Assessment Of Learning Curve Research Articles

Robot-assisted radical cystectomy with intracorporeal neobladder: impact of learning curve and long-term assessment of functional outcomes

There is paucity of data about functional outcomes of Robot-assisted Radical Cystectomy (RARC) with intracorporeal orthotopic neobladder (ICON), and the impact of learning curve (LC) on those outcomes remains to be addressed. The aim of this study was to report long-term functional outcomes of our single center series of RARC with ICON, assessing the role of LC in their achievement. Patients treated with Robot assisted radical cystectomy with intracorporeal orthotopic neobladder in our center between January 2012 and August 2019 were retrospectively analyzed. Preoperative, clinical, perioperative, pathologic and functional data were reported. The first cases were divided in tertiles, for assessing the impact of learning curve on the outcomes evaluated. Long-term functional outcomes of the whole cohort were evaluated. Overall, 167 patients were included. Concerning tertiles analysis, operative time (P<0.001), incidence of low (P=0.002) and high grade (P=0.001) complications and hospital stay (P=0.04) decreased significantly over time. Day-time continence recovery probability was significantly lower in the initial case series (1-yr rate 68.4%, 87% and 89.8 for I, II and III tertile, respectively; P=0.04;). Accordingly, Trifecta achievement was significantly higher in II and III tertiles (P=0.01). At a median follow- up of 34 months, the incidence of significant renal function deterioration of the whole cohort was 16.7%. Overall, 12, 24 and 60-mo day-time continence rates were 74.8%, 82.7% and 82.7%. Patients treated at the beginning of the learning curve show worse perioperative and functional results. Once standardized the procedure, complications rates, hospital stay, and day-time continence recovery experienced a significant improvement. At a long-term analysis of functional outcomes of our patients, renal function preservation and continence recovery results are encouraging.

Systematic review of the endoscopic enucleation of the prostate learning curve

It has been shown that endoscopic enucleation of the prostate (EEP) allows for similar efficacy and safety, no matter what energy and type of instruments we use, but the length of learning may differ greatly. The aim of this systematic review is to verify if there is any significant difference between EEP methods in learning. We performed a systematic literature search in three databases and included only the articles containing their own data on the EEP learning curve assessment during the last 10years. The primary endpoint was to determine the necessary experience needed to achieve a plateau. The secondary endpoints were to review methods used to evaluate a learning curve. The final sample included 17 articles, containing a total of 4615 EEPs performed by 76 surgeons, the most common method was HoLEP (9/17). The majority of articles studying HoLEP report a learning curve of experience level achievement in roughly 30-40 (min 20; max 60) cases. The studies of GreenLight laser showed high heterogeneity in the results with minimum of 20 cases and maximum of 150-200 cases. TUEB required roughly 40-50 cases to reach the plateau. Although EEP is considered challenging, it shows a steep learning curve with a plateau after 30-50 cases. Proper criteria are critical for accurate assessment of the learning curve. The Trifecta and Pentafecta criteria are currently the most appropriate method to evaluate EEP learning.

Functional Results and Learning Curve of Endoscopic Stapes Surgery: A 10-Year Experience.

To assess hearing outcomes and complications of endoscopic stapes surgery by a single surgeon in a 10-year period, to compare these data with conventional microscopic procedures by the same operator, and to describe the learning curve of endoscopic stapedotomy. Retrospective study. This is a retrospective study on patients who underwent endoscopic stapes surgery performed by the same senior surgeon, experienced both in microscopic and endoscopic techniques, between January 2009 and December 2018. Audiological data were compared, and intraoperative and postoperative complications were collected. The surgeon's last 30 cases of microscopic stapedotomy were enrolled as the control group. The results of the first 100 endoscopic stapes surgeries were analyzed separately to create a cumulative sum (CUSUM) control chart for learning curve assessment. One hundred seventy-eight endoscopic and 30 microscopic stapes surgeries were included. In the endoscopic group, the mean postoperative air-bone gap was 8.2 dB. No significant differences between the endoscopic and microscopic preoperative and postoperative values were reported. A total of eight complications (4.5%) were observed in the endoscopic cohort, although in the control group, no complication occurred. The mean surgical time was 51.9 minutes in the endoscopic group versus 48.2 minutes in the microscopic group (P > .05). No association between stapedotomy success and the increasing number of procedures was found. Our article demonstrates that functional results from endoscopic stapes surgery are similar to those from microscopic stapes surgery in terms of both safety and efficacy. After gaining endoscopic experience, the surgical duration of stapes surgery will be adequate starting from the first cases. 4 Laryngoscope, 131:885-891, 2021.

Assessment of Quality Outcomes and Learning Curve for Robot-Assisted Minimally Invasive McKeown Esophagectomy.

This study aimed to identify the results of the quality assessment and the learning curve of robot-assisted minimally invasive McKeown esophagectomy (RAMIE-MK). The study retrospectively reviewed the data of 400 consecutive patients with esophageal cancer who underwent RAMIE-MK by a single surgeon from November 2015 to March 2019. Cumulative summation analysis of the learning curve was performed. The patients were divided into decile cohorts of 40 cases to minimize demographic deviations and to maximize the power of detecting statistically significant changes in performance. The 90-day mortality rate for all the patients was 0.5% (2 cases). The authors' experience was divided into the ascending phase (40 cases), the plateau phase (175 cases), and the descending phase (185 cases). After 40 cases, significant improvements in operative time (328 vs. 251min; P = 0.019), estimated blood loss (350 vs. 200ml; P = 0.031), and conversion rates (12.5% vs. 2.5%; P < 0.001) were observed. After 80 cases, a decrease in the rates of anastomotic leakage (22.5% vs. 8.1%; P = 0.001) and vocal cord palsy (31.3% vs. 18.4%; P = 0.024) was observed. The number of harvested lymph nodes increased after 40 cases (13 vs. 23; P < 0.001), especially for lymph nodes along the recurrent laryngeal nerve (3.0 vs. 6.0; P < 0.001). The learning phase of RAMIE-MK consists of 40 cases, and quality outcomes can be improved after 80 procedures. Several turning points related to the optimization of surgical outcomes can be used as benchmarks for surgeons performing RAMIE-MK.

Erratum to: Two-Stage Indicators to Assess Learning Curves for Minimally Invasive Ivor Lewis Esophagectomy.

Erratum to: Two-Stage Indicators to Assess Learning Curves for Minimally Invasive Ivor Lewis Esophagectomy.

Operative time in adolescent idiopathic scoliosis surgery: a need for a standard definition.

Our objective is to report and define 'operative time' in adolescent idiopathic scoliosis (AIS) posterior spinal fusion surgeries. Documenting key times during surgery are important to compare operative risks, assess learning curves, and evaluate team efficiency in AIS surgery. 'Operative time' in literature has not been standardized. Systematic review was performed by two reviewers. Keywords included operative time, duration of surgery, and scoliosis. One thousand nine hundred six studies were identified, 1092 duplicates were removed and 670 abstracts were excluded. Of the 144 articles, 67 met inclusion and exclusion criteria. Studies were evaluated for number of patients, operative time, and definition of operative time. Meta-analysis was not performed due to confounders. Of the 67 studies (6678 patients), only 14 (1565 patients) defined operative time, and all specified as incision to closure. From these 14 studies, the median operative time was 248 minutes (range 174-448 minutes). In the 53 studies (5113 patients) without a definition, one study reported time in a non-comparable format, therefore, data were analyzed for 52 studies (5078 patients) with a median operative time of 252 minutes (wider range 139-523 minutes). A clear standardized definition of operative or surgical time in spine surgery does not exist. We believe that operative time should be clearly described for each published study for accurate documentation and be defined from incision time to spine dressing completion time in order to standardize study results. Level of evidence: IV.

Real-time assessment of learning curve for robot-assisted laparoscopic prostatectomy.

The learning curves analysed to date for robot-assisted laparoscopic prostatectomy are based on arbitrary cut-offs of the total cases. We analysed a large dataset of robot-assisted laparoscopic prostatectomies from a single centre between 2008 and 2019 for assessment of the learning curve for perioperative outcomes with respect to time and individual cases. A total of 1,406 patients were evaluated, with mean operative time 198.08 minutes and mean console time 161.05 minutes. A plot of operative time and console time showed an initial decline followed by a near-constant phase. The inflection points were detected at 1,398 days (308th case) for operative time and 1,470 days (324th case) for console time, with a declining trend of 8.83 minutes and 7.07 minutes, respectively, per quarter-year (p<0.001). Mean estimated blood loss showed a 70.04% reduction between the start (214.76ml) and end (64.35ml) (p<0.001). The complication rate did not vary with respect to time (p=0.188) or the number of procedures (p=0.354). There was insufficient evidence to claim that the number of operations (p=0.326), D'Amico classification (p=0.114 for intermediate versus low; p=0.158 for high versus low) or time (p=0.114) was associated with the odds of positive surgical margins. It takes about 300 cases and nearly 4 years to standardise operative and console times, with a requirement of around 80 cases per annum for a single surgical team in the initial years to optimise the outcomes of robot-assisted laparoscopic prostatectomy.

Learning curve assessment for total ankle replacement using the transfibular approach

BackgroundTotal ankle arthroplasty is an increasingly effective option for the treatment of end-stage arthritis. One recent innovation utilizes a transfibular, lateral approach. Like any new system, there is likely a learning curve associated with its use. We analyzed a series of patients who received a total ankle arthroplasty via a transfibular approach to state if it is possible to identify and to evaluate effects of a learning curve in the use of this novel total ankle replacement system. Methods76 consecutive patients meeting inclusion and exclusion criteria were retrospectively analyzed. All patients had a minimum of 24 months of follow-up. Intraoperative parameters, preoperative and postoperative subjective outcome scores, radiographic parameters, and complications were recorded and evaluated. ResultsThere were significant learning curve effects on various surgical and postoperative parameters. Surgical time decreased with the curve stabilizing after the 16th patient. With regard to patient outcomes, a learning curve was identified for the VAS, AOFAS, and SF-12 MCS scores. The number of patients required to stabilize these curves were 21, 13, and 16, respectively. Alignment as measured by alpha and gamma angles also improved with experience, with the curves stabilizing at 18 and 15 patients, respectively. There was a larger number cases required for complication rates, with the curve stabilizing after the 39th patient. No significant learning curve was found for ankle ROM, SF-12 PCS, beta angle, tibio-talar ratio (TTR), or tibio-talar surface angle (TTS). ConclusionsThis study demonstrates a significant learning curve with respect to operative time, patient outcomes, and radiographic parameters. Extrapolating this information, we urge surgeons to adequately familiarize themselves with any new implant through a training program in a high-volume center. Level of evidenceIV, case series.

Systematic review of learning curves in robot-assisted surgery.

BackgroundIncreased uptake of robotic surgery has led to interest in learning curves for robot‐assisted procedures. Learning curves, however, are often poorly defined. This systematic review was conducted to identify the available evidence investigating surgeon learning curves in robot‐assisted surgery.MethodsMEDLINE, Embase and the Cochrane Library were searched in February 2018, in accordance with PRISMA guidelines, alongside hand searches of key congresses and existing reviews. Eligible articles were those assessing learning curves associated with robot‐assisted surgery in patients.ResultsSearches identified 2316 records, of which 68 met the eligibility criteria, reporting on 68 unique studies. Of these, 49 assessed learning curves based on patient data across ten surgical specialties. All 49 were observational, largely single‐arm (35 of 49, 71 per cent) and included few surgeons. Learning curves exhibited substantial heterogeneity, varying between procedures, studies and metrics. Standards of reporting were generally poor, with only 17 of 49 (35 per cent) quantifying previous experience. Methods used to assess the learning curve were heterogeneous, often lacking statistical validation and using ambiguous terminology.ConclusionLearning curve estimates were subject to considerable uncertainty. Robust evidence was lacking, owing to limitations in study design, frequent reporting gaps and substantial heterogeneity in the methods used to assess learning curves. The opportunity remains for the establishment of optimal quantitative methods for the assessment of learning curves, to inform surgical training programmes and improve patient outcomes.

Consensus Statement on Robotic Mastectomy-Expert Panel From International Endoscopic and Robotic Breast Surgery Symposium (IERBS) 2019.

To achieve a consensus statement on robotic mastectomy. Robotic-assisted surgery has gained much attention especially the results of few case series reporting on the technical feasibility, safety and early oncologic outcomes of robotic-assisted mastectomy in a few centers worldwide. The aim of this consensus statement was to develop and provide standardized guidelines on robotic mastectomy based on consensus statement by a panel of experts from indications to outcome measures and indicators, thereby providing a valuable guide for breast surgeons worldwide. An internationally representative expert panel of 10 surgeons was invited to participate in the generation of a consensus statement. 52 statements were created in 6 domains: indications, contraindications, technical considerations, patient counseling, outcome measures and indicators, training and learning curve assessment. Experts were asked to vote if they agree, disagree or of the opinion that the statement should be rephrased. Two electronic rounds via online survey of iterative rating and feedback were anonymously completed, followed by a final round of in-person meeting during the inaugural International Endoscopic and Robotic Breast Surgery Symposium 2019 from May 24 to 25, 2019. Consensus was reached when there was at least 80% agreement on each statement. A total of 53 statements with at least 80% agreement were generated after 3 rounds of voting; 21 statements from first round of voting, 20 statements from second round of voting and 12 statements from the final round of in-person meeting. All experts agreed that the consensus statement served as expert recommendations but not mandatory for a successful and safe practice of robotic mastectomy. Robotic mastectomy is a promising technique and could well be the future of minimally invasive breast surgery whereas proving to be safe and feasible. The first consensus statement on robotic mastectomy from an international panel of experts serves as an extremely important milestone and provides recommendations for breast surgeons keen to embark on this technique.

Assessment of Learning Curve in Phacoemulsification Surgery Among the Eastern Province Ophthalmology Program Residents.

PurposeTo assess residents’ performance of phacoemulsification surgery and determine which steps of the procedure are most difficult to learn, and to measure rate of intraoperative complications.DesignThis was a prospective observational study.MethodsPhacoemulsification surgery was divided into steps and each step was given a proficiency grade by the attending consultant. All intraoperative complications were recorded and analyzed.Results200 cases performed by the Eastern Province ophthalmology program residents were evaluated. The most commonly encountered difficulty factors were hard nucleus (20.7%), small pupil (12.6%), and white cataract (10.3%). Capsulorhexis, nucleus disassembly and removal, and cortex removal were the most difficult steps to learn. General complication rate was 17.5%, and posterior capsular rupture was the most common complication (40%). Proficiency more than 90% of the time in each step was noted in residents with prior experience of more than 40 cases, except for nucleus disassembly.ConclusionThe study showed that nucleus disassembly remained the major obstacle in the residents’ exponential learning curve of phacoemulsification surgery. Majority of complications occurred at level of capsulorhexis and cortical removal steps.

Robotic-Assisted Roux-en-Y Gastric Bypass: Learning Curve Assessment Using Cumulative Sum and Literature Review.

Purpose: Robotic-assisted Roux-en-Y gastric bypass (RARYGB) is a procedure that is used with increasing frequency in the United States. Among other bariatric procedures, RARYGB is a good model for the robotic platform because it allows hand-sewn suturing and energy devices application. The aim of this study was to conduct a literature review of robotic approach in RARYGB, its learning curve using the cumulative sum (CUSUM) method, and our experience as Center of Excellence recognized by the American Society for Metabolic and Bariatric Surgery (ASMBS). Methods: A total of 67 patients were included. Results revealed that the learning curve was achieved after case 11. Eighteen studies were included in the pooled analysis. Results: An increase in the operative time was noted at case 46, in which a second phase was identified. A significant difference between these two phases was found only related to previous bariatric surgery. The outcomes of this series were comparable with the ones available in the literature. Conclusions: The robotic platform is increasing its role in complex procedures such as RARYGB. The hand-sewn technique may offer important advantages in terms of shorter learning curve, reduced conversion rate, and lower leakage rate.

Patient-specific high-tibial osteotomy's 'cutting-guides' decrease operating time and the number of fluoroscopic images taken after a Brief Learning Curve.

Patient-specific cutting guides (PSCGs) have been advocated to improve the accuracy of deformity correction in opening-wedge high-tibial osteotomies (HTO). It was hypothesized that PSCGs for HTO would have a short learning curve. Therefore, the goals of this study were to determine the surgeons learning curve for PSCGs used for opening-wedge HTO assessing: the operating time, surgeons comfort levels, number of fluoroscopic images, accuracy of post-operative limb alignment and functional outcomes. This prospective cohort study included 71 consecutive opening-wedge HTO with PSCGs performed by three different surgeons with different experiences. The operating time, the surgeon's anxiety levels evaluated using the Spielberger State-Trait Anxiety Inventory (STAI), the number of fluoroscopic images was systematically and prospectively collected. The accuracy of the postoperative alignment was defined by the difference between the preoperative targeted correction and the final post-operative correction both measured on standardized CT-scans using the same protocol (ΔHKA, ΔMPTA, ΔPPTA). Functional outcomes were evaluated at 1 year using the different sub-scores of the KOOS. Cumulative summation (CUSUM) analyses were used to assess learning curves. The use of PSCGs in HTO surgery was associated with a learning curve of 10 cases to optimize operative time (mean operative time 26.3min ± 8.8), 8 cases to lessen surgeon anxiety levels, and 9 cases to decrease the number of fluoroscopic images to an average of 4.3 ± 1.2. Cumulative PSCGs experience did not affect accuracy of post-operative limb alignment with a mean: ΔHKA = 1.0° ± 1.0°, ΔMPTA = 0.5° ± 0.6° and ΔPPTA = 0.4° ± 0.8°. No significant difference was observed between the three surgeons for these three parameters. There was no statistical correlation between the number of procedures performed and the patient's functional outcomes. The use of PSCGs requires a short learning curve to optimize operating time, reduce the use of fluoroscopy and lessen surgeon's anxiety levels. Additionally, this learning phase does not affect the accuracy of the postoperative correction and the functional results at 1year. II: prospective observational study.

PSU36 SYSTEMATIC REVIEW OF SURGEON LEARNING CURVES IN ROBOT-ASSISTED SURGERY

To assess and summarize the impact surgeon learning curve effects could have on surgical metrics, clinical outcomes, and cost-benefit decisions in robot-assisted surgery across all surgical procedures. A systematic literature search of MEDLINE, MEDLINE In-Process, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and NHS Economic Evaluation Database were searched from 2012 to February 5, 2018. There were 2,316 total publications identified with potentially relevant information. From the systematic search, 68 studies were included in this review (49 in surgical setting; 19 in simulator/training setting). Of the 49 surgical studies, 80% were retrospective, 73% were single-arm, and all were observational in design. The number of surgeons per study was small; 67% of studies included fewer than five. The most frequent specialties were urology (n=20), general surgery (n=13), and gynecology (n=7). Time-based variables were the most commonly reported to assess learning curves (86% of studies), and the most reported individual metric was operative time (67% of studies). Other measures, including length of hospital stay, morbidity/mortality rates, and specialty-specific metrics, were less commonly reported. Of the major surgical, safety, and recovery metrics captured within this review, operative time (67%), complication rate (18%), and length of stay (10%) were reported most frequently, respectively. When evaluating the evidence base, the variability in results between studies and surgeons makes it challenging to synthesize a reliable estimate for length and burden of the learning curve for any one procedure. The literature lacks studies with high-quality designs assessing surgeon learning curves in robot-assisted surgery. In addition, the methods used to assess learning curves are poorly described and frequently inadequate. Opportunities remain to establish quantitative, evidence-based approaches to measuring and defining learning curves in robotic surgery, as well as estimating the clinical and economic burdens associated with surgeon learning.

Quantitative Assessment of the Learning Curve for Robotic Thyroid Surgery.

With the increased utilization of robot thyroidectomy in recent years, surgical proficiency is the paramount consideration. However, there is no single perfect or ideal method for measuring surgical proficiency. In this study, we evaluated the learning curve of robotic thyroidectomy using various parameters. A total of 172 robotic total thyroidectomies were performed by a single surgeon between March 2014 and February 2018. Cumulative summation analysis revealed that it took 50 cases for the surgeon to significantly improve the operation time. Mean operation time was significantly shorter in the group that included the 51st to the 172nd case, than in the group that included only the first 50 cases (132.8 ± 27.7 min vs. 166.9 ± 29.5 min; p < 0.001). On the other hand, the surgeon was competent after the 75th case when postoperative transient hypoparathyroidism was used as the outcome measure. The incidence of hypoparathyroidism gradually decreased from 52.0%, for the first 75 cases, to 40.2% after the 76th case. These results indicated that the criteria used to assess proficiency greatly influenced the interpretation of the learning curve. Incorporation of the operation time, complications, and oncologic outcomes should be considered in learning curve assessment.

Evaluation of the learning curve for laparoscopic liver resection by risk-adjusted CUSUM analysis using the Iwate difficulty index

Background: Laparoscopic liver resection (LLR) is technically challenging and requires training in both hepatobiliary and advanced laparoscopic techniques. The aim of this study was to compare the learning curve of LLR using CUSUM (cumulative sum control chart) analysis before and after risk adjusting for operative difficulty using the Iwate difficulty index. Methods: Retrospective analysis of a prospective database of consecutive patients who underwent LLR by two surgeons at a single centre between January 2011 and June 2016. The learning curve for LLR for both surgeons was evaluated using CUSUM analysis before and after risk-adjusting for operative difficulty using the Iwate difficulty index. Results: 125 consecutive patients underwent LLR during the study period, including non-anatomical resection (57), left lateral sectionectomy (42) and major hepatectomy (26). Conversion to open surgery was necessary in 14 patients (11%). The first major resection was jointly performed by surgeon A and B after 38 minor resections (surgeon A – 15; surgeon B – 23). Unadjusted CUSUM analysis of operating time identified a learning curve of 50-60 procedures. After risk-adjusting for operative difficulty, the shape of the CUSUM plot changed and the learning curve reduced to 25-30 procedures. Conclusion: Risk-adjustment using the Iwate difficulty index may enhance the applicability of CUSUM analysis in the assessment of learning curve of laparoscopic liver resection, and warrants further study.

Learning Curve for Laparoscopic Hysterectomy: An Experience from Kathmandu University Hospital

Aims: The aim of this study is to assess learning curves for laparoscopic hysterectomies, compare the performance of surgeons and review demographic parameters of the patients, varieties of complications experienced and indications of the procedures.&#x0D; Methods: A retrospective study was conducted in Kathmandu University Hospital, Kavre of January 1, 2011 to June 30, 2018.&#x0D; Results: A total of 1849 cases were already performed by mid 2018. Of them, 261 (14.12%) cases were LAVH and TLH cases. Mean duration for laparoscopic hysterectomies (for both LAVH and TLH) was 142.21±43.46 minutes (range 55 to 310 minutes) and one third of the cases performed in a range of 121 to 150 minutes. There is difference in mean duration of operation between surgeons which is statistically significant (p &lt;0.001). Beside one of four surgeons (surgeon B) had significant reduction in mean duration for LAVH surgery (p=0.004). Same surgeon has significant reduction in mean duration for performing TLH (p=0.0047). Of the 261 laparoscopic hysterectomies, 8 cases (3.07%) turned into laparotomy.&#x0D; Conclusions: Laparoscopic hysterectomies are feasible with reducing mean operating time across the period. These minimal invasive surgeries are safe with low rate of complications and less conversion to open even in our set up.

Validation of a virtual reality laparoscopic appendicectomy simulator: a novel process using cognitive task analysis.

Virtual reality (VR) simulation is a vital component of surgical training with demonstrated improvements in surgical quality and clinical outcome. To validate the LAP Mentor (Simbionix™) laparoscopic appendicectomy (LA) VR simulator with inclusion of a novel tool, Cognitive Task Analysis (CTA). Thirty-two novices and nine experienced surgeons performed two simulated LAs. An expert-consensus questionnaire guided face validity assessment. Content validity was assessed using CTA-derived questions encompassing eight operative steps and four decision points. Construct validity was evaluated using dexterity metrics, masked assessment of surgical quality using the OSATS global rating scale, and mental workload from two validated tools: the NASA-TLX and SMEQ. Ten novices performed eight further LAs for learning curve assessment. Face validity was demonstrated across all domains. Considering content validity, the essential technical and non-technical steps were evident. The experienced group performed the procedure quicker (median time 361 vs. 538s, P= 0.0039) with fewer total movements (426 vs. 641, P< 0.0001) and shorter idle time (131 vs. 199s, P= 0.0006). This correlated with higher OSATS scores (median 33.5 vs. 22.2, P< 0.0001) and lower mental demand (NASA-TLX: 9.0 vs. 13.75, P= 0.012; SMEQ: 60 vs. 80, P= 0.0025), indicating construct validity. Learning curve data showed statistically significant improvements after the 7th session for procedure time, total movements and idle time, which correlated with reduction in mental demand. The LAP Mentor demonstrates face, content and construct validity for LA; thus, it can be used as an effective tool in surgical training. Task repetition leads to achievement of expert benchmarks.

Robotic-arm assisted total knee arthroplasty has a learning curve of seven cases for integration into the surgical workflow but no learning curve effect for accuracy of implant positioning

PurposeThe primary objective of this study was to determine the surgical team’s learning curve for robotic-arm assisted TKA through assessments of operative times, surgical team comfort levels, accuracy of implant positioning, limb alignment, and postoperative complications. Secondary objectives were to compare accuracy of implant positioning and limb alignment in conventional jig-based TKA versus robotic-arm assisted TKA.MethodsThis prospective cohort study included 60 consecutive conventional jig-based TKAs followed by 60 consecutive robotic-arm assisted TKAs performed by a single surgeon. Independent observers recorded surrogate markers of the learning curve including operative times, stress levels amongst the surgical team using the state-trait anxiety inventory (STAI) questionnaire, accuracy of implant positioning, limb alignment, and complications within 30 days of surgery. Cumulative summation (CUSUM) analyses were used to assess learning curves for operative time and STAI scores in robotic TKA.ResultsRobotic-arm assisted TKA was associated with a learning curve of seven cases for operative times (p = 0.01) and surgical team anxiety levels (p = 0.02). Cumulative robotic experience did not affect accuracy of implant positioning (n.s.) limb alignment (n.s.) posterior condylar offset ratio (n.s.) posterior tibial slope (n.s.) and joint line restoration (n.s.). Robotic TKA improved accuracy of implant positioning (p < 0.001) and limb alignment (p < 0.001) with no additional risk of postoperative complications compared to conventional manual TKA.ConclusionImplementation of robotic-arm assisted TKA led to increased operative times and heightened levels of anxiety amongst the surgical team for the initial seven cases but there was no learning curve for achieving the planned implant positioning. Robotic-arm assisted TKA improved accuracy of implant positioning and limb alignment compared to conventional jig-based TKA. The findings of this study will enable clinicians and healthcare professionals to better understand the impact of implementing robotic TKA on the surgical workflow, assist the safe integration of this procedure into surgical practice, and facilitate theatre planning and scheduling of operative cases during the learning phase.Level of evidenceII.

How well is each learner learning? Validity investigation of a learning curve-based assessment approach for ECG interpretation.

Learning curves can support a competency-based approach to assessment for learning. When interpreting repeated assessment data displayed as learning curves, a key assessment question is: "How well is each learner learning?" We outline the validity argument and investigation relevant to this question, for a computer-based repeated assessment of competence in electrocardiogram (ECG) interpretation. We developed an on-line ECG learning program based on 292 anonymized ECGs collected from an electronic patient database. After diagnosing each ECG, participants received feedback includingthe computer interpretation, cardiologist's annotation, and correct diagnosis.In 2015, participants from a single institution, across a range of ECG skill levels,diagnosed at least 60 ECGs. We planned, collected and evaluated validity evidence under each inference of Kane's validity framework. For Scoring, three cardiologists' kappa for agreement on correct diagnosis was 0.92. There was a range of ECG difficulty across and within each diagnostic category. For Generalization, appropriate sampling was reflected in the inclusion of a typical clinical base rate of 39% normal ECGs. Applying generalizability theory presented unique challenges. Under the Extrapolation inference, group learning curves demonstrated expert-novice differences, performance increased with practice and the incremental phase of the learning curve reflected ongoing, effortful learning. A minority of learners had atypical learning curves. We did not collect Implications evidence. Our results support a preliminary validity argument for a learning curve assessment approach for repeated ECG interpretation with deliberate and mixed practice. This approach holds promise for providing educators and researchers, in collaboration with their learners, with deeper insights into how well each learner is learning.