Risk-adjusted Cumulative Sum Analysis Research Articles

Evaluation of the learning curve and complications in unilateral biportal endoscopic transforaminal lumbar interbody fusion: cumulative sum analysis and risk-adjusted cumulative sum analysis

PurposeTo evaluate the learning curve and complications in unilateral biportal endoscopic transforaminal lumbar interbody fusion (ULIF) using the Cumulative Sum (CUSUM) analysis and Risk-adjusted Cumulative Sum (RA-CUSUM) analysis.MethodsThis study retrospectively analyzed 184 consecutive patients who received ULIF in our hospital, including 104 males and 80 females. CUSUM analysis and RA-CUSUM analysis were used to evaluate the learning curve of ULIF based on the operation time and surgical failure rate, respectively. All postoperative complications were defined as surgical failure. Variables of different phases were compared based on the learning curve.ResultsThe CUSUM analysis showed the cutoff point for ULIF was 29 cases, and the RA-CUSUM analysis showed the cutoff point for ULIF was 41 cases. Operating time and hospital stay were significantly decreased as the learning curve progressed (P < 0.05). Visual analogue score (VAS) and Oswestry disability index (ODI) at the last follow-up were significantly lower than preoperatively. At the last follow-up, a total of 171 patients reached intervertebral fusion, with a fusion rate of 92.9% (171/184). A total of eleven complications were observed, and RA-CUSUM analysis showed that the incidence of complications in the early phase was 17.07% and in the late phase was 2.6%, with a significant difference (P < 0.05).ConclusionULIF is an effective minimally invasive lumbar fusion surgical technique. But a learning curve of at least 29 cases will be required to master ULIF, while 41 cases will be required to achieve a stable surgical success rate.

A risk-adjusted cumulative sum analysis of the progression from a novice to an expert surgeon at a single institution

Background/objectiveLaparoscopic surgery for rectal cancer is challenging for novice surgeons because it requires a sharp dissection in a narrow pelvis with visual limitations. Therefore, this study aimed to analyze the learning curve and clinical outcomes of laparoscopic surgery for rectal cancer performed by a novice surgeon en route to becoming an expert. MethodsIn total, 119 patients who underwent laparoscopic surgery for rectal cancer performed by a single surgeon between June 2010 and December 2019 were analyzed. A single hybrid model based on the operative time, open conversion, complications, and resection margin involvement was generated to assess the success of laparoscopic surgery. Furthermore, the learning curve was evaluated using the risk-adjusted cumulative sum (RA-CUSUM) method. ResultsThe learning period was categorized into three phases according to the RA-CUSUM method (phase 1, 1st–33rd cases; phase 2, 34th–84th cases; and phase 3, 85th–119th cases). Tumor size (p = 0.004), distal resection margin (p = 0.003), and the number of harvested lymph nodes (p < 0.001) significantly increased with the learning period. The time to tolerable soft diet became shorter according to the learning period (p = 0.017). Advanced T stage (p = 0.024) and adjuvant chemotherapy (p = 0.012) were more common in phase 3. ConclusionsThis study suggested that the initial technical competence of laparoscopic surgery for rectal cancer was acquired in the 33rd case. Technical mastery was achieved in the 84th case. After mastering the technique, the surgeon tended to challenge more advanced cases, however, the complication rates did not increase.

Introducing a novice surgeon to an experienced robotic gynaecological oncology team: An observational cohort study on the impact of a structured curriculum on outcomes of cervical cancer surgery

ObjectiveTo evaluate the effect on patient outcomes when introducing a novice robotic surgeon, trained in accordance with a structured learning curriculum, to an experienced robotic surgery team treating cervical cancer patients. MethodsPatients with early-stage cervical cancer who were treated with primary robot-assisted surgery between 2007 and 2019 were retrospectively included. In addition to the 165 patients included in a former analysis, we included a further 61 consecutively treated patients and divided all 226 patients over three groups: early learning phase of 61 procedures without structured training (group 1), experienced phase of 104 procedures (group 2), and the 61 procedures during introduction of a novice with structured training (group 3). Risk-adjusted cumulative sum (RA-CUSUM) analysis was performed to assess the learning curve effect. Patient outcomes between the groups were compared. ResultsBased on RA-CUSUM analysis, no learning curve effect was observed for group 3. Regarding surgical outcomes, mean operation time in group 3 was significantly shorter than group 1 (p < 0.001) and similar to group 2 (p = 0.96). Proportions of intraoperative and postoperative adverse events in group 3 were not significantly different from the experienced group (group 2). Regarding oncological outcomes, the 5-year disease-free survival, disease-specific survival, and overall survival in group 3 were not significantly different from the experienced group. ConclusionsIntroducing a novice robotic surgeon, who was trained in accordance with a structured learning curriculum, resulted in similar patient outcomes as by experienced surgeons suggesting novices can progress through a learning phase without compromising outcomes of cervical cancer patients.

Learning curves of robotic extended totally extraperitoneal (eTEP) hernia repair among two surgeons at a high-volume community hospital: a cumulative sum analysis.

Robotic extended totally extraperitoneal hernia (eTEP) repair is a novel technique for minimally invasive ventral hernia repair with retromuscular placement of mesh. This study aimed to evaluate the learning curve for robotic eTEP hernia repair using risk-adjusted cumulative sum (RA-CUSUM) analysis for two general surgeons-one with dedicated fellowship training in robotic eTEP technique (surgeon 2) and another without robotic eTEP-specific training (surgeon 1). We conducted a retrospective analysis of 98 patients undergoing robotic eTEP hernia repair from July 2020 to February 2022 for two surgeons. RA-CUSUM method was applied to the overall operative time (OT) in minutes, adjusting for transversus abdominis release (TAR). Figures 3 (surgeon 1) and 4 (surgeon 2) illustrate the three phases in the RA-CUSUM graphs of OT. For surgeon 1, the cases for each phase were determined: phase 1 (1 to 12), phase 2 (13 to 24), and phase 3 (25 to 51). For surgeon 2, the three phases were similarly determined as 1 to 8, 9 to 32, and 33 to 47, respectively. A significant (p = 0.017) difference existed for the OTs between phases 1 (262 ± 69) and 3 (192 ± 63.0) for surgeon 1. OT compared to the risk-adjusted value stabilized after case 12 and decreased after case 24 for surgeon 1; it began to decrease after case 8 for surgeon 2. The initial learning curve for surgeon 1 reached its plateau after 12 cases, shorter than comparable studies. This was likely due to the surgeon's intentional focus on learning this technique through courses, proctoring, and active mentorship. The flat learning curve seen in surgeon 2's series illustrates the value of experience gained during fellowship training. Our data support that, given the right resources and support, a short learning curve for eTEP is attainable for community surgeons without prior training in the technique.

Uniportal video-assisted anatomical segmentectomy: an analysis of the learning curve

BackgroundThis study aimed to demonstrate the learning curve of anatomical segmentectomy performed by uniportal video-assisted thoracoscopic surgery (U-VATS).MethodWe conducted a retrospective study of U-VATS segmentectomies performed by the same surgeon between September 2019 and August 2022. The learning curve was demonstrated using risk-adjusted cumulative sum (RA-CUSUM) analysis in terms of perioperative complications, which reflected surgical quality and technique proficiency. The surgical outcomes were also compared between different phases.ResultThe complication-based learning curve of U-VATS segmentectomy could be divided into two phases based on RA-CUSUM analysis: phase I, the initial learning phase (cases 1–50) and phase II, the proficiency phase (cases 51–141). Significantly higher complication rates (24.0 vs. 8.8%, p=0.013), longer surgical times (119.8±31.9 vs. 106.2±23.8 min, p=0.005), and more blood loss (20 [IQR, 20–30] vs. 20 [IQR, 10–20] ml, p=0.003) were observed in phase I than in phase II.ConclusionThe learning curve of U-VATS segmentectomy consists of two phases, and at least 50 cases were required to gain technique proficiency and achieve high-quality surgical outcomes.

Risk-Adjusted Assessment of the Learning Curve for Pure Laparoscopic Donor Hepatectomy for Adult Recipients.

Studies on pure laparoscopic donor hepatectomy (PLDH) have been reported. However, only few studies have reported on the learning curve of PLDH. In this report, we aimed to determine the learning curve of PLDH in adult patients using cumulative sum (CUSUM) and risk-adjusted CUSUM (RA-CUSUM) analyses. The data of donors who underwent PLDH at a single center between December 2012 and May 2022 were retrospectively reviewed. The learning curve was evaluated using the CUSUM and RA-CUSUM methods based on surgery duration. Forty-eight patients were finally included in the present study. The mean operation time was 393.6 ± 80.3min. PLDH was converted to laparotomy in three cases (6.3%). According to the Clavien-Dindo classification, nine cases (18.8%) had higher-than-grade III postoperative complications and the most frequent complications were biliary complications. The CUSUM graph shows two peaks, at the 13th and 27th case. The multivariate analysis revealed that a body mass index ≥ 23kg/m2 and intraoperative cholangiography were the only factors that were independently associated with longer operation time. Based on these results, an RA-CUSUM analysis was performed to assess the learning curve, which showed a decrease in the learning curve after 33 to 34 PLDH procedures. A learning curve effect was demonstrated in this study after 33 to 34 PLDH procedures. There are relatively many biliary complications, and it is necessary to further examine the method of bile duct transection.

Learning curve and factors influencing successful robot-assisted bilateral sentinel lymph node mapping in early-stage cervical cancer: an observational cohort study

ABSTRACT Objectives To evaluate whether a learning curve affects the bilateral sentinel lymph node (SLN) detection in early-stage cervical cancer. Methods All patients with FIGO (2018) stage IA1-IB2 or IIA1 cervical cancer who had undergone robot-assisted SLN mapping performed with a combination of preoperative technetium-99m nanocolloids (including preoperative imaging) and intraoperative blue dye were retrospectively included. Risk-adjusted cumulative sum (RA-CUSUM) analysis was used to determine if a learning curve based on bilateral SLN detection existed in this cohort. Results A total of 227 cervical cancer patients were included. In 98.2% of patients (223/227) at least one SLN was detected. The bilateral SLN detection rate was 87.2% (198/227). Except for age (OR 1.06 per year, 95%CI 1.02–1.09), no significant risk factors for non-bilateral SLN detection were found (e.g., prior conization, BMI or FIGO stage). The RA-CUSUM analysis showed no clear learning phase during the first procedures and cumulative bilateral detection rate remained at least 80% during the entire inclusion period. Conclusions In this single-institution experience, we observed no learning curve affecting robot-assisted SLN mapping using a radiotracer and blue dye in early-stage cervical cancer patients, with stable bilateral detection rates of at least 80% when adhering to a standardized methodology.

The Learning Curve for Hand-Assisted Laparoscopic Total Gastrectomy in Gastric Cancer Patients.

(1) Background: Hand-assisted laparoscopic total gastrectomy (LTG) for patients with gastric cancer (GC) has been established as the standard surgical treatment at our center. This study aims to quantify the learning curve for surgeons performing minimally invasive total gastrectomy at a high-volume single center. (2) Methods: One hundred and eighteen consecutive patients who underwent minimally invasive total gastrectomy between January 2014 and December 2020 at a single high-volume center were included and reviewed retrospectively. Risk-adjusted cumulative sum analysis (RA-CUSUM) was used to monitor the surgical outcomes for patients with different risks of postoperative mortality using varying-coefficient logistic regression models. Patients were ordered by the sequential number of the procedure performed and divided into two groups according to the degree of surgeon proficiency as determined by RA-CUSUM analysis (group A: 45; group B: 73 patients). Age, gender, body mass index (BMI), tumor location, pathology, and comorbidities were compared while primary endpoints comprised surgical parameters, postoperative course, and survival outcomes. (3) Results: Forty-four cases were required for the completion of the learning curve. During this time, the mean operating time decreased. Hand-assisted laparoscopic total gastrectomy performed after a learning curve was associated with a shorter median operating time (OT) (360 min vs. 289 min, &lt;0.001), and a reduced length of stay (A = 18.0 vs. B = 14.0 days) (p = 0.154), while there was a trend toward less major complications (Clavien-Dindo (CD) 3-5 within 90 days (12 (26.67%) vs. 10 (13.70%) p = 0.079). Our results showed no difference in anastomotic leakage between the two groups (group A vs. group B, 3 (6.67%) vs. 4 (5.48%) p = 0.99). Similarly, 30-day (0 (0%) vs. 1 (1.7%), p = 0.365) and 90-day mortality (1 (2.08%) vs. 2 (3.39%), p = 0.684) were comparable. Following multivariate analysis, the level of surgical proficiency was not a significant prognostic factor for overall survival. (4) Conclusions: A minimum of 44 cases are required for experienced laparoscopic surgeons to achieve technical competence for performing LTG. While operation time decreased after completion of the learning curve, quality criteria such as achievement of R0 resection, anastomotic leakage, and perioperative mortality remained unaltered. Of note, the level of surgical training showed no significant impact on the 2 year OS or DFS.

The taTME learning curve for mid-low rectal cancer: a single-center experience in China

PurposeAs transanal total mesorectal excision (taTME) is performed worldwide, the optimization of existing training and guidance programs to enhance new taTME learners’ competence in performing this procedure is warranted. This study aimed to evaluate the taTME learning curve in patients with mid-low rectal cancer.MethodsPatients who underwent taTME for mid-low rectal cancer between October 2015 and August 2021 at a single center were included. A cumulative sum (CUSUM) learning curve analysis was performed with the total operation time as the study outcome. The learning curve was analyzed using risk-adjusted CUSUM analysis, with postoperative complications and anastomotic leakage (AL) as outcomes.ResultsIn total, 104 consecutive patients were included in this study. The CUSUM learning curve for total operative time started declining after 42 cases (309.1 ± 84.4 vs. 220.2 ± 46.4, P < 0.001). The risk-adjusted CUSUM (RA-CUSUM) learning curve for postoperative complications fluctuated in cases 44–75 and declined significantly after case 75. The RA-CUSUM learning curve for AL declined after 68 cases.ConclusionstaTME had learning curves of 42, 75, and 68 cases for total operative time, postoperative complications, and AL, respectively. A surgeon may require 42 and 75 cases to achieve “proficiency” and “mastery” in taTME procedures, respectively.

Learning Curve and Complications of Unilateral Biportal Endoscopy: Cumulative Sum and Risk-Adjusted Cumulative Sum Analysis.

ObjectiveThe purpose of this study was to investigate the learning curve and complications of unilateral biportal endoscopy (UBE) in the treatment of lumbar disc herniation (LDH) and lumbar spinal stenosis (LSS). MethodsThis was a retrospective cohort analysis of 197 consecutive patients who received UBE unilateral laminotomy bilateral decompression (UBE-ULBD) or lumbar discectomy (UBE-LD) surgery, including 107 males and 90 females with an average age of 64.83±14.29 years. Cumulative sum (CUSUM) and risk-adjusted cumulative sum analysis (RA-CUSUM) were used to evaluate the learning curve, with the occurrence of complications defined as surgical failure, and variables of different phase of the learning curve were compared. ResultsThe cutoff point of learning curve of UBE surgery was 54 cases according to CUSUM analysis. The learning curve of UBE-ULBD and UBE-LD were divided into 3 phases. The first cutoff points were 31 and 12 cases, and the second cutoff point were 67 and 32 cases respectively. With the progress of the learning curve, the operation time and postoperative hospital stays decreased. The visual analogue scale and Oswestry Disability Index at the last follow-up were significantly lower than that before surgery. The incidence of surgical failure was 6.11% and began to decrease after the 89th case based on RA-CUSUM analysis. The surgical failure rate decreased from 10.11% to 2.78 after the 89th case with significant different. ConclusionUBE surgery is effective in the treatment of LDH and LSS with low incidence of complications. But a learning curve of at least 54 cases still required for mastering UBE surgery.

Extensive open lobectomy experience is not a prerequisite for learning uniportal video-assisted thoracic surgery lobectomy.

Uniportal video-assisted thoracoscopic surgery (U-VATS) lobectomy has been increasingly adopted to manage early stage lung cancer. However, little information is available on whether this technique can be taught to surgeons inexperienced in open lobectomy. This study aimed to investigate the learning curve for U-VATS lobectomy performed by a single surgeon with limited open lobectomy experience. From July 2018 to September 2020, 103 patients received U-VATS lobectomy for lung cancer by a single surgeon. The learning curve was assessed using three statistical methods: the moving average analysis, cumulative sum (CUSUM) analysis, and risk-adjusted CUSUM (RA-CUSUM) analysis. The moving average analysis showed a continuous decrease in operative time throughout the study period. The CUSUM analysis demonstrated three well-differentiated learning phases: Phase 1 (the initial 34 cases) representing the initial learning, Phase 2 (the middle 33 cases) representing the improvement of competence, and Phase 3 (the final 36 cases) representing technical proficiency. RA-CUSUM analysis revealed that the maximized cumulative surgical failure, defined as the maximum cumulative difference between the observed and predicted surgical failures, was found in the 61st case. U-VATS lobectomy is feasible for surgeons with limited open lobectomy experience. Multidimensional statistical analyses suggested that 61-67 cases were required to gain technical proficiency and ensure acceptable surgical outcomes.

Robot-assisted minimally invasive esophagectomy (RAMIE) with side-to-side semi-mechanical anastomosis: analysis of a learning curve

Minimally invasive esophagectomy (MIE) reduces mortality and morbidity related to esophageal surgery, but a long learning curve is necessary due to the technical difficulties of thoracoscopy (35 to 119 patients required as reported in literature). Robot-assisted minimally invasive esophagectomy (RAMIE) with side-to-side semi-mechanical (SM) anastomosis may shorten completion of the learning curve. We present the results of the first 40 RAMIEs performed by a single surgeon with experience in esophageal and minimally invasive surgery. Patients included in this study underwent RAMIE between April 1, 2018 and April 30, 2021. According to the risk-adjusted cumulative sum analysis for postoperative complications, the first 19 patients were compared to the last 21. Pulmonary complications and atrial fibrillation occurred in 2.5% and 5% of cases, respectively. A single case of anastomotic leak in the early group was registered. Thirty-day mortality was 2.5%. R0 resection was obtained in all cases. No anastomotic strictures occurred during the follow-up (median of 20months). A significant difference between the early group and the late one was observed for median operative time (425 vs 393min, p = 0.001), estimated intraoperative blood loss (100 vs 50ml, p = 0.003), Intensive Care Unit stay (days2 vs 1, p = 0.004), hospital stay (days13 vs 10, p = 0.007) and number oflymph nodes harvested (17 vs 21, p = 0.020). In conclusion, this study showed RAMIE to be safe and effective even in the early phase of its application. The learning curve resulted shorter than in MIE, with 19 patients needed to gain proficiency in our series.

Impact of an emergency endovascular aneurysm repair protocol on 30-day ruptured abdominal aortic aneurysm mortality

ObjectiveTo characterize the longstanding impact of an emergency endovascular aneurysm repair (EVAR) protocol for ruptured abdominal aortic aneurysm (rAAA) on 30-day mortality. MethodsAll adult patients with an rAAA who underwent a surgical or endovascular intervention at a tertiary care center between March 2001 and December 2018 were evaluated. An emergency EVAR protocol was introduced in January 2004. The primary outcome was 30-day mortality, which was calculated using risk-adjusted logistic regression for the preprotocol and postprotocol periods. A risk-adjusted cumulative sum analysis examined changes in 30-day mortality after protocol implementation. ResultsWe identified 376 patients with rAAA between 2001 and 2018 (75 preprotocol and 301 postprotocol), with a decreasing incidence of rAAA during the study period. The introduction of the protocol in 2004 was associated with increased EVAR use (63.6% vs 6.7%; P < .001). Patients managed according to the protocol were more frequently unstable (systolic blood pressure [SBP] of ≤80 mm Hg, 46.5% postprotocol vs 22.7% preprotocol; P < 0.001), with a lower average SBP (87.4 mm Hg postprotocol vs 106 mm Hg preprotocol; P < .001) and worse renal function (estimated glomerular filtration rate 61.5 mL/min postprotocol vs 83.2 mL/min preprotocol; P < .001). The risk-adjusted 30-day mortality was 23.2% with the emergency EVAR protocol, versus 35.8% preprotocol (P = .0727). A subgroup analysis demonstrated improved the 30-day mortality for unstable patients (SBP of ≤80 mm Hg) at 38.0% (vs 62.4% preprotocol introduction; P = .0190). A cumulative sum analysis demonstrated worse than expected mortality outcomes in the preprotocol period, and stability of surgical performance over 15 years after protocol introduction. ConclusionsOn reflection of a 17-year experience with EVAR for rAAA, the implementation of an emergency EVAR protocol demonstrated stable surgical performance for all patients with an rAAA and evidence of improved 30-day mortality for unstable patients with an rAAA. Since the protocol introduction, EVAR has become a mainstay intervention and, despite an increase in comorbid patients, the overall incidence of rAAA is declining. EVAR should be considered the first-line intervention for the appropriate patient unstable with an rAAA.

Learning Curve of Ex Vivo Liver Resection and Autotransplantation in Treating End-Stage Hepatic Alveolar Echinococcosis: A RA-CUSUM Analysis.

Background: This retrospective study aimed to evaluate the safety and learning curve of ex vivo liver resection and autotransplantation (ELRA).Methods: A total of 102 consecutive end-stage HAE patients who underwent ELRA between 2014 and 2020 in West China Hospital were enrolled. The primary endpoint was major postoperative complications (comprehensive complication index, CCI > 26). The ELRA learning curve was evaluated using risk-adjusted cumulative sum (RA-CUSUM) methods. The learning phases were determined based on RA-CUSUM analysis and tested for their association with intra- and post-operative endpoints.Results: The median surgery time was 738 (659–818) min, with a median blood loss of 2,250 (1,600–3,000) ml. The overall incidence of major morbidity was 38.24% (39/102). Risk-adjusted cumulative sum analysis demonstrated a learning curve of 53 ELRAs for major postoperative complications. The learning phase showed a significant association with the hemodynamic unstable time (HR −30.29, 95% CI −43.32, −17.25, P < 0.0001), reimplantation time (HR −13.92, 95% CI −23.17, −4.67, P = 0.004), total postoperative stay (HR −6.87, 95% CI −11.33, −2.41, P = 0.0033), and postoperative major morbidity (HR 0.25, 95% CI 0.09, 0.68, p = 0.007) when adjusted for age, disease course, liver function, and remote metastasis.Discussion: Ex vivo liver resection and autotransplantation is feasible and safe with a learning curve of 53 cases for major postoperative complications.

Bowel resection performed by gynecologists - Outcomes and learning curves. Activity profile in a Gynecology Department: 7-year observational cohort

ObjectiveBowel resection is frequently used when performing oncological surgery to obtain complete cytoreduction or to remove endometriosis in case of intestinal invasion. Acquiring the surgical skills to perform this kind of procedure is crucial to offer to our patients an optimal management. The aim of this study is to describe a 7-years surgical experience in bowel resections of a gynecologic surgeon and to determine his learning curves. Study DesignThis is a monocentric retrospective cohort study reporting digestive resection performed between January 2013 and April 2020 in the Gynecology Department of Strasbourg University Hospital. Ninety-one consecutive patients were assigned in two groups: gynecological cancer (n = 44) and deep infiltrating endometriosis (DIE) (n = 47). The main outcome measure was the postoperative complications rate at 30 days, based on the modified Clavien-Dindo severity system. Learning curves were evaluated using cumulative sum (CUSUM) analysis of operative time and risk-adjusted cumulative sum (RA-CUSUM) analysis of severe perioperative complications. Identification of predictive factors for operation duration and severe perioperative complication occurrence was conducted using multivariate analysis. ResultsMinor complications were found in 25% of cases. Major complication rate (Clavien-Dindo ≥ IIIa) was 14% in total and only involved patients operated for cancer. The CUSUM curve for operative time peaked at the 35th case and showed a downward slope after the 45th case. Significant predictive factors of operating time were cytoreductive tumoral surgery, size of the bowel resection and laparoscopic surgery, while learning phase 3 significantly decreased it. The RA-CUSUM curve for severe perioperative complications (Clavien-Dindo ≥ IIIa) showed a progressive decrease in the complication rate as the number of interventions increases without showing clear inflection points. Only cardiopulmonary pathologies were found as significant predictive factor of severe complications. ConclusionProficiency in performing highly complex surgery was achieved after approximately 45 cases, cancer and DIE all together. Acceptable rates of severe perioperative complications were observed even during the initial learning period and are comparable with those found in the literature concerning bowel resection performed by gynecologic oncologists but also by general and digestive surgeons.

Learning curve of graft bench operation in living donor liver transplantation: A cumulative sum analysis

The middle hepatic vein reconstruction is a critical issue for successful living donor liver transplantation. In the live donor liver transplantation, using an extended graft donor, preventing congestion by bench surgery becomes more important. Focusing on the bench surgery, which is important in liver transplant surgery, we analyzed the learning curve and described the factors affecting the learning curve, and the postoperative outcomes. Data from donors undergoing bench surgery between January 2019 to May 2020 retrospectively reviewed. To overcome operator-dependent bias, data from procedures performed by only a single surgeon (Jeong-Moo Lee) were included. The learning curve was evaluated using the cumulative sum (CUSUM) method based on the duration of surgery. A total of 58 bench surgery were evaluated. The mean operative time was 64.0 ± 20.8 minutes, and all grafts were successfully transplanted. The CUSUM analysis demonstrated a learning curve of approximately 41 cases of bench surgery. Double portal vein orifices were seen to be risk factors for longer surgery time. Having adjusted for case-mix with these factors, the risk-adjusted CUSUM analysis demonstrated a learning curve of 39-41 cases of bench surgery. At least 41 cases of learning curve are required for successful bench surgery in living donor liver transplantation. Multiple portal vein office is related with longer operative time and learning curve for the bench operation.

Learning curve for robot-assisted Ivor Lewis esophagectomy.

This study aimed to demonstrate the learning curve of robot-assisted minimally invasive esophagectomy (RAMIE). A retrospective analysis of the first 124 consecutive patients who underwent RAMIE with intrathoracic anastomosis (Ivor Lewis) by a single surgeon between May 2015 and August 2020 was performed. An risk-adjusted cumulative sum (RA-CUSUM) analysis was applied to generate a learning curve of RAMIE considering the major complication rate, which reflected the technical proficiency. The overall 30-day morbidity rate was 38.7%, while the major complication rate was 25.8%. The learning curve was divided into two phases based on the RA-CUSUM analysis: phase I, the initial learning phase (cases 1-51) and phase II, the proficiency phase (cases 52-124). As we compared the proficiency phase with the initial learning phase, significantly decreased trends were observed in relation to the major complication rate (37.3% vs. 18.7%, P = 0.017), total operation time (330.9 ± 55.6 vs. 267.3 ± 39.1minutes, P < 0.001), and length of hospitalization (10 [IQR, 9-14] days vs. 9 [IQR, 8-11] days, P = 0.034). In conclusion, the learning curve of RAMIE consisted of two phases, and at least 51 cases were required to gain technical proficiency.

Does the learning curve in robotic rectal cancer surgery impact circumferential resection margin involvement and reoperation rates? A risk-adjusted cumulative sum analysis.

The aim of this study was to evaluate the impact of surgeons' learning curve in robotic surgery for rectal cancer on circumferential resection margin (CRM) involvement and reoperation rates. Learning curve data were prospectively collected from four centers. Patients undergoing robotic proctectomy for resectable rectal cancer were included. CRM was involved when ≥1 mm. TME quality was classified as complete, nearly complete, or incomplete. T-test and χ2 tests were used to compare continuous and categorical variables, respectively. Risk-adjusted cumulative sum (RA-CUSUM) analysis was utilized to evaluate the effect of the learning curve on primary endpoints. Univariate analysis of potential risk factors for CRM involvement and reoperation was performed. Factors with the P value ≤0.2 were included in the multivariate logistic regression model for further RA-CUSUM analysis. A total of 221 patients (80, 36, 62, and 43 patients operated on by surgeons 1, 2, 3, and 4, respectively) who underwent robotic surgery for rectal cancer during the surgeons' learning curves were included. CRM involvement rate was 0%, 11%, 3%, and 5% in surgeons 1, 2, 3, and 4, respectively. Reoperation rate was 3.7%, 8.3%, 4.8%, and 11.6%, respectively. RA-CUSUM analysis of CRM involvement (R2=0.9886) and reoperation (R2=0.9891) found a statistically significant decreasing trend in aggregate CUSUM values throughout the learning curve. This study found a continued significant decrease in CRM involvement and reoperation rates throughout the learning curve in robotic rectal cancer surgery.

Does the learning curve in robotic rectal cancer surgery impact circumferential resection margin involvement and reoperation rates? A risk-adjusted cumulative sum analysis

Background The aim of this study was to evaluate the impact of surgeons' learning curve in robotic surgery for rectal cancer on circumferential resection margin (CRM) involvement and reoperation rates. Methods Learning curve data were prospectively collected from four centers. Patients undergoing robotic proctectomy for resectable rectal cancer were included. CRM was involved when ≥1 mm. TME quality was classified as complete, nearly complete, or incomplete. T-test and Chi-square tests were used to compare continuous and categorical variables, respectively. Risk-adjusted cumulative sum (RA-CUSUM) analysis was utilized to evaluate the effect of the learning curve on primary endpoints. Univariate analysis of potential risk factors for CRM involvement and reoperation was performed. Factors with the p-value ≤0.2 were included in the multivariate logistic regression model for further RA-CUSUM analysis. Results A total of 221 patients (80, 36, 62, and 43 patients operated on by surgeons 1, 2, 3, and 4, respectively) who underwent robotic surgery for rectal cancer during the surgeons' learning curves were included. CRM involvement rate was 0%, 11%, 3%, and 5% in surgeons 1, 2, 3, and 4, respectively. Reoperation rate was 3.7%, 8.3%, 4.8%, and 11.6%, respectively. RA-CUSUM analysis of CRM involvement (R2=0.9886) and reoperation (R2=0.9891) found a statistically significant decreasing trend in aggregate CUSUM values throughout the learning curve. Conclusions This study found a continued significant decrease in CRM involvement and reoperation rates throughout the learning curve in robotic rectal cancer surgery.

Can better surgical outcomes be obtained in the learning process of robotic rectal cancer surgery? A propensity score-matched comparison between learning phases.

Although studies of robotic rectal cancer surgery have demonstrated the effects of learning on operation time, comparisons have failed to demonstrate differences in clinicopathological outcomes between unadjusted learning phases. This study aimed to investigate the learning curve of robotic rectal cancer surgery for clinicopathological outcomes and compare surgical outcomes between adjusted learning phases. Study design We enrolled 506 consecutive patients with rectal adenocarcinoma who underwent robotic resection by a single surgeon between 2007 and 2018. Risk-adjusted cumulative sum (RA-CUSUM) for surgical failure was used to analyze the learning curve. Surgical failure was defined as the occurrence of any of the following: conversion to open surgery, severe complications (Clavien-Dindo grade ≥ 3a), insufficient number of harvested lymph nodes (LNs), or R1 resection. Comparisons between learning phases analyzed by RA-CUSUM were performed before and after propensity score matching. In RA-CUSUM analysis, the learning curve was divided into two learning phases: phase 1 (1st-177th cases, n = 177) and phase 2 (178th-506th cases, n = 329). Before matching, patients in phase 2 had deeper tumor invasion and higher rates of positive LNs on pretreatment images and preoperative chemoradiotherapy. After matching, phase 1 (n = 150) and phase 2 (n = 150) patients exhibited similar clinical characteristics. Phase 2 patients had lower rates of surgical failure overall and these components: conversion to open surgery, severe complications, and insufficient harvested LNs. For robotic rectal cancer surgery, surgical outcomes improved after the 177th case. Further studies by other robotic surgeons are required to validate our results.