Learning Curve For Operative Time Research Articles

Gasless laparoscopy in rural India-registry outcomes and evaluation of the learning curve

BackgroundA program of gasless laparoscopy (GL) has been implemented in rural North-East India. To facilitate safe adoption, participating rural surgeons underwent rigorous training prior to independent clinical practice. An online registry was established to capture clinical data on safety and efficacy and to evaluate initial learning curves for gasless laparoscopy.MethodsSurgeons who had completed the GL training program participated in the online RedCap Registry. Patients included in the registry provided informed consent for the use of their data. Data on operative times, conversion rates, perioperative complications, length of stay, and hospital costs were collected. Fixed reference cumulative sum (CUSUM) model was used to evaluate the learning curve based on operative times and conversion rates published in the literature.ResultsFour surgeons from three rural hospitals in North-East India participated in the registry. The data were collected over 12 months, from September 2019 to August 2020. One hundred and twenty-three participants underwent GL procedures, including 109 females (88.6%) and 14 males. GL procedures included cholecystectomy, appendicectomy, tubal ligation, ovarian cystectomy, diagnostic laparoscopy, and adhesiolysis. The mean operative time was 75.3 (42.05) minutes for all the surgeries. Conversion from GL to open surgery occurred in 11.4% of participants, with 8.9% converted to conventional laparoscopy. The main reasons for conversion were the inability to secure an operative view, lack of operating space, and adhesions. The mean length of stay was 3 (2.1) days. The complication rate was 5.7%, with one postoperative death. The CUSUM analysis for GL cholecystectomy showed a longer learning curve for operative time and few conversions. The learning curve for GL tubal ligation was relatively shorter.ConclusionGasless laparoscopy can be safely implemented in the rural settings of Northeast India with appropriate training programs. Careful case selection is essential during the early stages of the surgical learning curve.

Robotic Handpiece-Assisted Total Knee Arthroplasty - Analysis of the Learning Curve for Operative Time and Alignment Accuracy

Robotic Handpiece-Assisted Total Knee Arthroplasty - Analysis of the Learning Curve for Operative Time and Alignment Accuracy

Learning curve of robot-assisted total knee arthroplasty and its effects on implant position in asian patients: a prospective study

BackgroundRobot-assisted total knee arthroplasty (r-TKA) can reportedly achieve more accurate implant positioning than conventional total knee arthroplasty (c-TKA), although its learning curve is controversial. Moreover, few studies have investigated r-TKA in Asians, who have different anatomical characteristics. This study aimed to determine the learning curve for r-TKA and compare implant positions between r-TKA and c-TKA according to the learning curve in Asian patients.MethodsThis prospective study included 50 consecutive c-TKAs (group C), followed by 50 consecutive r-TKAs conducted using the MAKO robotic system (Stryker, USA). Cumulative summation analyses were performed to assess the learning curve for operative time in r-TKA. Accordingly, the r-TKA cases were divided into the initial (group I) and proficiency cases (group P). The femoral and tibial component positions in the coronal, sagittal, and axial planes and lower limb alignment were compared among the three groups.Resultsr-TKA was associated with a learning curve for operative time in 18 cases. The operative time was significantly shorter in groups C and P than that in group I, with no significant difference between groups C and P. Groups I and P demonstrated fewer outliers with respect to lower limb alignment, femoral component coronal position, axial position, and tibial component sagittal position than those in group C, with no significant difference between groups I and P.ConclusionThe operative time did not differ significantly between r-TKA and c-TKA after the learning curve. Surgeons could expect more accurate and reproducible lower limb alignment and implant positioning with r-TKA in Asian patients, irrespective of the learning curve.

INTRODUCTION OF ROSA ROBOTIC ARM SYSTEM FOR TOTAL KNEE ARTHROPLASTY IS ASSOCIATED WITH A MINIMAL LEARNING CURVE FOR OPERATIVE TIME

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.

Challenges and Learning Curves in Adopting TaTME and Robotic Surgery for Rectal Cancer: A Cusum Analysis.

Simple SummaryRectal cancer surgery remains a challenge and information about the learning curve in adopting new techniques is lacking. This paper analyzes our experience in taTME (since 2015) and robotic surgery (since 2018) at a fully accredited referral center for the treatment of rectal cancer in Spain. In this retrospective study, we aim to analyze the learning curves for taTME and robot-assisted rectal procedures in the incorporation of these platforms into our practice. We sought to describe our team’s experience in incorporating these techniques and to analyze the difficulties that we have had. Hoping that sharing our experience can help other groups improve their results during the difficult initial phase of incorporating new techniques.New techniques are being developed to improve the results of laparoscopic surgery for rectal cancer. This paper analyzes the learning curves for transanal total mesorectal excision (taTME) and robot-assisted surgery in our colorectal surgery department. We analyzed retrospectively data from patients undergoing curative and elective surgery for rectal cancer ≤12 cm from the anal verge. We excluded extended surgeries. We used cumulative sum (CUSUM) curve analysis to identify inflection points. Between 2015 and 2021, 588 patients underwent surgery for rectal cancer at our center: 67 taTME and 79 robot-assisted surgeries. To overcome the operative time learning curve, 14 cases were needed for taTME and 53 for robot-assisted surgery. The morbidity rate started to decrease after the 17th case in taTME and after the 49th case in robot-assisted surgery, but it is much less abrupt in robot-assisted group. During the initial learning phase, the rate of anastomotic leakage was higher in taTME (35.7% vs. 5.7%). Two Urological lesions occurred in taTME but not in robot-assisted surgery. The conversion rate was higher in robot-assisted surgery (1.5% vs. 10.1%). Incorporating new techniques is complex and entails a transition period. In our experience, taTME involved a higher rate of serious complications than robot-assisted surgery during initial learning period but required a shorter learning curve.

Determining the component-based operative time learning curve for robotic-assisted radical prostatectomy.

To determine the learning curve (LC) of total operative time and the discrete components of the robotic-assisted radical prostatectomy (RARP) for a recent robotic fellowship-trained urologic surgeon. We performed a retrospective analysis of RARP procedures performed by a single new attending surgeon from August 2015 to April 2019. Patients' demographics and operative details were assessed. Total operative time was divided and prospectively recorded in 7 parts: (a) docking robot, (b) dissecting seminal vesicles (SVs) (c) dissecting endopelvic fascia (EPF), (d) incising bladder neck (BN), (e) completing the dissection, (f) lymph node dissection, and (g) urethrovesical anastomosis (UVA) and robot undocking. Cumulative sum analysis was used to ascertain the LC for total operative time and the 7 parts of the procedure. One hundred twenty consecutive RARPs were performed. The LC was overcome at 25 cases for total operative time, 13 cases for docking the robot, 33 cases for dissecting SVs, 31 cases for dissecting EPF, 46 cases for incising BN, 38 cases for prostate dissection, 25 cases for lymph node dissection, and 52 cases for UVA. Total operative time was decreased 22.8% (p < 0.0001) and time for robot docking, dissecting SVs, dissecting EPF, incising BN, completing prostate dissection, lymph node dissection, and UVA were decreased 16.7%, 30.5%, 29.5%, 36.2%, 37.3%, 32.2%, and 26.9%, respectively (all p < 0.05). We observed a 25-case LC for a fellowship-trained urologist to achieve stable operative performance of RARP surgery. Procedural components demonstrated variable LCs including the UVA that required upward of 52 cases.

Introduction of ROSA robotic-arm system for total knee arthroplasty is associated with a minimal learning curve for operative time

PurposeThe 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.MethodsThis 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 graded and Hip-Knee-Ankle Axis 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 (infection, periprosthetic fracture, thromboembolism, and compromised wound healing) and revisions were reviewed.ResultsThe 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 one revision for instability in the conventional TKA group and none in the RA TKA group. There were no significant difference (p > 0.99) in post-operative complication rates between the conventional TKA and RA TKA groups.ConclusionsThe 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.

Imageless robotic-assisted total knee arthroplasty accurately restores the radiological alignment with a short learning curve: a randomized controlled trial.

The study compared a novel imageless robotic-assisted total knee arthroplasty (RATKA) and conventional TKA by considering (1) radiological outcomes, (2) outliers of radiological outcomes, and (3) learning curve. This prospective randomized controlled study performed by a single surgeon evaluated 152 patients (152 knees): 75 patients undergoing RATKA and 77 patients undergoing conventional TKA. Mechanical alignment, radiological implant positioning, and outliers were analyzed for radiological outcomes. Cumulative summation (CUSUM) analysis was used to assess the learning curve for operative time in RATKA. The RATKA had significantly better accuracy of knee alignment and component positioning than conventional TKA. The hip-knee-ankle axis and implant position outliers were significantly lower in the RATKA, with 94.7% of patients had achieved an overall mechanical alignment within 3° of a neutral mechanical axis. Changes in posterior condylar offset and joint line were significantly lower in the RATKA. A learning curve of seven cases for operative time was obtained for the RATKA. The imageless RATKA has better alignment accuracy with a short learning curve; thus, it presents an attractive option for TKA.

Mitigation of the Robotic Pancreaticoduodenectomy Learning Curve through comprehensive training

BackgroundThere is an associated lag in achieving competency for robotic pancreaticoduodenectomy (PD), resulting in a learning curve. We hypothesize that the reported learning curve can be mitigated through a comprehensive graduated training protocol. MethodsAll patients (n = 237) who underwent an open (n = 197, 83.1%) or robotic (n = 40, 16.9%) PD between 2015-2019 were identified at The Ohio State University. The learning curve for operative time and surgical failure (defined as conversion to open, blood transfusion, or Clavien-Dindo complication grade ≥3) was analyzed using a risk adjusted cumulative summation technique. ResultsAfter 10 cases, operative time plateaued to a mean of 468.3 ± 96.3 minutes for robotic PD versus a mean of 332.5 ± 103.9 minutes for open PD (P < 0.001). There was no further apparent learning curve over time relative to rates of operative time or surgical failure. After propensity score-matching, patients undergoing robotic PD had a similar incidence of major complications, grade B/C postoperative pancreatic fistula, and delayed gastric emptying versus patients undergoing open PD (all P > 0.05). ConclusionCompletion of a comprehensive procedure-specific robotic training protocol for PD mitigated the learning curve for this operative approach by shifting the curve into the training/simulation phase rather than the live operating phase. These data hold important implications for the future training and accreditation of surgeons embarking on robotic PD.

Feasibility and educational value of fluorescence cholangiography in laparoscopic cholecystectomy.

Near-infrared fluorescence cholangiography during a laparoscopic cholecystectomy has become widely accepted as a useful auxiliary tool to visualize the extrahepatic biliary structures. We investigated the feasibility and educational value of a method with longer interval between the administration of indocyanine green and the imaging of these structures. Approximately 18 hours before their surgery, patients (n=51) were intravenously administered 0.25 mg/kg of indocyanine green. Each laparoscopic cholecystectomy was performed under fluorescence imaging in combination with white-light imaging. Operative outcomes including visualization of the extrahepatic biliary structures and operative time were compared between the patients on whom board-certified surgeons operated (feasibility phase; n=18) and the patients on whom a surgery resident operated (educational phase; n=33). There were no adverse events related to the longer interval method. The visualization rates of extrahepatic biliary structures were comparable between the two phases. Both the mean time to divide the cystic duct and the mean time to remove the gallbladder in the educational phase were significantly longer than those in the feasibility phase (68.2 vs 24.4minutes and 30.2 vs 15.8minutes, P < .001 each). There was no significant difference in other operative outcomes. The operative time learning curve did not decrease with a resident's experience. Fluorescence cholangiography with the longer interval method was feasible and could identify the extrahepatic biliary structures irrespective of the surgeon's experience; however, it did not decrease the operative time with experience.

Supraclavicular Approach for Neurogenic Thoracic Outlet Syndrome: Description of a Learning Curve

The supraclavicular exposure represents an alternative approach for thoracic outlet decompression in neurogenic thoracic outlet syndrome with unique access to neurovascular structures. We aimed to evaluate the learning curve for this approach and associated patient outcomes. Patients undergoing first-time, unilateral, supraclavicular thoracic outlet decompression for neurogenic thoracic outlet syndrome were included. Cumulative-sum and linear-spline-regression analyses were used to determine the operative time learning curve. Patients were consecutively organized into early (learning phase) and late (competency) cohorts. Primary endpoints were the operative time learning curve operation number and association of this learning curve on differences in self-reported postoperative symptomatic improvement between early and late cohorts, adjusting for American Society of Anesthesiology classification, body mass index, previous treatment (opioid/neuropathic medication/botulinum-injection), and length of stay. Among 114 patients, learning curve analyses showed decreasing operative times, plateauing at the 51st operation (ß= -1.63, 95% confidence interval [-2.30, -0.95], P < .001). No periprocedural differences existed between early (operations 1-50) and late (operations 51-114) cohorts. Self-reported 90-day outcomes were similar in early and late cohorts (odds ratio [OR]: 1.60 [0.65, 3.95], P= .31). Mediators of poor self-reported outcomes included increasing American Society of Anesthesiology classification (OR 0.21 [0.08, 0.54], P= .001), failed preoperative botulinum injection (OR 0.15 [0.03, 0.65], P= .01), and increased length of stay (OR 0.40 [0.22, 0.73], P= .003). The learning curve for supraclavicular thoracic outlet decompression in neurogenic thoracic outlet syndrome occurred after 51 operations with a trend towards improved 90-day self-reported outcomes from the early to late phases. These findings, along with mediators of poorer outcomes, may aid surgeons in adopting a new approach and counseling patients on expected outcomes.

The Learning Curve by Operative Time for Soft Tissue Balancing in Total Knee Arthroplasty Using Electronic Sensor Technology

BackgroundElectronic sensor devices can provide an objective assessment of soft tissue balancing in total knee arthroplasty (TKA) which may potentially decrease postoperative pain. We aim to quantify the learning curve for operative time (OT) for this technology. MethodsConsecutive TKA cases balanced with an electronic sensor balancing device by one senior surgeon from 2013 to 2017 were included in this study. The OT (in minutes) was analyzed using the cumulative sum analysis to evaluate the learning curve for this technology. Further analysis was done by splitting the 287 patients into 7 cohorts, 41 patients each. ResultsTwo hundred eighty-seven patients balanced with sensor technology were available for analysis. The cumulative sum OT learning curve estimated that this technology’s learning curve was 41 cases. This curve consisted of 2 phases: phase 1 which includes the first 41 cases and phase 2 which includes the remaining 246 patients. The mean OT for the first and last sensor-assisted cohorts was 120.4 and 108.9 minutes (P = .021). The mean OT for the first sensor-assisted cohort and the control cohort was 120.4 versus 109 minutes (P = .023). The mean OT for the last sensor-assisted cohort and the control cohort was 108.9 versus 109 minutes (P = .94). ConclusionOur findings suggest that it takes approximately 41 cases of sensor-assisted TKA cases to achieve OTs identical to manually balanced TKA cases. This is a relatively shallow learning curve for the sensor technology, and allows arthroplasty surgeons to objectively achieve soft tissue balancing without adding OT to the surgery.

The learning curve of robot-assisted laparoscopic pyeloplasty in children: a multi-outcome approach

Few studies have evaluated the learning curve (LC) for robot-assisted laparoscopic pyeloplasty (RALP) for ureteropelvic junction obstruction in children. It was attempted to assess the LC of this procedure using a multi-outcome approach, accounting for patient complexity. Data on the first series of children undergoing RALP between November 2007 and December 2017at the study institution were prospectively collected. Patient complexity factors and peri-operative data including operative time (OT) were retrospectively analyzed. The LC was analyzed using cumulative sum (CUSUM) methodology for OT and a composite parameter (combination of 3 parameters: OT adjusted for patient complexity factors (AOT), complications, and surgical success). Two surgeons without any experience in robotic surgeryperformed 42 consecutive RALP in 41 patients. Median age at surgery was 5 years (6 months-15 years), and mean OT was 200±72.8min. Cumulative sum chart demonstrated biphasic LC for OT and multiphasic LC for composite factor. Based on the CUSUM analysis for composite outcome, the LC for RALP could be divided into three different phases: phase 1, the learning period (1-12 cases); phase 2, the consolidation period (13-22 cases); and phase 3, representing the period of increased competence (23-39cases). Interphase comparison showed a significant reduction in OT, length of stay, and postoperative pain (P=0.0001; P=0.0076; P=0.039, respectively) CONCLUSION: Numerous distinctly shaped LCs depending on the outcome measures and well-defined learning phase transition points were demonstrated. Patient complexity factors were accounted for, which can influence surgical outcomes. Because there is no perfect indicator of proficiency, a multi-outcome approach was adopted to provide a comprehensive view of the learning process for RALP. More than 41 cases are needed to achieve mastery.

Operative Learning Curve After Transition to Endoscopic Transsphenoidal Pituitary Surgery.

No clear consensus yet defines the endpoints for operative learning curves in the transition to minimally invasive endoscopic techniques. This retrospective review of our first 202 patients who underwent endoscopic pituitary resection examines the statistical learning curve related to operative times-a measure of our surgical team's efficiency and complication rate, a reflection of surgical skill and maturity. Retrospective chart review included patient demographic data, tumor type, operative time, complications, and follow-up. During the 5-year study period, surgeries were performed by an otolaryngology-neurosurgery team. Statistical analysis by Pearson's correlation delineated a learning curve for operative time and complications. Our learning curve showed comparable plateaus: 120 cases (48% males, 52% females) for operative time (mean, 134 minutes; range, 62-307 minutes) and 100 cases for incidence of cerebrospinal fluid (CSF) leak. The risk of CSF leak declined significantly with the surgeon's increasing experience. Complication rates were as follows: temporary nasal obstruction, 9.9%; CSF leak, 8.4%; postoperative epistaxis, 7%; sinusitis, 4.5%; septal osteomyelitis, 2.4%; postoperative sellar hematoma, 1.5%; anosmia, 0.5%; and septal perforation, 0.5%. The overall CSF leak rate included 5.5% intraoperative and 2.9% postoperative; most cases resolved with a lumbar drain. Four patients (2%) underwent postoperative surgical repair and lumbar drainage. Our learning curve-defined endpoints for 2 measures, operative time and complication rates, support improved outcomes for reduced CSF leaks, the most common complication, with increasing operative experience. We will continue to examine the implications related to safety, efficacy, and the need for subspecialization in this minimally invasive surgery.

Serial improvement of quality metrics in pediatric thoracoscopic lobectomy for congenital lung malformation: an analysis of learning curve.

Video-assisted thoracic surgery (VATS) pulmonary resection in children is a technically demanding procedure that requires a relatively long learning period. This study aimed to evaluate the serial improvement of quality metrics according to case volume experience in pediatric VATS pulmonary resection of congenital lung malformation (CLM). Methods VATS anatomical resection in CLM was attempted in 200 consecutive patients. The learning curve for the operative time was modeled by cumulative sum analysis. Quality metrics were used to measure technical achievement and efficiency outcomes. Results The median operative time was 95min. The median length of hospital stay and chest tube indwelling time was 4 and 2 days, respectively. The improvement of operation time was observed persistently until 200 cases. However, two cut-off points, the 50th case and 110th case, were identified in the learning curve for operative time, and the 110th case was the turning point for stable outcomes with short operation time. Significant reduction of length of hospital stay and chest tube indwelling time was observed after 50 cases (p = .002 and p = .021, respectively). The complication rate decreased but continued at a low rate for entire study period and the interval decrease was not statistically significant. Conversion rate decreased significantly (p = .001), and technically challenging procedures were performed more frequently in later cases. Conclusions Improvements of quality metrics in operation time, conversion rate, length of hospital stay, and chest tube indwelling time were observed in proportion to case volume. Minimum experience of 50 is necessary for stable outcomes of pediatric VATS pulmonary resection.

Learning curves for strabismus surgery in two ophthalmologists

PurposeTo identify the average turning point by comparing the learning curves of two surgeons learningto perform strabismus surgery.MethodsPatients who underwent procedures to correctexotropia between January 2010 and December 2014 followed for at least 3 months were retrospectivelyassessed. The first 70 patients on whom each of two ophthalmologists (A and B) performed surgery to treatstrabismus were divided into 7 cohorts comprising 10 patients each based on the chronological order ofthe surgery. Factors, including patient age, preoperative angle of deviation, operative time, and success orfailure of the operation, were compared between the two surgeons. Learning curves were calculated basedon changes in operative time and operation success rate. Operation success was determined by measuringthe angle of deviation at a distance of 5 m 3 months after the operation.ResultsA turning point wasobserved after 40 cases for Surgeon A and 50 cases for Surgeon B based on the operative time learning curve. No turning point was observed in the operation success rate learning curve based on the absence of a specifictrend. Success rate by cohort was not significantly different between the two surgeons (p &gt; 0.05). Surgeon B had a significantly longer mean operative time than Surgeon A (p = 0.045).ConclusionsApproximately 50 cases are required for an ophthalmologist to reach a turning point in strabismus surgery. This outcomecan be used as a guideline when training surgeons to perform strabismus surgery.

Laparoscopic radical prostatectomy outcome data: how should surgeon's performance be reported? A retrospective learning curve analysis of two surgeons.

ObjectiveTo document the learning curve for the laparoscopic radical prostatectomy (LRP) procedure and discuss the optimal usage of prospectively documented outcome data for reporting a surgeon’s performance.Materials and methodsUsing prospectively collected data from the first series of patients to undergo LRP by two surgeons in the same institution, linear and logistic regression multivariate analyses per 25 patients were carried out to graphically represent the surgical learning curve for operative time, blood loss, complications, length of stay (LOS), and positive margins. Surgeon A carried out 275 operations between 2003–2009; Surgeon B carried out 225 between 2008–2012.ResultsLearning curves showing continuous improvement of each of the above outcomes were demonstrated for both cohorts. For surgeon A, a plateau was observed for LOS and T2 positive margins after 100 and 150 surgeries respectively. No such plateau was observed for surgeon B.ConclusionOn documenting these learning curves and discussion of the reporting methods used, we concluded that the most informative outcome measure, with the least potential observer bias was T2 positive margins. Whether as a single measure or in combination with others, this has potential for use as an objective outcome representative of improvement in a surgeon’s skill over time.

Learning curve assessment in 102 laparoscopic distal pancreatectomies: single surgeon series

Introduction: Laparoscopic distal pancreatectomy (LDP) has become standard treatment for left-sided pancreatic disease in expert centers. However, large (>30 cases) single surgeon series assessing the surgical learning curve are lacking. Methods: Data of patients undergoing LDP between June 2007 and April 2015 were prospectively collected. LDPs were performed by a single surgeon (MAH). Patients were divided into three equal groups of consecutive LDPs. Results: In total, 102 LDPs were performed (age 61 years (IQR = 44.5–70.0), 63% (n = 64) female). Two LDPs (2%) were converted. Operative time was 205 min. (SD = 75), blood loss 200 mL (IQR = 50–300). Groups were comparable for baseline, operative time and blood loss. The use of LDPs including the pancreatic body (group 1 = 29%, 2 = 47%, 3 = 47%; p = 0.04) and multivisceral resections (group 1=6%, 2 = 15%, 3 = 21%; p = 0.21) increased with time. The Clavien–Dindo ≥3 complication rate decreased (24%, 6% and 3% for group 1, 2 and 3; p = 0.02), whereas the ISGPF grade B/C fistula rate showed a non-significant increase (35%, 59% and 53%; p = 0.13), because more patients were discharged with a drain in situ in groups 2 and 3. Due to this change in drain management, a reduction in percutaneous drainage was achieved (21%, 6% and 1%; p = 0.03). Hospital stay decreased (9, 6 and 4 days for group 1, 2 and 3; p < 0.001). Conclusion: No learning curve for operative time was found, possibly due to more difficult procedures performed with growing experience. Nevertheless, a steady improve in postoperative outcomes was observed throughout the whole series.

Establishing the Learning Curve of Robotic Sacral Colpopexy in a Start-up Robotics Program

Study ObjectiveTo determine the learning curve of the following segments of a robotic sacral colpopexy: preoperative setup, operative time, postoperative transition, and room turnover. DesignA retrospective cohort study to determine the number of cases needed to reach points of efficiency in the various segments of a robotic sacral colpopexy (Canadian Task Force II-2). SettingA university-affiliated community hospital. PatientsWomen who underwent robotic sacral colpopexy at our institution from 2009 to 2013 comprise the study population. InterventionsPatient characteristics and operative reports were extracted from a patient database that has been maintained since the inception of the robotics program at Winthrop University Hospital and electronic medical records. Based on additional procedures performed, 4 groups of patients were created (A–D). Measurements and Main ResultsLearning curves for each of the segment times of interest were created using penalized basis spline (B-spline) regression. Operative time was further analyzed using an inverse curve and sequential grouping. A total of 176 patients were eligible. Nonparametric tests detected no difference in procedure times between the 4 groups (A–D) of patients. The preoperative and postoperative points of efficiency were 108 and 118 cases, respectively. The operative points of proficiency and efficiency were 25 and 36 cases, respectively. Operative time was further analyzed using an inverse curve that revealed that after 11 cases the surgeon had reached 90% of the learning plateau. Sequential grouping revealed no significant improvement in operative time after 60 cases. Turnover time could not be assessed because of incomplete data. ConclusionsThere is a difference in the operative time learning curve for robotic sacral colpopexy depending on the statistical analysis used. The learning curve of the operative segment showed an improvement in operative time between 25 and 36 cases when using B-spline regression. When the data for operative time was fit to an inverse curve, a learning rate of 11 cases was appreciated. Using sequential grouping to describe the data, no improvement in operative time was seen after 60 cases. Ultimately, we believe that efficiency in operative time is attained after 30 to 60 cases when performing robotic sacral colpopexy. The learning curve for preoperative setup and postoperative transition, which is reflective of anesthesia and nursing staff, was approximately 110 cases.

Learning curves for strabismus surgery in two ophthalmologists

Purpose:To identify the average turning point by comparing the learning curves of two surgeons learning to perform strabismus surgery.Materials and Methods:Patients who underwent procedures to correct exotropia between January 2010 and December 2014 followed for at least 3 months were retrospectively assessed. The first 70 patients on whom each of two ophthalmologists (A and B) performed surgery to treat strabismus were divided into 7 cohorts comprising 10 patients each based on the chronological order of the surgery. Factors, including patient age, preoperative angle of deviation, operative time, and success or failure of the operation, were compared between the two surgeons. Learning curves were calculated based on changes in operative time and operation success rate. Operation success was determined by measuring the angle of deviation at a distance of 5 m 3 months after the operation.Results:A turning point was observed after 40 cases for Surgeon A and 50 cases for Surgeon B based on the operative time learning curve. No turning point was observed in the operation success rate learning curve based on the absence of a specific trend. Success rate by cohort was not significantly different between the two surgeons (P > 0.05). Surgeon B had a significantly longer mean operative time than Surgeon A (P = 0.045).Conclusions:Approximately 50 cases are required for an ophthalmologist to reach a turning point in strabismus surgery. This outcome can be used as a guideline when training surgeons to perform strabismus surgery.