Aims. Manual impaction, with a mallet and introducer, remains the standard method of installing cementless acetabular cups during total hip arthroplasty (THA). This study aims to quantify the accuracy and precision of manual impaction strikes during the seating of an acetabular component. This understanding aims to help improve impaction surgical techniques and inform the development of future technologies. Methods. Posterior approach THAs were carried out on three cadavers by an expert orthopaedic surgeon. An instrumented mallet and introducer were used to insert cementless acetabular cups. The motion of the mallet, relative to the introducer, was analyzed for a total of 110 strikes split into low-, medium-, and high-effort strikes. Three parameters were extracted from these data: strike vector, strike offset, and mallet face alignment. Results. The force vector of the mallet strike, relative to the introducer axis, was misaligned by an average of 18.1°, resulting in an average wasted strike energy of 6.1%. Furthermore, the mean strike offset was 19.8 mm from the centre of the introducer axis and the mallet face, relative to the introducer strike face, was misaligned by a mean angle of 15.2° from the introducer strike face. Conclusion. The direction of the impact vector in manual impaction lacks both accuracy and precision. There is an opportunity to improve this through more advanced impaction instruments or surgical training. Cite this article: Bone Joint Res 2024;13(4):193–200

Background. Musculoskeletal disorders, including low back pain, affects 68% of UK physiotherapists across their career with patient handling considered a key risk factor. Manual handling training is mandatory for all allied health professionals, however there is limited research investigating whether professionals adopt recommended manual handling principles following training. Purpose of Study. To investigate spinal angles when facilitating sit-to-stand, and a turning manoeuvre in bed, comparing first-year physiotherapy students (who have not received manual handling training) with final-year physiotherapy students (who have received manual handling training). Methods. Cross-sectional pilot study (n= 20; 10 first-year, 10 final-year). All participants were exposed to a short training video outlining how to safely perform each manoeuvre. Retroreflective markers were attached to: L4, ASIS, PSIS, T12, C7, tragus and canthus. Spinal (neck, thoracic, lumbar and pelvic) angles were established via digital photographs using a bespoke MATLAB programme (MathWorks). A Mann-Whitney U test was conducted to determine between group differences. Results. No statistically significant results were observed between first-year and final-year students for both manoeuvres (p<0.05), except for neck angle during the turning manoeuvre (final-year students demonstrating more upright postures, p=0.037). Interestingly, for the turning manoeuvre in bed it was noted that none of the participants adjusted the bed height. Conclusion. The results suggest that clinical experience and routine manual handling training may not have a significant effect on spinal posture, especially in relation to pelvic, lumbar and thoracic angles. Further work is needed to understand how training relates to adoption of manual handling principles in practice. Conflicts of interest. None. Sources of funding. None

Aims. The purpose of this study was to compare the radiological outcomes of manual versus robotic-assisted medial unicompartmental knee arthroplasty (UKA). Methods. Postoperative radiological outcomes from 86 consecutive robotic-assisted UKAs (RAUKA group) from a single academic centre were retrospectively reviewed and compared to 253 manual UKAs (MUKA group) drawn from a prior study at our institution. Femoral coronal and sagittal angles (FCA, FSA), tibial coronal and sagittal angles (TCA, TSA), and implant overhang were radiologically measured to identify outliers. Results. When assessing the accuracy of RAUKAs, 91.6% of all alignment measurements and 99.2% of all overhang measurements were within the target range. All alignment and overhang targets were simultaneously met in 68.6% of RAUKAs. When comparing radiological outcomes between the RAUKA and MUKA groups, statistically significant differences were identified for combined outliers in FCA (2.3% vs 12.6%; p = 0.006), FSA (17.4% vs 50.2%; p < 0.001), TCA (5.8% vs 41.5%; p < 0.001), and TSA (8.1% vs 18.6%; p = 0.023), as well as anterior (0.0% vs 4.7%; p = 0.042), posterior (1.2% vs 13.4%; p = 0.001), and medial (1.2% vs 14.2%; p < 0.001) overhang outliers. Conclusion. Robotic system navigation decreases alignment and overhang outliers compared to manual UKA. Given the association between component placement errors and revision in UKA, this strong significant improvement in accuracy may improve implant survival. Level of Evidence: III. Cite this article: Bone Jt Open 2021;2-3:191–197

The objectives of our study were to compare patient reported outcome measures between manual and robotic-assisted total hip arthroplasty. Between 1st May 2021 and 31st August 2022, 539 consecutive patients who underwent 564 primary total hip arthroplasties were identified from the local registry database. Data were prospectively collected, and included patient demographics, American Society of Anaesthesiologists (ASA) grade, surgical approach, robotic-assistance, Oxford Hip Score (OHS), EQ-5D-3L and EQ-VAS pre-operatively and at twelve months. Robotic-assistance, compared against manual total hip arthroplasty, was associated with an enhanced median (interquartile range) OHS (46 [42 – 48] vs 43 [36 – 47], p-value < 0.001), EQ-5D-3L (5 [5 – 7] vs 6 [5 – 8], p-value 0.002), and EQVAS (90 [75 – 95] vs 80 [70 – 90], p-value 0.003) at twelve months after surgery. Robotic-assistance was confirmed to be an independent predictor of a greater OHS at twelve months on a multivariate linear regression analysis (p-value 0.001). Robotic assistance was superior to manual total hip arthroplasty in enhancing patient reported outcomes at twelve months after surgery

As patient data continues to grow, the importance of efficient and precise analysis cannot be overstated. The employment of Generative Artificial Intelligence (AI), specifically Chat GPT-4, in the realm of medical data interpretation has been on the rise. However, its effectiveness in comparison to manual data analysis has been insufficiently investigated. This quality improvement project aimed to evaluate the accuracy and time-efficiency of Generative AI (GPT-4) against manual data interpretation within extensive datasets pertaining to patients with orthopaedic injuries. A dataset, containing details of 6,562 orthopaedic trauma patients admitted to a district general hospital over a span of two years, was reviewed. Two researchers operated independently: one utilised GPT-4 for insights via prompts, while the other manually examined the identical dataset employing Microsoft Excel and IBM® SPSS® software. Both were blinded on each other's procedures and outcomes. Each researcher answered 20 questions based on the dataset including injury details, age groups, injury specifics, activity trends and the duration taken to assess the data. Upon comparison, both GPT-4 and the manual researcher achieved consistent results for 19 out of the 20 questions (95% accuracy). After a subsequent review and refined prompts (prompt engineering) to GPT-4, the answer to the final question aligned with the manual researcher's findings. GPT-4 required just 30 minutes, a stark contrast to the manual researcher's 9-hour analytical duration. This quality improvement project emphasises the transformative potential of Generative AI in the domain of medical data analysis. GPT-4 not only paralleled the accuracy of manual analysis but also achieved this in significantly less time. For optimal accurate results, data analysis by AI can be enhanced through human oversight. Adopting AI-driven approaches, particularly in orthopaedic data interpretation, can enhance efficiency and ultimately improve patient care. We recommend future investigations on large and more varied datasets to reaffirm these outcomes

Aims. To perform an incremental cost-utility analysis and assess the impact of differential costs and case volume on the cost-effectiveness of robotic arm-assisted unicompartmental knee arthroplasty (rUKA) compared to manual (mUKA). Methods. This was a five-year follow-up study of patients who were randomized to rUKA (n = 64) or mUKA (n = 65). Patients completed the EuroQol five-dimension questionnaire (EQ-5D) preoperatively, and at three months and one, two, and five years postoperatively, which was used to calculate quality-adjusted life years (QALYs) gained. Costs for the primary and additional surgery and healthcare costs were calculated. Results. rUKA was associated with a relative 0.012 QALY gain at five years, which was associated with an incremental cost per QALY of £13,078 for a unit undertaking 400 cases per year. A cost per QALY of less than £20,000 was achieved when ≥ 300 cases were performed per year. However, on removal of the cost for a revision for presumed infection (mUKA group, n = 1) the cost per QALY was greater than £38,000, which was in part due to the increased intraoperative consumable costs associated with rUKA (£626 per patient). When the absolute cost difference (operative and revision costs) was less than £240, a cost per QALY of less than £20,000 was achieved. On removing the cost of the revision for infection, rUKA was cost-neutral when more than 900 cases per year were undertaken and when the consumable costs were zero. Conclusion. rUKA was a cost-effective intervention with an incremental cost per QALY of £13,078 at five years, however when removing the revision for presumed infection, which was arguably a random event, this was no longer the case. The absolute cost difference had to be less than £240 to be cost-effective, which could be achieved by reducing the perioperative costs of rUKA or if there were increased revision costs associated with mUKA with longer follow-up. Cite this article: Bone Jt Open 2023;4(11):889–898

Total Hip Arthroplasty (THA) surgery is a physical and cognitive challenge for surgeons. Data on stress levels, cognitive and physical load of orthopaedic surgeons, as well as ergonomic impact, are limited. With and without the use of an automated impaction device, operational efficiency and the surgeon's ergonomic, mental, and physical load was investigated. In a total of thirty THA procedures, a standard manual technique was compared with an automated impaction device. Three computerized cognitive tasks (Simon, pattern comparison, and pursuit rotor) and five physical tests (isometric wall-sit, plank-to-fatigue, handgrip, supra-postural task, and shoulder endurance) were used to assess psychophysiological load of the surgeon. Surgeon's cortisol concentration was evaluated from saliva samples. Postural risk was assessed by Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA). Efficiency was assessed by timing surgical steps and instrumentation flow. Cognitive performances after automated impaction showed faster response times and lower error rates with a greater time-on-target (+1.5 s) and a lower mouse deviation from target (−1.7 pixels). Manual impaction showed higher physical exhaustion in the isometric wall-sit test (10.6% vs. 22.9%), plank-to-fatigue (2.2% vs. 43.8%), the number of taps in the supra-postural task (−0.7% vs. −7.7%), handgrip force production in the dominant (−6.7% vs. −12.7%) and contralateral hand (+4.7% vs. +7.7%), and in shoulder endurance (−15s vs. −56s). An increase of 38.2% in salivary cortisol concentration between the midday (1.31 nmol/l) and afternoon session (1.81 nmol/l) was observed with manual impaction. After using automated impaction, salivary cortisol concentration decreased (−51.2%). Manual broaching time was on average 6′20’’ versus 7’3’’ with automated impaction. RULA of manual impaction scored 6 for cup impaction and 5 for femoral broaching, versus 3 and 3 for automated impaction, respectively. REBA of manual impaction scored 9 for cup impaction and 5 for femoral broaching, versus 4 and 3 for automated impaction, respectively. Automated impaction lowers surgeons’ cognitive and physical fatigue and leads to reduced stress and improved ergonomics without loss of surgical efficiency

Purpose and background. Work-related musculoskeletal disorders, particularly back pain, are a significant issue for healthcare workers, with patient handling being the most frequently reported risk factor. Patient handling is often performed without assistive devices or equipment, which can cause healthcare staff to maintain awkward postures or experience high loads. This review aimed to comprehensively map the literature surrounding manual patient handling (without assistive devices) by healthcare practitioners to identify the current evidence-base on moving and handling of patients and explore what primary research had been conducted. Methods and results. JBI methodology for scoping reviews and an a priori registered protocol (DOI 10.17605/OSF.IO/8PR7A) was followed and AMED, CINAHL, MEDLINE, SPORTDiscus and EMBASE databases were searched. Literature published in English between 2002 and 2021 was included. Forty-nine records were included: 36 primary research studies, 1 systematic review and 12 ‘other’ including narrative and government reports. Primary research predominantly used observational cross-sectional designs (n = 21 studies). Most studies took place in hospitals (n = 13) and laboratories (n = 12). Nurses formed the largest population group (n = 13), with very little research on physiotherapists and other allied health professionals. Conclusion. This scoping review comprehensively reviewed the available literature in the area. Most of the included primary research was observational. Nurses were often investigated in hospitals and laboratories. Qualitative research investigating moving and handling and further biomechanical investigation into therapeutic handling by healthcare staff were identified as areas for further research. Conflicts of interest. None. Sources of funding. None. This work has been published in Physiotherapy: Johnson, K., Swinton, P., Pavlova, A. and Cooper, K., 2023. Manual patient handling in the healthcare setting: a scoping review. Physiotherapy. (120) 60–77 . https://doi.org/10.1016/j.physio.2023.06.003

Introduction. The accuracy of hexapod circular external fixator deformity correction is contingent on the precision of radiographic analysis during the planning stage. The aim of this study was to compare the SMART TSF (Smith and Nephew, Memphis, Tennessee) in-suite radiographic analysis methods with the traditional manual deformity analysis methods in terms of accuracy of correction. Materials and Methods. Sawbones models were used to simulate two commonly encountered clinical scenarios. Traditional manual radiographic analysis and digital SMART TSF analysis methods were used to correct the simulated deformities. Results. The final outcomes of all six analysis methods across both simulated scenarios were satisfactory. Any differences in residual deformity between the analysis methods are unlikely to be clinically relevant. All three SMART TSF digital analyses were faster to complete than manual radiographic analyses. Conclusions. With experience and a good understanding of the software, manual radiographic analysis can be extremely accurate and remains the gold standard for deformity analysis. In-suite SMART TSF radiographic analysis is fast and accurate to within clinically relevant parameters. Surgeons can with confidence trust the SMART TSF software to provide analysis and corrections that are clinically acceptable

Aims. This systematic review aims to compare the precision of component positioning, patient-reported outcome measures (PROMs), complications, survivorship, cost-effectiveness, and learning curves of MAKO robotic arm-assisted unicompartmental knee arthroplasty (RAUKA) with manual medial unicompartmental knee arthroplasty (mUKA). Methods. Searches of PubMed, MEDLINE, and Google Scholar were performed in November 2021 according to the Preferred Reporting Items for Systematic Review and Meta-­Analysis statement. Search terms included “robotic”, “unicompartmental”, “knee”, and “arthroplasty”. Published clinical research articles reporting the learning curves and cost-effectiveness of MAKO RAUKA, and those comparing the component precision, functional outcomes, survivorship, or complications with mUKA, were included for analysis. Results. A total of 179 articles were identified from initial screening, of which 14 articles satisfied the inclusion criteria and were included for analysis. The papers analyzed include one on learning curve, five on implant positioning, six on functional outcomes, five on complications, six on survivorship, and three on cost. The learning curve was six cases for operating time and zero for precision. There was consistent evidence of more precise implant positioning with MAKO RAUKA. Meta-analysis demonstrated lower overall complication rates associated with MAKO RAUKA (OR 2.18 (95% confidence interval (CI) 1.06 to 4.49); p = 0.040) but no difference in re-intervention, infection, Knee Society Score (KSS; mean difference 1.64 (95% CI -3.00 to 6.27); p = 0.490), or Western Ontario and McMaster Universities Arthritis Index (WOMAC) score (mean difference -0.58 (95% CI -3.55 to 2.38); p = 0.700). MAKO RAUKA was shown to be a cost-effective procedure, but this was directly related to volume. Conclusion. MAKO RAUKA was associated with improved precision of component positioning but was not associated with improved PROMs using the KSS and WOMAC scores. Future longer-term studies should report functional outcomes, potentially using scores with minimal ceiling effects and survival to assess whether the improved precision of MAKO RAUKA results in better outcomes. Cite this article: Bone Joint J 2022;104-B(5):541–548

Background. The complex deformities in cavovarus feet may be difficult to assess and understand. Weight-bearing CT (WBCT) is increasingly used to evaluate complex deformities. However, the bone axes may be difficult to calculate in the setting of severe deformity. Computer-assisted 3D-axis calculation is a novel approach that may allow for more accurate assessment of foot alignment / deformity. The aim of this study was to assess differences in measurements done manually on 2D slices of WBCT versus 3D computer models in normal and cavus feet. Methods. We retrospectively analyzed WBCT scans from 16 normal and 16 cavus feet in patients with Charcot-Marie Tooth. Eight measurements were assessed: Talus-1. st. metatarsal angle (axial plane), Forefoot arch angle (coronal plane), and Meary's angle, calcaneal pitch, cuneiform to floor, cuneiform to skin, navicular to floor and navicular to skin distance (sagittal plane). 2D measurements were performed manually and 3D measurements were performed using specialised software (BoneLogic, DISIOR). Results. There was no significant difference in the measured variables (2D manual versus 3D automated) in normal feet. In the cavus group, 3D assessment calculated increased values for the sagittal angles: Meary's 7.3 degrees greater (p = 0.004), calcaneal pitch 2.4 degrees greater (p = 0.011)), and lower values for the axial talus-1. st. MT angle, 10.6 degrees less (p = 0.001). Conclusion. There were no significant differences in the normal group. This suggests 3D automated techniques can reliably assess the alignment of bony axes. However, the 3D axis calculations suggest there may be greater sagittal and lesser axial deformity in cavus feet than measured by 2D techniques. This discrepancy may be on account of the rotation seen in cavovarus feet, which may not be readily assessed manually. 3D automated measurements may therefore have a role in better assessing and classifying the cavus foot which may ultimately help inform treatment algorithms

Abstract. Objectives. The fidelity of a 3D model created using image segmentation must be precisely quantified and evaluated for the model to be trusted for use in subsequent biomechanical studies such as finite element analysis. The bones within the ankle joint vary significantly in size and shape. The purpose of this study was to test the hypothesis that the accuracy and reliability of a segmented bone geometry is independent of the particular bone being measured. Methods. Computed tomography (CT) scan data (slice thickness 1 mm, pixel size 808±7 µm) from three anonymous patients was used for the development of the ankle geometries (consisting of the tibia, fibula, talus, calcaneus, and navicular bones) using Simpleware Scan IP software (Synopsys, Exeter, UK). Each CT scan was segmented 4 times by an inexperienced undergraduate, resulting in a total of 12 geometry assemblies. An experienced researcher segmented each scan once, and this was used as the ‘gold standard’ to quantify the accuracy. The solid bone geometries were imported into CAD software (Inventor 2023, Autodesk, CA, USA) for measurement of the surface area and volume of each bone, and the distances between bones (tibia to talus, talus to navicular, talus to calcaneus, and tibia to fibula) were carried out. The intra-class coefficient (ICC) was used to assess intra-observer reliability. Bland Altman plots were employed as a statistical measure for criteria validity (accuracy) [1]. Results. The average ICC score was 0.93, which is regarded as a high reliability score for an inexperienced user. The talus to navicular and talus to tibia separations, which had the smallest distances, showed a slight decrease in reliability and this was observed for all separations shorter than 2 mm. According to the Bland-Altman plots, more than 95% of the data points were inside the borders of agreement, which is an excellent indication of accuracy. The bias percentage (average error percentage) varied between 1% and 4% and was constant across all parameters, with the proportion rising for short distance separations. Conclusions. The current study demonstrates that an inexperienced undergraduate, with access to software manuals, can segment an ankle CT scan with excellent reliability. The present study also concluded that all five bones were segmented with high levels of accuracy, and this was not influenced by bone volume or type. The only factor found to influence the reliability was the magnitude of distance between bones, where if this was smaller than 2 mm it reduced the reliability, indicating the influence of CT scan resolution on the segmentation reliability. Declaration of Interest. (b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project

Introduction. The purpose of this study was to compare the radiographic outcomes of manual versus robotic-assisted medial unicompartmental knee arthroplasty (UKA). Materials & Methods. Postoperative radiographic outcomes from 86 consecutive robotic-assisted UKAs (RAUKA group) from a single academic center were retrospectively reviewed and compared to 253 manual UKAs (MUKA group) drawn from a prior study at our institution. Femoral coronal and sagittal angles (FCA, FSA), tibial coronal and sagittal angles (TCA, TSA), and implant overhang were radiographically measured to identify outliers. Clinical results at 4–6 weeks postoperative were compared to a control cohort of total knee arthroplasty (TKA) patients from our institution. Results. When assessing the accuracy of RAUKAs, 91.6% of all alignment measurements and 99.2% of all overhang measurements were within the target range. All alignment and overhang targets were simultaneously met in 68.6% of RAUKAs. When comparing radiographic outcomes between the RAUKA and MUKA groups, statistically significant differences were identified for combined outliers in FCA (2.3% vs. 12.6%, p=0.006), FSA (17.4% vs. 50.2%, p<0.001), TCA (5.8% vs. 41.5%, p<0.001), and TSA (8.1% vs. 18.6%, p=0.023), as well as anterior (0.0% vs. 4.7%, p=0.042), posterior (1.2% vs. 13.4%, p=0.001), and medial (1.2% vs. 14.2%, p<0.001) overhang outliers. RAUKA demonstrated statistically significant improvements in pain and outcomes compared to TKA at 4–6 weeks (p<0.05). Conclusions. Robotic navigation decreases alignment and overhang outliers compared to manual UKA and improves clinical results compare to TKA in the early postoperative period. Given the association between component placement errors and revision in UKA, this strong significant improvement in accuracy is likely to improve implant survival

Aims. The primary aim of this study was to compare the hip-specific functional outcome of robotic assisted total hip arthroplasty (rTHA) with manual total hip arthroplasty (mTHA) in patients with osteoarthritis (OA). Secondary aims were to compare general health improvement, patient satisfaction, and radiological component position and restoration of leg length between rTHA and mTHA. Methods. A total of 40 patients undergoing rTHA were propensity score matched to 80 patients undergoing mTHA for OA. Patients were matched for age, sex, and preoperative function. The Oxford Hip Score (OHS), Forgotten Joint Score (FJS), and EuroQol five-dimension questionnaire (EQ-5D) were collected pre- and postoperatively (mean 10 months (SD 2.2) in rTHA group and 12 months (SD 0.3) in mTHA group). In addition, patient satisfaction was collected postoperatively. Component accuracy was assessed using Lewinnek and Callanan safe zones, and restoration of leg length were assessed radiologically. Results. There were no significant differences in the preoperative demographics (p ≥ 0.781) or function (p ≥ 0.383) between the groups. The postoperative OHS (difference 2.5, 95% confidence interval (CI) 0.1 to 4.8; p = 0.038) and FJS (difference 21.1, 95% CI 10.7 to 31.5; p < 0.001) were significantly greater in the rTHA group when compared with the mTHA group. However, only the FJS was clinically significantly greater. There was no difference in the postoperative EQ-5D (difference 0.017, 95% CI -0.042 to 0.077; p = 0.562) between the two groups. No patients were dissatisfied in the rTHA group whereas six were dissatisfied in the mTHA group, but this was not significant (p = 0.176). rTHA was associated with an overall greater rate of component positioning in a safe zone (p ≤ 0.003) and restoration of leg length (p < 0.001). Conclusion. Patients undergoing rTHA had a greater hip-specific functional outcome when compared to mTHA, which may be related to improved component positioning and restoration of leg length. However, there was no difference in their postoperative generic health or rate of satisfaction. Cite this article: Bone Joint Res 2021;10(1):22–30

Patients with advanced cancer can develop bone metastases in the femur which are often painful and increase the risk of pathological fracture. Accurate segmentation of bone metastases is, amongst others, important to improve patient-specific computer models which calculate fracture risk, and for radiotherapy planning to determine exact radiation fields. Deep learning algorithms have shown to be promising to improve segmentation accuracy for metastatic lesions, but require reliable segmentations as training input. The aim of this study was to investigate the inter- and intra-operator reliability of manual segmentation of femoral metastatic lesions and to define a set of lesions which can serve as a training dataset for deep learning algorithms. F. CT-scans of 60 advanced cancer patients with a femur affected with bone metastases (20 osteolytic, 20 osteoblastic and 20 mixed) were used in this study. Two operators were trained by an experienced radiologist and then segmented the metastatic lesions in all femurs twice with a four-week time interval. 3D and 2D Dice coefficients (DCs) were calculated to quantify the inter- and intra-operator reliability of the segmentations. We defined a DC>0.7 as good reliability, in line with a statistical image segmentation study. Mean first and second inter-operator 3D-DCs were 0.54 (±0.28) and 0.50 (±0.32), respectively. Mean intra-operator I and II 3D-DCs were 0.56 (±0.28) and 0.71 (±0.23), respectively. Larger lesions (>60 cm. 3. ) scored higher DCs in comparison with smaller lesions. This study reveals that manual segmentation of metastatic lesions is challenging and that the current manual segmentation approach resulted in dissatisfying outcomes, particularly for lesions with small volumes. However, segmentation of larger lesions resulted in a good inter- and intra-operator reliability. In addition, we were able to select 521 slices with good segmentation reliability that can be used to create a training dataset for deep learning algorithms. By using deep learning algorithms, we aim for more accurate automated lesion segmentations which might be used in computer modelling and radiotherapy planning

Accurate cup placement in total hip arthroplasty (THA) for the patients with developmental dysplasia of the hip (DDH) is one of the challenges due to distinctive bone deformity. Robotic-arm assisted system have been developed to improve the accuracy of implant placement. This study aimed to compare the accuracy of robotic-arm assisted (Robo-THA), CT-based navigated (Navi-THA), and manual (M-THA) cup position and orientation in THA for DDH. A total of 285 patients (335 hips) including 202 M-THAs, 45 Navi-THAs, and 88 Robo-THA were analyzed. The choice of procedure followed the patient's preferences. Horizontal and vertical center of rotation (HCOR and VCOR) were measured for cup position, and radiographic inclination (RI) and anteversion (RA) were measured for cup orientation. The propensity score-matching was performed among three groups to compare the absolute error from the preoperative target position and angle. Navi-THA showed significantly smaller absolute errors than M-THA in RI (3.6° and 5.4°) and RA (3.8° and 6.0°), however, there were no significant differences between them in HCOR (2.5 mm and 3.0 mm) or VCOR (2.2 mm and 2.6 mm). In contrast, Robo-THA showed significantly smaller absolute errors of cup position than both M-THA and Navi-THA (HCOR: 1.7 mm and 2.9 mm, vs. M-THA, 1.6 mm and 2.5 mm vs. Navi-THA, VCOR:1.7 mm and 2.4 mm, vs. M-THA, 1.4 mm and 2.2 mm vs. Navi-THA). Robo-THA also showed significantly smaller absolute errors of cup orientation than both M-THA and Navi-THA (RI: 1.4° and 5.7°, vs. M-THA, 1.5° and 3.6°, vs. Navi-THA, RA: 1.9° and 5.8° vs. M-THA, 2.1° and 3.8° vs. Navi-THA). Robotic-arm assisted system showed more accurate cup position and orientation compared to manual and CT-based navigation in THA for DDH. CT-based navigation increased the accuracy of cup orientation compared to manual procedures, but not cup position

We present an analysis of manual and computer-assisted preoperative pedicle screw placement planning. Preoperative planning of 256 pedicle screws was performed manually twice by two experienced spine surgeons (M1 and M2) and automatically once by a computer-assisted method (C) on three-dimensional computed tomography images of 17 patients with thoracic spinal deformities. Statistical analysis was performed to obtain the intraobserver and interobserver variability for the pedicle screw size (i.e. diameter and length) and insertion trajectory (i.e. pedicle crossing point, sagittal and axial inclination, and normalized screw fastening strength). In our previous study, we showed that the differences among both manual plannings (M1 and M2) and computer-assisted planning (C) are comparable to the differences between manual plannings, except for the pedicle screw inclination in the sagittal plane. In this study, however, we obtained also the intraobserver variability for both manual plannings (M1 and M2), which revealed that larger differences occurred again for the sagittal screw inclination, especially in the case of manual planning M2 with average differences of up to 18.3°. On the other hand, the interobserver variability analysis revealed that the intraobserver variability for each pedicle screw parameter was, in terms of magnitude, comparable to the interobserver variability among both manual and computer-assisted plannings. The results indicate that computer-assisted pedicle screw placement planning is not only more reproducible and faster than, but also as reliable as manual planning

Introduction. Existing studies report more accurate implant placement with robotic-assisted unicompartmental knee arthroplasty (UKA); however, surgeon experience has not always been accounted for. The purpose of this study was to compare the accuracy of an experienced, high-volume surgeon to published data on robotic-assisted UKA tibial component alignment. Methods. One hundred thirty-one consecutive manual UKAs performed by a single surgeon using a cemented, fixed bearing implant were radiographically reviewed by an independent reviewer to avoid surgeon bias. Native and tibial implant slope and coronal alignment were measured on pre- and postoperative lateral and anteroposterior radiographs, respectively. Manual targets were set within 2° of native tibial slope and 0 to 2° varus tibial component alignment. Deviations from target were calculated as root mean square (RMS) errors and were compared to robotic-assisted UKA data. Results. One hundred twenty-eight UKAs were analyzed. The proportion of manual UKAs within the target for tibial component alignment (66%) exceeded published values comparing robotic (58%) to manual (41%) UKA. RMS error for tibial component alignment (1.5°) was less than published RMS error rates in robotic UKAs (range 1.8 to 5°). Fifty-eight percent of study UKAs were within the surgeon's preoperative goal for tibial slope, closer to published findings of 80% for robotic UKAs vs. 22% of manual UKAs. RMS error for tibial slope in study UKAs (1.5°) was smaller than RMS error rates for tibial slope in robotic UKAs (range 1.6 to 1.9°). Conclusion. These data demonstrate that an experienced, high-volume surgeon's accuracy in manual UKA can meet or exceed robotic-assisted UKA. Therefore, a surgeon's experience and aptitude should be taken into account when determining the value of robotics in knee arthroplasty. Further, the relationship between implant position and patient outcomes, and consensus on ideal surgical targets for optimal survivorship need further elucidation

Introduction. Component position and overall limb alignment following total knee arthroplasty (TKA) have been shown to influence prosthetic survivorship and clinical outcomes. Robotic-assisted (RA) total knee arthroplasty has demonstrated improved accuracy to plan in cadaver studies compared to conventionally instrumented (manual) TKA, but less clinical evidence has been reported. The objective of this study was to compare the three-dimensional accuracy to plan of RATKA with manual TKA for overall limb alignment and component position. Methods. A non-randomized, prospective multi-center clinical study was conducted to compare RATKA and manual TKA at 4 U.S. centers between July 2016 and August 2018. Computed tomography (CT) scans obtained approximately 6 weeks post-operatively were analyzed using anatomical landmarks. Absolute deviation from surgical plans were defined as the absolute value of the difference between the CT measurements and surgeons’ operative plan for overall limb, femoral and tibial component mechanical varus/valgus alignment, tibial component posterior slope, and femoral component internal/external rotation. We tested the differences of absolute deviation from plan between manual and RATKA groups using stratified Wilcoxon tests, which controlled for study center and accounted for skewed distributions of the absolute values. Alpha was 0.05 two-sided. At the time of this abstract, data collections were completed for two centers (52 manual and 58 RATKA). Results. Comparing absolute deviation from plan between groups, RATKA demonstrated clear benefits for tibial component alignment (median absolute deviation from plan: 1.5° vs. 0.8°, manual vs RATKA, p<.001), tibial slope (2.7° vs. 1.1°, manual vs RATKA, p<.001), and femoral component rotation (1.4° vs. 0.9°, manual vs RATKA, p<0.02). Femoral component and overall limb alignment accuracy were comparable (p>0.10). Discussion and Conclusions. In this study, compared to manual TKA, RATKA cases were 47% more accurate for tibial component alignment, 59% more accurate for tibial slope, and 36% more accurate for femoral component rotation (percent differences of median absolute deviations from plan). Further clinical data is needed to study the longer-term benefits of robotic technologies. Nevertheless, this study supports improved accuracy to plan utilizing RATKA compared to manual TKA. For any figures or tables, please contact authors directly

Abstract. Objectives. Total hip arthroplasty (THA) procedures are physically demanding for surgeons. Repetitive mallet swings to impact a surgical handle (impactions), can lead to muscle fatigue, discomfort and injuries. The use of an automated surgical hammer may reduce fatigue and increase surgical efficiency. The aim of this study was to develop a method to quantify user's performance, by recording surface electromyography (sEMG), for automated and manual impactions. Methods. sEMG signals were recorded from eight muscle compartments (arm and back muscles) of an orthopaedic surgeon during repetitions of manual and automated impaction tasks, replicating femoral canal preparation (broaching) during a THA. Each task was repeated, randomly, four times manually and four times with the automated impaction device. The mechanical outcomes (broaching efficiency and broach advancement) were quantified by tracking the kinematics of the surgical instrumentation. Root mean square (RMS) values and median frequency (MDF) were calculated for each task to, respectively, investigate which muscles were mostly involved (higher RMS) in each task and to quantify the decrease in MDF, which is an indicator of muscle fatigue. Results. RMS for arm muscles was significantly higher (p-value=0.002) during manual impactions than during automated impactions and muscle fatigue was significantly reduced (p-value=0.011), for the same muscles, when the same tasks were performed with the automated surgical hammer. The time required to achieve the same mechanical outcome, in terms of broaching efficiency and broach advancement, was significantly reduced with the automated surgical hammer (p=0.019). Conclusions. Results from this study showed how with this methodology it was possible to discern muscle performance and fatigue, between impaction modalities. Moreover, the reduction in exposure time to automated impactions, could be a factor in muscle fatigue decrease. These results could therefore provide useful insights into the study of surgical ergonomic improvements, to reduce surgeons muscle fatigue and, potentially, injuries. Declaration of Interest. (a) fully declare any financial or other potential conflict of interest