Aims. The primary aim of this study was to determine the surgical team’s learning curve for introducing robotic-arm assisted unicompartmental knee arthroplasty (UKA) into routine surgical practice. The secondary objective was to compare accuracy of implant positioning in conventional jig-based UKA versus robotic-arm assisted UKA. Patients and Methods. This prospective single-surgeon cohort study included 60 consecutive conventional jig-based UKAs compared with 60 consecutive robotic-arm assisted UKAs for medial compartment knee osteoarthritis. Patients undergoing conventional UKA and robotic-arm assisted UKA were well-matched for baseline characteristics including a mean age of 65.5 years (. sd. 6.8) vs 64.1 years (. sd. 8.7), (p = 0.31); a mean body mass index of 27.2 kg.m2 (. sd. 2.7) vs 28.1 kg.m2 (. sd. 4.5), (p = 0.25); and gender (27 males: 33 females vs 26 males: 34 females, p = 0.85). Surrogate measures of the learning curve were prospectively collected. These included operative times, the Spielberger State-Trait Anxiety Inventory (STAI) questionnaire to assess preoperative stress levels amongst the surgical team, accuracy of implant positioning, limb alignment, and postoperative complications. Results. Robotic-arm assisted UKA was associated with a learning curve of six cases for operating time (p < 0.001) and surgical team confidence levels (p < 0.001). Cumulative robotic experience did not affect accuracy of implant positioning (p = 0.52), posterior condylar offset ratio (p = 0.71), posterior tibial slope (p = 0.68), native joint line preservation (p = 0.55), and postoperative limb alignment (p = 0.65). Robotic-arm assisted UKA improved accuracy of femoral (p < 0.001) and tibial (p < 0.001) implant positioning with no additional risk of postoperative complications compared to conventional jig-based UKA. Conclusion. Robotic-arm assisted UKA was associated with a learning curve of six cases for operating time and surgical team confidence levels but no learning curve for accuracy of implant positioning. Cite this article: Bone Joint J 2018;100-B:1033–42

Aims. Periacetabular osteotomy (PAO) is widely recognized as a demanding surgical procedure for acetabular reorientation. Reports about the learning curve have primarily focused on complication rates during the initial learning phase. Therefore, our aim was to assess the PAO learning curve from an analytical perspective by determining the number of PAOs required for the duration of surgery to plateau and the accuracy to improve. Methods. The study included 118 consecutive PAOs in 106 patients. Of these, 28 were male (23.7%) and 90 were female (76.3%). The primary endpoint was surgical time. Secondary outcome measures included radiological parameters. Cumulative summation analysis was used to determine changes in surgical duration. A multivariate linear regression model was used to identify independent factors influencing surgical time. Results. The learning curve in this series was 26 PAOs in a period of six months. After 26 PAO procedures, a significant drop in surgical time was observed and a plateau was also achieved. The mean duration of surgery during the learning curve was 103.8 minutes (SD 33.2), and 69.7 minutes (SD 18.6) thereafter (p < 0.001). Radiological correction of acetabular retroversion showed a significant improvement after having performed a total of 93 PAOs, including anteverting PAOs on 35 hips with a retroverted acetabular morphology (p = 0.005). Several factors were identified as independent variables influencing duration of surgery, including patient weight (β = 0.5 (95% confidence interval (CI) 0.2 to 0.7); p < 0.001), learning curve procedure phase of 26 procedures (β = 34.0 (95% CI 24.3 to 43.8); p < 0.001), and the degree of lateral correction expressed as the change in the lateral centre-edge angle (β = 0.7 (95% CI 0.001 to 1.3); p = 0.048). Conclusion. The learning curve for PAO surgery requires extensive surgical training at a high-volume centre, with a minimum of 50 PAOs per surgeon per year. This study defined a cut-off value of 26 PAO procedures, after which a significant drop in surgical duration occurred. Furthermore, it was observed that a retroverted morphology of the acetabulum required a greater number of procedures to acquire proficiency in consistently eliminating the crossover sign. These findings are relevant for fellows and fellowship programme directors in establishing the extent of training required to impart competence in PAO. Cite this article: Bone Joint J 2024;106-B(4):336–343

Aims

Traditionally, acetabular component insertion during total hip arthroplasty (THA) is visually assisted in the posterior approach and fluoroscopically assisted in the anterior approach. The present study examined the accuracy of a new surgeon during anterior (NSA) and posterior (NSP) THA using robotic arm-assisted technology compared to two experienced surgeons using traditional methods.

Unicompartmental knee arthroplasty (UKA) has a higher risk of revision than total knee arthroplasty, particularly for low volume surgeons. The recent introduction of robotic-arm assisted systems has allowed for increased accuracy, however new systems typically have learning curves. The objective of this study was to determine the learning curve of a robotic-arm assisted system for UKA. Methods A total of 152 consecutive robotic-arm assisted primary medial UKA were performed by five surgeons between 2017 and 2021. Operative times, implant positioning, reoperations and patient-reported outcome measures (PROMS; Oxford Knee Score, EuroQol-5D, and Forgotten Joint Score) were recorded. There was a learning curve of 11 cases with the system that was associated with increased operative time (13 minutes, p<0.01) and improved insert sizing over time (p=0.03). There was no difference in implant survival (98.2%) between learning and proficiency phases (p = 0.15), and no difference in survivorship between ‘high’ and ‘low’ usage surgeons (p = 0.23) at 36 months. There were no differences in PROMS related to the learning curve. This suggested that the learning curve did not lead to early adverse effects in this patient cohort. The introduction of a robotic-arm assisted UKA system led to learning curves for operative time and implant sizing, but there was no effect on patient outcomes at early follow- up. The short learning curve was independent of UKA usage and indicated that robotic-arm assisted UKA may be particularly useful for low-usage surgeons

Source of the study: University of Auckland, Auckland, New Zealand. Unicompartmental knee arthroplasty (UKA) has benefits for patients with appropriate indications. However, UKA has a higher risk of revision, particularly for low-usage surgeons. The introduction of robotic-arm assisted systems may allow for improved outcomes but is also associated with a learning curve. We aimed to characterise the learning curve of a robotic-arm assisted system (MAKO) for UKA in terms of operative time, limb alignment, component sizing, and patient outcomes. Operative times, pre- and post-surgical limb alignments, and component sizing were prospectively recorded for consecutive cases of primary medial UKA between 2017 and 2021 (n=152, 5 surgeons). Patient outcomes were captured with the Oxford Knee Score (OKS), EuroQol-5D (EQ-5D), Forgotten Joint Score (FJS-12) and re-operation events up to two years post-UKA. A Cumulative Summation (CUSUM) method was used to estimate learning curves and to distinguish between learning and proficiency phases. Introduction of the system had a learning curve of 11 cases. There was increased operative time of 13 minutes between learning and proficiency phases (learning 98 mins vs. proficiency 85 mins; p<0.001), associated with navigation registration and bone preparation/cutting. A learning curve was also found with polyethylene insert sizing (p=0.03). No difference in patient outcomes between the two phases were detected for patient-reported outcome measures, implant survival (both phases 98%; NS) or re-operation (learning 100% vs. proficiency: 96%; NS). Implant survival and re-operation rates did not differ between low and high usage surgeons (cut-off of 12 UKAs per year). Introduction of the robotic-arm assisted system for UKA led to increased operative times for navigation registration and bone preparation, but no differences were detected in terms of component placement or patient outcomes regardless of usage. The short learning curve regardless of UKA usage indicated that robotic-arm assisted UKA may be particularly useful for low-usage surgeons

INTRODUCTION. The direct anterior approach (DAA) for total hip arthroplasty has become a popular technique. Proponents of the anterior approach cite advantages such as less muscle damage, lower dislocation risk, faster recovery, and more accurate implant placement for the approach. However, there is a steep, complex learning curve associated with the technique. The present study seeks to define the learning curve based on individual surgical and outcome variables for a high-volume surgeon. METHODS. 300 consecutive patients were retrospectively analyzed. Intraoperative outcomes measured include surgery time and estimated blood loss (EBL). Complications include intraoperative fracture, post-operative fracture, infection, dislocation, leg length discrepancy, loosening, and medical complications such as deep vein thrombosis (DVT) and pulmonary embolism (PE). Segmented regression models were used to elucidate the presence of a learning curve and mastery of the procedure with regard to each individual variable. RESULTS. The mean operative time was 77.1 minutes (range 40–213). Operative time improved at a rate of 6.6 minutes per case for the first 15 cases then by an average of 5 seconds per subsequent case. The mean EBL for the series was 288.6 mL. Segmented regression shows EBL decreased at a rapid rate until case 52, followed by a more gradual decline. Complications were higher in the first 7 surgeries, with a 48% decrease in the likelihood of complication with each subsequent surgery. The improvement continued through the rest of the series with a 0.5% decrease in likelihood with each surgery. DISCUSSION. Our data contributes to the current body of literature by defining the learning curve with what we consider the most pertinent outcomes. First, we show that operative efficiency can be gained quite quickly (15 cases) while the slower improvement in EBL demonstrates continued learning about the anatomy. Our data is consistent with previous published reports regarding complication improvement. The present study will provide surgeons considering DAA useful information regarding what to expect during their learning curve. Furthermore, the data can be useful for surgeons charged with teaching the technique to critically evaluate what learning curve variables can be improved to hasten the learning curve

The introduction of robotics for total knee arthroplasty (TKA) into the operating theatre is often associated with a learning curve and is potentially associated with additional complications. The purpose of this study was to determine the learning curve of robotic-assisted (RA) TKA within a multi-surgeon team. This prospective cohort study included 83 consecutive conventional jig-based TKAs compared with 53 RA TKAs using the Robotic Surgical Assistant (ROSA) system (Zimmer Biomet, Warsaw, Indiana, USA) for knee osteoarthritis performed by three high-volume (> 100 TKA per year) orthopaedic surgeons. Baseline characteristics including age, BMI, sex and pre-operative Kellgren-Lawrence grade were well-matched between the conventional and RA TKA groups. Cumulative summation (CUSUM) analysis was used to assess learning curves for operative times for each surgeon. Peri-operative and delayed complications were reviewed. The CUSUM analysis for operative time demonstrated an inflexion point after 5, 6 and 15 cases for each of the three surgeons, or 8.7 cases on average. There were no significant differences (p = 0.53) in operative times between the RA TKA learning (before inflexion point) and proficiency (after inflexion point) phases. Similarly, the operative times of the RA TKA group did not differ significantly (p = 0.92) from the conventional TKA group. There was no discernible learning curve for the accuracy of component planning using the RA TKA system. The average length of post-operative follow-up was 21.3 ± 9.0 months. There was no significant difference (p > 0.99) in post-operative complication rates between the groups. The introduction of the RA TKA system was associated with a learning curve for operative time of 8.7 cases. Operative times between the RA TKA and conventional TKA group were similar. The short learning curve implies this RA TKA system can be adopted relatively quickly into a surgical team with minimal risks to patients

Robotic assistance in knee arthroplasty has become increasingly popular due to improved accuracy of prosthetic implantation. However, literature on the mid-term outcomes is limited especially that of hand-held robotic-assisted devices. We present one of the longest follow-up series to date using this novel technology and discuss the learning curve for introducing robotic technology into our practice. The purpose of this single-surgeon study is to evaluate the survival, patient-reported outcomes and learning curve for handheld boundary-controlled robotic-assisted unicompartmental knee arthroplasties (HBRUKAs) at our hospital. This retrospective study evaluates 100 cases (94 Medial, 6 Lateral) performed by a single surgeon between October 2012 and July 2018. 52% were males, mean age was 64.5y (range 47.3y-85.2y) and mean BMI was 31.3 (range 21.8–43). Both inlay (40%) and onlay (60%) designs were implanted. Patients were followed up routinely at 1 and 5 years with Oxford Knee Scores (OKS) recorded. The learning curve was determined by tourniquet times. At a mean follow-up of 4.3 years (range 1.6y–7.3y), survivorship was 97%. There were three revisions: One case of aseptic loosening (1.5y), one case of deep-infection (3.8y) and one case of contralateral compartment osteoarthritis progression (5y). Mean 5-year OKS was 39.8. A 14.3% reduction in mean tourniquet times between the first 25 cases (105.5minutes) and subsequent cases (90.4minutes) was seen. This single-surgeon study showed good survivorship and patient-reported outcomes for HBRUKAs at our hospital. A learning curve of approximately 25 cases was shown, with significant decreases in tourniquet times with respect to increased surgeon experience

Introduction: A learning curve is a recognised phenomenon in surgery. It implies that the frequency of peri-operative adverse events will decrease with the increase in experience of the surgeon. Evidence shows increased instruction and experience in a specific surgical task leads to improved performance. There is conflicting evidence as to whether there is a learning curve for total ankle replacement, and a paucity of evidence for foot and ankle surgery as a whole. Current evidence is centered on perioperative complications, rather than functional outcome. Aim: To determine whether a learning curve effect is present during the first year of independent practice by measuring patient outcome. Materials and Methods: 150 patients underwent elective foot or ankle surgery during the first 12 months of a newly appointed consultant’s practice. Preoperative and six month postoperative functional scores were recorded, together with perioperative complications. Two patients died of unrelated causes in the first 12 months. 121 patients (81.8%) were followed up for a minimum of six months by telephone. Functional outcome was assessed with a modified American Orthopaedic Foot and Ankle Society midfoot Score (85 points). Outcome was compared between the first and second six-month periods using the student’s t-test. Results: Eighty procedures were undertaken during the first six months compared to 70 in the second. Total ankle replacements were only undertaken in the latter period. Otherwise there was no statistical difference in the caseload. One wound infection occurred during each period and other perioperative complications were equivalent. Functional improvement was greater in the group from the second 6 months (+23.86 v’s +18.69). This difference did not reach statistical significance (p = 0.061). Discussion and Conclusion: There is a trend, approaching significance, towards a learning curve during a foot and ankle consultant surgeon’s first year of practice. Collating data from other new consultants may demonstrate a learning curve with statistical significance

Background. Several recent reports have documented high frequency of malpositioned acetabular components, even amongst high volume arthroplasty surgeons. Robotic assisted total hip arthroplasty (THA) has the potential to improve component positioning; however, to our knowledge there are no reports examining the learning curve during the adoption of robotic assisted THA. Purpose. The purpose of this study was to examine the learning curve of robotic assisted THA as measured by component position, operative time, intra-operative technical problems, and complications. Methods. The first 105 robotic-assisted THAs performed by a single surgeon with a posterior approach from June 2011 to August 2013 patients were divided into three groups based on the order of surgery. Group A was cases 1–35, group B 36–70 and group C 71–105. Component position, operative time, intra-operative technical problems, and intra-operative complications were recorded. Results. There was no significant difference between groups A, B, and C for BMI or age (Figure 1). Gender was different between groups with 20 males in group A, 9 in group B, and 16 in group C (p < 0.05). There was no difference for mean acetabular inclination, acetabular anteversion, or leg length discrepancy between groups as experience increased (p > 0.05) (Figure 2). The average operative time for groups A, B, and C was 79.8 ± 27 min, 63.2 ± 14.2 min, and 69.4 ± 16.3 min respectively (p = 0.02). The cumulative number of outliers was two for the Lewenick safe zone and six for the Callanan safe zone. Figure 3 displays acetabular component positioning in relation to previously documented safe zones for the three groups. The risk of having an acetabular component outside of Lewenick's safe zone was not different between groups (p = 0.60). The risk of having an acetabular component outside of Callanan's safe zone decreased after group A and was statistically significant (p = 0.02). Overall there were nine (9%) intra-operative technical problems and complications. In group A there were three complications: one loosened femoral array, one loosened pelvic array, and one cup that appeared erroneous according to the navigation system. In group B there was one femoral calcar fracture treated with a cerclage wire, one loosened femoral array, and one intra-operative delay. In group C there were three technical problems, all a loosened femoral array. There was no difference in the overall number of intra-operative complications between groups (p = 1.0). Conclusion. A learning curve was observed, as a decreased incidence of acetabular component outliers and decreased operative time were noted with increased experience. Satisfactory acetabular component positioning and leg length matching were found throughout the learning curve of robotic assisted total hip arthroplasty, with very few outliers in either category. Based on these findings, we conclude that there is a learning curve of approximately 35 cases in robotic-assisted total hip arthroplasty

Summary Statement. Uptake of robotically-assisted orthopaedic surgery may be limited by a perceived steep learning curve. We quantified the technological learning curve and 5 surgeries were found to bring operating times to appropriate levels. Implant positioning was as planned from the outset. Introduction. Compared to total knee replacement, unicondylar knee replacement (UKR) has been found to reduce recovery time as well as increase patient satisfaction and improve range of motion. However, contradictory evidence together with revision rates concern may have limited the adoption of UKR surgery. Semi-active robotically-assisted orthopaedic tools have been developed to increase the accuracy of implant position and subsequent mechanical femorotibial angle to reduce revision rates. However, the perceived learning curve associated with such systems may cause apprehension among orthopaedic surgeons and reduce the uptake of such technology. To inform this debate, we aimed to quantify the learning curve associated with the technological aspects of the NavioPFS™ (Blue Belt Technologies Inc., Pittsburgh, USA) with regards to both operation time and implant accuracy. Methods. Five junior orthopaedic trainees volunteered for the study following ethical permission. All trainees attended the same initial training session and subsequently each trainee performed 5 UKR surgeries on left-sided synthetic femurs and tibiae (model 1146–2, Sawbones-Pacific Research Laboratories Inc, Vashon, WA, USA). A few days lapsed between surgeries, which were all completed in a two week window. Replica Tornier HLS Uni Evolution femoral and tibial implants (Tornier, France) were implanted without cementation. Each surgery was videoed and timings taken for key operation phases, as well as the overall operative time. A ball point probe with four reflective spherical markers attached was used to record the position of manufactured divots on the implant, which allowed the 3D position of the implant to be compared to the planned position. Absolute translational and rotational deviations from the planned position were analysed. Results. Total surgical time decreased significantly with surgery number (p < 0.001) from an initial average of 85 minutes to 48 minutes after 5 surgeries. All stages, except the cutting tool set up, demonstrated a significant difference in operative time with increasing number of surgeries performed (all p < 0.05) with the cutting phase decreasing from 41 to 23 minutes (p < 0.001). The translational and rotational accuracy of the implants did not significantly vary with surgery number. Discussion and Conclusion. The accuracy in implant position obtained by trainee surgeons on synthetic bones were similar to published data for experienced orthopaedic surgeons on other systems on cadavers. Whilst cadaver operations increase the complexity of operation, this should not theoretically affect the robotic system in preventing innaccurate implantation. Moreover, the fact that this accuracy was obtainable on the first surgery clearly demonstrates the system's ability in ensuring accurate implantation. Five surgeries dramatically reduced the total operative time, and moreover, the trend suggests that more surgeries would further decrease the total operation time. It was not the intention of the study to compare absolute trainee times on synthetic bones to surgeons with cadavers, but the learning curve of the protocol and technology suggests a halving of the operation time after 5 sessions would not be unrealistic

Introduction. Semi-active robots can improve the accuracy and precision of total knee arthroplasty (TKA). The surgical efficiency of the recently introduced NAVIO robotic-assisted (RA-TKA) surgery was assessed in this study to define: (1) the time commitment for RA-TKA; (2) the learning curve for RA-TKA; and (3) to compare RA-TKA surgical time commitment to conventional, instrumented TKA (CI-TKA). Materials and Methods. Beginning in May 2017, the first 100 patients undergoing NAVIO RA-TKA were registered pre-operatively. Operative time, defined as the time from surgical skin incision to capsular closure, was recorded. Exclusion criteria were cases in which surgical time was not recorded. During the same study period, surgical case times for fifty cases of CI-TKA procedures were also assessed. Baseline data, including age, gender, BMI, range of motion, was recorded for all subjects. Surgical and anesthetic technique, multi-modality pain management protocol, and post-operative mobilization was consistent for all patients enrolled in the study. Results. No cases were excluded due to missing data. Demographics were similar in the study groups. Average surgical time for the first 100 RA-TKA cases was 68.2 minutes (range 48–100 minutes). The learning curve, as defined by both absolute (added surgical time) and relative measures (percentage of added time) was forty cases. Significant further surgical efficiency was achieved after 80 cases. In comparison to CI-TKA (average surgical time 51.7 minutes), the first ten RA-TKA cases required an average of 80 minutes, or over 50% increase in surgical time. After case #40, RA-TKA took only 10 minutes longer (18% greater) than CI-TKA. After case #80, RA-TKA required less than 5% more time than RA-TKA. Discussion/Conclusions. The initial experience with the NAVIO RA-TKA produced predictable surgical efficiency as measured by surgical time commitment. The learning curve for this user was forty cases. After eighty cases, RA-TKA was time neutral (<5% added time). This study demonstrates that implementation of robotic-assisted technology in TKA can achieve a high level of surgical efficiency within an acceptable learning curve

Introduction. The FitBone lengthening nail (Orthofix UK) is an intramedullary device licensed for the lengthening of long bones in adults in the UK. It contains a motor powered by electricity transmitted via an induction coil placed underneath the skin. It was developed in Germany two decades ago but uptake in the UK has only started more recently. The aim of this study was to review the first cohort of FitBone lengthening nails in a unit with significant experience of other lengthening nails (including PRECICE and Stryde). Materials & Methods. Demographic, clinical and radiological data was prospectively collected on all FitBone cases starting in February 2022. Accuracy of lengthening rate, patient satisfaction and implant issues were all considered. Complications and learning points were recorded and discussed by the multidisciplinary team involved in the patients care. Results. Eleven lengthening nails were inserted between February and November 2022 (6 right femurs, 5 left femurs). The average patient age was 31 (16–57) with 4 females and 7 males. The average lengthening achieved was 44mm (13– 70) over an average of 59 days (35 to 104). Significant technical issues were encountered in this cohort of patients including slow opening up at osteotomy site (3 requiring speeding up of programme), early consolidation (one requiring re-do osteotomy) and backing out of locking screws (3 out of 11 nails). There were also patient use concerns with difficulty using the motor and the inability to reverse the lengthening without an additional component to the motor. Conclusions. We present the first UK cohort of patients with femoral lengthening using the FitBone implant and device. We highlight the technical and patient issues encountered during this learning curve and propose solutions to avoid these pitfalls

Aim: The purpose of this study is to explore the experience of a consultant orthopaedic surgeon, and to quantitatively describe the learning curve for hip arthroscopy. Introduction: Arthroscopic surgery in orthopaedics is a well established procedure for both diagnostic and therapeutic purposes. Unlike many other joint arthroscopies, hip arthroscopy has been delayed in its development. It was first pioneered by Burman in 1931, who under-took a study on cadavers, stating that ‘it is manifestly impossible to insert a needle between the head of the femur and the acetabulum’. Over several decades, this technique has developed considerably, but still remains a technically demanding and difficult procedure. The learning curve for hip arthroscopy has not previously been objectively quantified. Method: We prospectively reviewed the first 100 hip arthroscopies performed in the supine position between 1999 and 2004. Surgery was performed by a single experienced hip and knee consultant orthopaedic surgeon (FH). We assessed the operative time (traction time), surgeon comfort, patient satisfaction at 6 months and operative complications. This was analysed for consecutive blocks of 10 cases. Results of the first 10 and the remaining 90 cases, subsequently the first 20 and remaining 80 cases, and finally the first 30 and remaining 70 cases were compared for a difference. Results: The mean traction time was 55 minutes (range: 36–94 minutes). Mean surgeon comfort was 73% (range: 52–89%). 49% of patients reported an excellent outcome at 6 months follow – up. Only 8% of patients reported an unsatisfactory outcome. The main complications noted were chondral damage (6 cases) and perineal injuries (4 cases). There was a remarkable decrease in complications from the first 30 cases compared to the remaining 70 operations. 5 cases of chondral damage was noted in the first 30 cases, compared to 1 (1.4%) in the remaining 70 cases. The number of perineal injuries was noted to decrease from 3 cases in the first 30 operations to 1 (1.4%) in the subsequent 70 operations. There is an overall decrease in operative time over the 100 cases, representing a gradual learning process throughout. However, the fall from an average time of 75 minutes for the first 30 cases, to the average operative time of 30 minutes for the remaining 70 cases, is a significant learning process (40% fall in operative time). We thus, believe the learning curve to be 30 operations. Conclusion: We have demonstrated that there is a considerable fall in operative time when comparing the first 30 cases with the remaining 70 cases. This quantitative decrease is indicative of a rapid learning curve. This is further suggested by the remarkable fall in complications during this learning phase

Previous research has shown that tunnel placement is critical in ACL reconstruction. The ultimate position of both the femoral and tibial tunnel determines knee kinematics and overall function of the knee post surgery. As with all techniques there is a definite learning curve for the arthroscopic technique. However, the effect of the learning curve on tunnel placement has been studied sparsely. The purpose of this project therefore is to investigate the effect of the learning curve on tunnel placement. Postoperative radiographs of the first 200 anterior cruciate reconstructions with bone-tendon-bone patella tendon of a single orthopaedic surgeon performed during the first four years of independent practice were analysed for tunnel placement. Radiographs were digitalised and imported into a CAD program. Tunnel placement both femoral and tibial antero-posterior and sagittal was assessed using Sommer's criteria. A rating scale was developed to assess overall placement. A total of 100 points indicated perfect placement. A maximum of 30 points each were allocated for sagittal femoral and tibial placement and a maximum of 20 points each were allocated for coronal placement. Tunnel placement scores improved from 66 for the first 25 procedures to 87 for the last 25 procedures. Sagittal femoral placement (zone 1–4 with zone 1 being the preferred zone of placement) improved from an average of 1.44 to 1.08. Sagittal tibial placement (45% from anterior border of tibia) did not change significantly and remained between 42.82 t0 44.76%. Coronal femoral placement (between 10:00–11:00 o'clock for the right knee and 1:00–2:00 for the left knee) ranged from 10.45–11.15 and 12:45-1:15 o'clock respectively. This finding may be related to the transtibial tibial technique used to place the femoral tunnel. Coronal tibial placement (45% from medial tibial border) ranged from 45-46.58%. Correct placement of the femoral and tibial bone tunnels is important for a successful reconstruction of the anterior cruciate ligament (ACL). This study demonstrated a definitive learning curve and steady improvement of tunnel placement. Whilst there was no significant improvement in sagittal placement, overall placement improved significantly

Introduction. Total knee arthroplasty (TKA) is a well established treatment option for patients with end stage osteoarthritis. Conventional TKA with manual instruments has been shown to be a cost effective and time efficient surgery. While robotic-assisted operative systems have been shown to have benefits in surgical accuracy, they have also been reported to have longer surgical times. The purpose of this work was to determine surgical time and learning curve for a novel robotic-assisted TKA platform. Methods. Eighty-five subjects underwent robotic-assisted TKA by one of three investigators as part of an FDA and IRB approved Investigational Device Exemption (IDE). All patients received a cruciate retaining total knee implant system. Intra-operative safety, Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Knee Society Scores (KSS) were collected pre-operatively and at three month follow-up. In addition, surgical times were collected as part of a TKA work flow. To identify activities related to surgical steps required for robotic procedures specific time stamps were determined from the system. Capture of the hip center to final bone cut was used to define case time and identify robotic learning curve. Descriptive statistics were used to analyze results. Results. Surgeon one completed 24 cases, surgeon two completed 32, and surgeon three completed 29 cases in the study. An average surgical time of 44 minutes with standard deviation of 15.7 minutes was recorded. On average surgeons improved in surgical time with increasing cases as indicated by linear regression results. During initial cases, surgeons repeated intra-operative planning steps which decreased with the learning curve. In addition, the average WOMAC score improvement from pre-operative to three months was 33.1 ± 20.04 (p<0.0001). The average KSS Knee score improvement was 46.12 ± 19.68 (p<0.0001). Subjects recovered their pre-operative range of motion by three months post-operative. Conclusion. With cost related pressures in healthcare, hospitals and surgeons focus on improvements in surgical efficiency to stay competitive. The results of this study indicated comparable operative times to conventional TKA cases as reported in literature with the added benefit of optimizing surgical accuracy. Robotic solutions in TKA may become increasingly efficient as surgeons complete a learning curve

Background. Minimally invasive surgery is being widely used in the field of total hip arthroplasty (THA). The advantages of the direct anterior approach (DAA), which is used in minimally invasive surgery, include low dislocation rate, quick recovery with less pain, and accuracy of prosthesis placement. However, minimally invasive surgery can result in more complications related to the learning curve. The aim of this study was to evaluate the learning curve of DAA-THA performed by a senior resident. Methods. Thirty-three consecutive patients (33 hips) who underwent primary THA were enrolled in this study. All operations were performed by a senior resident using DAA in the supine position without the traction table. The surgeon started using DAA exclusively for all cases of primary THA after being trained in this approach for 6 months. Operative time, intraoperative blood loss, complications, and accuracy of prosthesis placement were investigated. Results. The mean intraoperative blood loss was 524 mL (range, 130–1650 m L). The mean operative time was 60 min (range, 41–80 min). Radiographic analysis showed an average acetabular anteversion angle of 17.0±3.3°, abduction angle of 37.8±4.3°, and stem alignment of 0±0.8°. Thirty-two (97%) of 33 cups were placed within the Lewinnek's safe zone. The overall complication rate was 12% (4 of 33 hips), including 1 proximal femoral fracture (salvaged with circumferential wiring), 1 temporary femoral nerve palsy (completely recovered in 2 weeks), 1 stem subsidence (5 mm), and 1 cup migration. Three of these complications were occurred in the first 10 cases. No revision surgery was required, No postoperative dislocation occurred. Conclusion. We investigated the learning curve of DAA-THA performed by a senior resident. We considered the first 10 cases as the learning curve, but concluded that with adequate training this procedure can be performed safely and effectively without increasing the risk of complications

Rheumatology and Musculoskeletal Sciences, NIHR Biomedical Research Unit, University of Oxford and the Nuffield Orthopaedic Hospital, Oxford. Purpose. The aim of this study was to use motion analysis to objectively study the learning curve of surgical trainees performing arthroscopic meniscal repair on a training model in a skills laboratory. Background. With improving technology and an appreciation of its likely chondroprotective effects, meniscal repair surgery is becoming more common. It remains a difficult procedure and is not routinely learnt during surgical training. Methodology. 19 orthopaedic surgical trainees watched an instructional video of a meniscal repair method (Smith & Nephew Fast-Fix) and then performed 12 meniscal repair episodes on a ‘sawbones’ knee simulator with a standardised lateral meniscal tear. The 12 repair episodes were performed during over a 3 week period. A validated motion analysis system was used to record: distance travelled by each hand; number of hand movements; and time taken to complete the task. Results. Time taken, number of hand movements and total path travelled all showed improvements over the twelve episodes. Time taken improved by 34%, Total path travelled by 21%, and Hand movements improved by 27% for the camera hand (right) and 19% for the instrument hand (left). There was evidence of plateau on the learning curve over the 12 episodes, with larger improvements in measured outcomes over the initial episodes compared to the last episodes. Conclusion. This study objectively demonstrates a learning curve for surgeons performing arthroscopic meniscal repair in a skills laboratory. It indicates the benefits to surgical trainees of practicing such arthroscopic techniques in a skills centre prior to progressing to the operating theatre

With the introduction of new technology in orthopaedics, surgeons must balance anticipated benefits in patient outcomes with challenges or complications associated with surgical learning curve for the technology. The purpose of this study was to determine whether surgeon learning curve with a new multi-radius primary TKA system and instruments designed to improve surgical team ease would impact clinical outcomes, surgical time, and complications. From November 2012 to July 2015, 2369 primary TKAs were prospectively enrolled in two multicentre studies across 50 sites in 14 countries with a new knee system (NEW-TKA) evenly balanced across four configurations: cruciate retaining or posterior stabilised with either fixed bearing or rotating platform (CRFB, CRRP, PSFB, PSRP). 2128 knees had a<1 year visit and 1189 had a minimum 1 year visit. These knees were compared to a reference dataset of 843 primary TKAs from three manufacturers in the same four configurations with currently available products (CA-TKA). Demographics for NEW-TKA and CA-TKA were similar and typical for primary TKA. Operative times, clinical outcomes and a series of five patient reported outcomes were compared for NEW-TKA vs. CA-TKA. The first 10 New-TKA subjects for each surgeon were defined as learning curve cases (N=520) and were compared to all later subjects (N=1849). Patient reported outcome measure and clinical outcome analyses were covariate adjusted for patient demographics, pre-op assessment and days post-op. Mean (SD) surgical time for NEW-TKA learning curve cases was 79.1 (24.3) minutes, which reduced thereafter to 73.6 (24.3) (p=0.002). Beyond 10 cases, there was a continued reduction in NEW-TKA surgical time (R-Squared = 0.031). After 10 cases, surgical time was on par with the mean (SD) 71.9 (21.6) for CA-TKA (p=0.078). PROM outcomes of the first 10 learning curve cases for NEW-TKA were not statistically different from later cases at less than 1 year or later when adjusted for relevant covariates including configuration, patient demographics, pre-op functional status, and time post-op (p-values > 0.01). PROM outcomes for NEW-TKA vs. CA-TKA under the same covariate adjustments showed a trend favoring KOOS ADL, Symptoms, and Sport and Recreation subscores at minimum 1 year (p-values < 0.01). The incidence of intraoperative operative site complications was 1.3% for the NEW-TKA learning curve cases which was similar to the 0.6% rate for historical CA-TKA (p=0.231) and the intraoperative complication rate for the NEW-TKA later cases was consistent with learning curve cases (p=0.158). The introduction of new implants into the market place needs to have adequate data to support that they are safe and effective. Except for a minor increase in surgical time during the first 10 patients, this study found that surgeon learning curve with this new primary TKA system does not adversely affect patient short term outcomes and complication rates

INTRODUCTION. The goal of the study was to perform quality control with a commercially available navigation system when introducing PST technique at our academic department. The learning curve was assessed by the Cumulative Sum (CUSUM) test. We hypothesized that the PST process for TKA was immediately under control after its introduction when analyzed with the CUSUM technique. MATERIAL AND METHODS. The first 50 TKAs implanted with the use of PST at an academic department were scheduled to enter in a prospective, observational study. All TKAs were implanted by an experienced, high volume senior consultant with high experience in knee navigation. PSTs were carefully positioned over the bone and articular surfaces to the best fit position, without any navigated information. Then the 3D femoral and tibia PSTs positioning were recorded. The surgical procedure was then completed following the routine navigated procedure with standard navigated templates. To assess the 3D positioning of each template individually and of both templates together as a surrogate of the final TKA positioning, one point was given for each item inside the target, giving a maximal femur and tibia scores of 4 points, and a maximal knee score of 8 points, when all items were fulfilled. Following dataset was used for CUSUM chart plotting: allowable slack = 0.5SD, acceptable limit score = 6 points for knee score and 2 points for femur and tibia scores. For each measurement Mx, two CUSUMs (upper and lower CUSUMs) were calculated. These sums were plotted against the rank of the observation i. A trend in the process results in a change in the slope of the CUSUM, whereas the values are expected to fluctuate around a horizontal line if the process is in control. The process was considered out of control if upper CUSUM or lower CUSUM is outside the acceptable deviation interval. RESULTS. The knee score was still out of control after the 20th case (fig. 1). Both femur (fig. 2) and tibia (fig. 3) scores were still out of control after the 20th case as well. The decision was taken to interrupt the study after the 20th case as the learning curve appeared unacceptably long in comparison to the routine navigated technique. DISCUSSION. The main result of this study is that introduction of PST in an academic center may involve a significant learning curve: the process remained out of control even after 20 procedures. The present results contradict the common belief that introduction of PSTs is easy and does not require special instruction. These results indicate that surgeons should have only a progressive confidence with the self-sitting of PSTs when introducing this technology. Introducing PSTs might involve a significant loss of accuracy, at least when comparing with a navigation controlled implantation. In conclusion, CUSUM analysis allows monitoring the learning curve when introducing PSTs for TKA in an academic department. There may be a significant learning curve to achieve the steady state of accuracy and obtain an acceptable alignment. The decision was taken to discontinue using PSTs for TKA. For any figures or tables, please contact the authors directly