non-union, or functional outcome. Assuming equivalent surgical expertise with both techniques, the results suggest that IM nail fixation is the treatment modality of choice for these challenging fractures.
Jones GG, Logishetty K, Clarke S, et al., 2018, Do patient-specific instruments (PSI) for UKA allow non-expert surgeons to achieve the same saw cut accuracy as expert surgeons?, Archives of Orthopaedic and Trauma Surgery, Vol: 138, Pages: 1601-1608, ISSN: 0936-8051
INTRODUCTION: High-volume unicompartmental knee arthroplasty (UKA) surgeons have lower revision rates, in part due to improved intra-operative component alignment. This study set out to determine whether PSI might allow non-expert surgeons to achieve the same level of accuracy as expert surgeons. MATERIALS AND METHODS: Thirty-four surgical trainees with no prior experience of UKA, and four high-volume UKA surgeons were asked to perform the tibial saw cuts for a medial UKA in a sawbone model using both conventional and patient-specific instrumentation (PSI) with the aim of achieving a specified pre-operative plan. Half the participants in each group started with conventional instrumentation, and half with PSI. CT scans of the 76 cut sawbones were then segmented and reliably orientated in space, before saw cut position in the sagittal, coronal and axial planes was measured, and compared to the pre-operative plan. RESULTS: The compound error (absolute error in the coronal, sagittal and axial planes combined) for experts using conventional instruments was significantly less than that of the trainees (11.6°±4.0° v 7.7° ±2.3º, p = 0.029). PSI improved trainee accuracy to the same level as experts using conventional instruments (compound error 5.5° ±3.4º v 7.7° ±2.3º, p = 0.396) and patient-specific instruments (compound error 5.5° ±3.4º v 7.3° ±4.1º, p = 0.3). PSI did not improve the accuracy of high-volume surgeons (p = 0.3). CONCLUSIONS: In a sawbone model, PSI allowed inexperienced surgeons to achieve more accurate saw cuts, equivalent to expert surgeons, and thus has the potential to reduce revision rates. The next test will be to determine whether these results can be replicated in a clinical trial.
Aqil A, Patel S, Wiik A, et al., 2018, Patient-specific guides improve hip arthroplasty surgical accuracy, COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING, Vol: 21, Pages: 579-584, ISSN: 1025-5842
Jones G, Jaere M, Clarke S, et al., 2018, A Clinical Trial Examining the Accuracy of High Tibial Osteotomy When Performed by Experts Using a Novel Patient Specific Instrument (PSI), SSRN
Jones GG, Clarke S, Jaere M, et al., 2018, 3D printing and unicompartmental knee arthroplasty, EFORT Open Reviews, Vol: 3, Pages: 248-253, ISSN: 2058-5241
In suitable patients, unicompartmental knee arthroplasty (UKA) offers a number of advantages compared with total knee arthroplasty. However, the procedure is technically demanding, with a small tolerance for error. Assistive technology has the potential to improve the accuracy of implant positioning. This review paper describes the concept of detailed UKA planning in 3D, and the 3D printing technology that enables a plan to be delivered intraoperatively using patient-specific instrumentation (PSI). The varying guide designs that enable accurate registration are discussed and described. The system accuracy is reported. Future studies need to ascertain whether accuracy for low-volume surgeons can be delivered in the operating theatre using PSI, and reflected in improved patient reported outcome measures, and lower revision rates.
Jones GG, Jaere M, Clarke S, et al., 2018, 3D printing and high tibial osteotomy, EFORT Open Reviews, Vol: 3, Pages: 254-259, ISSN: 2058-5241
High tibial osteotomy (HTO) is a relatively conservative surgical option in the management of medial knee pain. Thus far, the outcomes have been variable, and apparently worse than the arthroplasty alternatives when judged using conventional metrics, owing in large part to uncer-tainty around the extent of the correction planned and achieved.This review paper introduces the concept of detailed 3D planning of the procedure, and describes the 3D printing technology that enables the plan to be performed.The different ways that the osteotomy can be undertaken, and the varying guide designs that enable accurate regis-tration are discussed and described. The system accuracy is reported.In keeping with other assistive technologies, 3D printing enables the surgeon to achieve a preoperative plan with a degree of accuracy that is not possible using conventional instruments. With the advent of low dose CT, it has been possible to confirm that the procedure has been under-taken accurately too.HTO is the ‘ultimate’ personal intervention: the amount of correction needed for optimal offloading is not yet com-pletely understood.For the athletic person with early medial joint line over-load who still runs and enjoys life, HTO using 3D printing is an attractive option. The clinical effectiveness remains unproven.
Clarke S, Cobb J, Jaere M, et al., 2018, Osteotomies: Advanced and complex techniques, ESSKA Instructional Course Lecture Book: Glasgow 2018, Pages: 129-151, ISBN: 9783662561263
We started performing precise surgery based upon CT plans in the last century - the first embodiment of this approach was a robotic assistant built for total knee replacement, the “Acrobot” [1]. Abundant evidence now exists to confirm that assistive technologies enable surgeons to achieve their preoperative goals [2]. The concept of planned surgery is therefore not novel. Patient-matched instruments share several key elements with the robotic platform, and these formed the basis of this current project. The essential elements include image segmentation, planning, and registration. We applied the know-how of these dimensions to design and build patient-matched guides for a range of tasks using biocompatible polymer 3D printers. Having established a workflow for arthroplasty, the adaptation of the same principles to osteotomy was a short step, requiring software to be developed to deliver semiautomated useful information regarding limb segment alignment and the shapes of bones.
Wiik AV, Aqil A, Brevadt M, et al., 2017, Abnormal ground reaction forces lead to a general decline in gait speed in knee osteoarthritis patients., World Journal of Orthopedics, Vol: 8, Pages: 322-328, ISSN: 2218-5836
AIM: To analyse ground reaction forces at higher speeds using another method to be more sensitive in assessing significant gait abnormalities. METHODS: A total of 44 subjects, consisting of 24 knee osteoarthritis (OA) patients and 20 healthy controls were analysed. The knee OA patients were recruited from an orthopaedic clinic that were awaiting knee replacement. All subjects had their gait patterns during stance phase at top walking speed assessed on a validated treadmill instrumented with tandem force plates. Temporal measurements and ground reaction forces (GRFs) along with a novel impulse technique were collected for both limbs and a symmetry ratio was applied to all variables to assess inter-limb asymmetry. All continuous variables for each group were compared using a student t-test and χ(2) analysis for categorical variables with significance set at α = 0.05. Receiver operator characteristics curves were utilised to determine best discriminating ability. RESULTS: The knee OA patients were older (66 ± 7 years vs 53 ± 9 years, P = 0.01) and heavier (body mass index: 31 ± 6 vs 23 ± 7, P < 0.001) but had a similar gender ratio when compared to the control group. Knee OA patients were predictably slower at top walking speed (1.37 ± 0.23 m/s vs 2.00 ± 0.20 m/s, P < 0.0001) with shorter mean step length (79 ± 12 cm vs 99 ± 8 cm, P < 0.0001) and broader gait width (14 ± 5 cm vs 11 ± 3 cm, P = 0.015) than controls without any known lower-limb joint disease. At a matched mean speed (1.37 ± 0.23 vs 1.34 ± 0.07), ground reaction results revealed that push-off forces and impulse were significantly (P < 0.0001) worse (18% and 12% respectively) for the knee OA patients when compared to the controls. Receiver operating characteristic curves analysis demonstrated total impulse to be the best discriminator of asymmetry, with an area under the curve of 0.902, with a cut-off
Jones G, Kotti M, Wiik A, et al., 2016, Gait comparison of unicompartmental and total knee arthroplasties with healthy controls, Bone & Joint Journal, Vol: 98-B, Pages: 16-21, ISSN: 2049-4394
Aims:To compare the gait of unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) patients with healthy controls, usinga machine learning approach.Patients:145 participants (121 healthy controls, 12 cruciate retaining TKA patients, and 12 mobile bearing UKA patients) were recruited. The TKAand UKA patients were a minimum of 12 months post-op, and matched for pattern and severity of arthrosis, age, and BMI.Methods:Participants walked on an instrumented treadmill until their maximum walking speed was reached. Temporospatial gait parameters, andvertical ground reaction force data was captured at each speed. Oxford knee scores (OKS) were also collected. An ensemble of treesalgorithm was used to analyse the data: 27 gait variables were used to train classification trees for each speed, with a binary outputprediction of whether these variables were derived from a UKA or TKA patient. Healthy control gait data was then tested by the decisiontrees at each speed and a final classification (UKA or TKA) reached for each subject in a majority voting manner over all gait cycles andspeeds. Top walking speed was also recorded.Results:92% of the healthy controls were classified by the decision tree as a UKA, 5% as a TKA, and 3% were unclassified. There was nosignificant difference in OKS between the UKA and TKA patients (p=0.077). Top walking speed in TKA patients (1.6 m/s [1.3-2.1]) wassignificantly lower than that of both the UKA group (2.2 m/s [1.8-2.7]) and healthy controls (2.2 m/s [1.5-2.7]) (p<0.001).Conclusion:UKA results in a more physiological gait compared to TKA, and a higher top walking speed. This difference in function was not detectedby the OKS.
Logishetty K, Jones GG, Cobb JP, 2016, Letter to the Editor: The John Insall Award: no functional benefit after unicompartmental knee arthroplasty performed with patient-specific instrumentation: a randomized trial, Clinical Orthopaedics and Related Research, Vol: 474, Pages: 272-273, ISSN: 1528-1132
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