Cumulative Sum Analysis Research Articles

A-PoRM SIPLAS: Assessing The Post-Disaster Recovery Of Mangrove Forest In Siargao Island Protected Landscape And Seascape (SIPLAS) Area Using Sentinel-1 SAR Data

Abstract. Tropical cyclones and typhoons pose significant threats to coastal ecosystems, particularly mangrove forests. Assessing the extent of mangrove damage and monitoring recovery post-disaster is vital for effective conservation and management strategies. Space-based observations have become increasingly common in monitoring forest damage in tropical regions. However, the predominant methods for change detection rely on satellite optical imagery, which faces challenges in humid tropical zones. Technological advancements have led to the development of detection techniques utilizing synthetic aperture radar (SAR) to address cloud cover issues. The study specifically targets Siargao Island Protected Landscape and Seascape (SIPLAS), the largest contiguous forest in the Philippines, from destruction caused by Super typhoon Rai (Odette). The study utilized SAR time-series data, unsupervised log ratio change detection method and Cumulative Sum (CuSum) analysis via Google Earth Engine (GEE). Analysis of Sentinel-1 GRD images found VV polarization had the highest accuracy at 92% and an F-measure of 0.92. VH polarization had 87.5% accuracy and an F-measure of 0.87, while combining VV and VH and VV/VH achieved the same results of 80.5% overall accuracy with an F-measure of 0.82. With that, results indicated that 53% of mangroves in SIPLAS area were damaged, with 38.05% regenerating by 2022 and 56.75% by 2023, notably after September 16, 2022 detected from CuSum analysis using the VV polarization. These findings substantiate the robustness of the data and methodologies employed in monitoring mangrove resilience and supporting conservation initiatives within the SIPLAS area.

Learning curve of colorectal endoscopic submucosal dissection of an endoscopist experienced hands-on training in Japan.

Colorectal endoscopic submucosal dissection is a technically demanding procedure with a steep learning curve. In Japan, the National Cancer Center Hospital allows overseas doctors to participate in hands-on training. We aimed to assess the colorectal endoscopic submucosal dissection performance and learning curve of an endoscopist who participated in hands-on training. In this retrospective analysis using a prospectively collected database, 100 consecutive superficial colorectal tumors from 100 patients treated with endoscopic submucosal dissection by a colorectal surgeon between January 2020 and May 2024 were included. The cases were grouped into three learning periods: phase I (the initial 30 cases under local expert supervision before training in Japan), phase II (the middle 30 cases), and phase III (the last 40 cases). The primary outcome was resection speed. The median resection speed was 5, 11.7, and 13.2cm2/h in phases I, II, and III, respectively. In matched data, the resection speeds in phases II and III were higher than that in phase I (P=0.02 and P<0.001, respectively). En bloc and R0 resection rates were 99% and 95%, respectively. The en bloc resection, R0 resection, and complication rates were not different between phases. Cumulative sum analysis of the resection speed revealed that proficiency was achieved after 36 cases. An endoscopist who underwent a tutored approach and hands-on training in Japan achieved the proficiency benchmarks for colorectal endoscopic submucosal dissection after 36 cases. However, the endoscopist's extensive experience before training may contribute to excellent outcomes.

Learning curve for the combined trans-oral and chest approach to endoscopic selective neck dissection: a cumulative sum (CUSUM) analysis.

The combined trans-oral and chest approach is a novel technique for endoscopic selective neck dissection (SND), with satisfactory oncological safety and cosmetic results. However, this hybrid approach is difficult, and the learning curve remains unclear. In this study, we aimed to evaluate the short-term outcomes for this hybrid approach, and to define the associated learning curve. Clinical data and surgical outcomes of 58 PTC patients who underwent endoscopic SND via combined trans-oral and chest approach between September 2020 and April 2023 were retrospectively reviewed. The cumulative sum (CUSUM) sequential analysis technique is used to detect change, and has been applied for the evaluation of learning curves. The study population included 58 patients (40 females, 18 males), with mean age of 38.9 ± 12.7years and average body mass index of 22.6 ± 4.8kg/m2. In all cases, the same surgical team performed endoscopic SND via combined trans-oral and chest approach. The numbers of positive/retrieved lymph nodes were 4.3 ± 3.2/27.8 ± 8.4 in the lateral compartment and 4.0 ± 3.5/8.4 ± 5.1 in the central compartment. The learning curve was evaluated in terms of an initial phase (20 cases) and a mature phase (38 cases). Operative time was longer during the initial phase, compared to the mature phase (375.2 vs. 274.6min, p = 0.002). The frequency of operative complications was higher during the initial phase, compared to the mature phase (85% vs. 55.3%, p = 0.048). After the experience acquired using endoscopic SND via combined trans-oral and chest approach to treat PTC in 20 patients, the number of complications decreased significantly. Compared to data collected for the initial phase, data collected for the mature phase showed trends toward decreased operating time.

Machine learning adjusted sequential CUSUM-analyses are superior to cross-sectional analysis of excess mortality after surgery

BackgroundThe assessment of clinical outcome quality, particularly in surgery, is crucial for healthcare improvement. Traditional cross-sectional analyses often fall short in timely and systematic identification of clinical quality issues. This study explores the efficacy of machine learning adjusted sequential CUSUM (Cumulative Sum) analyses in monitoring post-surgical mortality. Material and methodsUtilizing the Global Open Source Severity of Illness Score (GOSSIS) dataset involving 91,714 patient records from 147 hospitals, this study involved the development of a machine learning model for mortality using a modified LightGBM algorithm. With this, sequential and cross sectional quality monitoring was simulated and compared. ResultsThe modified LightGBM model demonstrated superior predictive accuracy (ROC AUC of 0.88). Simulations revealed that the AI risk-adjusted CUSUM required fewer patient outcome alterations to detect atypical trends compared to standard methods. ConclusionThe AI risk-adjusted CUSUM analysis represents a significant advancement in monitoring clinical outcome quality in healthcare, especially in surgery. Its ability to detect minor discrepancies in mortality rates with greater sensitivity and specificity positions it as a valuable tool for healthcare providers. This approach could lead to earlier interventions and improved patient care.

Learning curve and complication analysis of oblique lateral interbody fusion in cases with single-segment lumbar tuberculosis: a retrospective single-center consecutive study

ObjectiveOblique lateral interbody fusion (OLIF) is becoming widely used in patients with single-segment spinal tuberculosis (STB). The learning curve and complications associated with OLIF for the treatment of STB are still unknown. This study aims to figure out the learning curve and associated complications experience of OLIF for the treatment of STB.MethodsBetween September 2018 and August 2023, 61 STB patients underwent OLIF plus percutaneous pedicle screw fixation (PPSF) were consecutively included in this research. Cumulative sum analysis (CUSUM) was applied to establish the learning curve of OLIF and determine the cut-off case number. All cases were divided into learning and experienced groups based on the cut-off case number. Clinical characteristics and relating surgical complications were compared and analyzed between the two groups.ResultsThe best-fitting curve was quadratic. The fitting equation was CUSUM (min) = 95.83 + 34.16x − 0.611 x 2 (x means operation case). The cut-off operation case number was 27 cases. The presence of significant differences particularly in the duration of operation, operative blood loss, overall incidence, and severity of postoperative complications was noteworthy between the two groups.ConclusionA total of 27 cases is the minimum number to master OLIF combined with PPSF for the treatment of patients with single-segment STB. When surgeons master this operation, the operative time, operative blood loss, overall incidence, and severity of postoperative complications will improve.

Transbronchial lung cryobiopsy for interstitial lung disease: early experience, learning curve, and the impact of sedation on complication rates at a single centre in Japan

BackgroundTransbronchial lung cryobiopsy (TBLC) has emerged as a promising diagnostic tool for interstitial lung disease (ILD). This study aimed to assess the initial experience, procedural learning curve, and influence of sedative medications on complication rates, particularly bleeding and pneumothorax, in the implementation of a TBLC program for ILD diagnosis.MethodsIn this retrospective cohort study, we analysed 119 patients who underwent TBLC at Nippon Medical School Hospital from April 2021 to March 2024. Procedural times, complication rates, and histopathological outcomes were evaluated. The learning curve was assessed using cumulative sum (CUSUM) analysis, focusing on procedure time and biopsy yield. The association between sedative medication dosages and bleeding risk was also examined.ResultsThe overall diagnostic yield was high, with alveolar tissue obtained in 97.5% of cases and a definitive pathological diagnosis achieved in 81.5% of patients. CUSUM analysis revealed a proficiency threshold at approximately 56 cases, with improved efficiency and biopsy yield in the consolidation phase. Fentanyl dosage was significantly associated with reduced bleeding complications (odds ratio 0.51, 95% confidence interval 0.27–0.97, p = 0.041).ConclusionsTBLC is a safe and effective diagnostic tool for ILDs, with a manageable learning curve for procedural efficiency. Sedation, particularly fentanyl dosage, may plays a crucial role in minimizing complications, but further research is needed to clarify this relationship. These findings support the adoption of TBLC as a standard diagnostic approach for ILD and highlight the importance of adequate training and optimized sedation protocols to ensure safety and efficacy in clinical practice.

The learning curve for robotic living donor right hepatectomy: Analysis of outcomes in two specialized centers.

Robotic surgery is an emerging minimally invasive option for living donor hepatectomy. Currently, there are no studies on the learning curve of robotic donor hepatectomy. Thus, we evaluated the learning curve for robotic donor right hepatectomy (RH). We retrospectively reviewed prospectively collected data from consecutive living donors who underwent robotic hepatectomy at two specialized centers between 2016 and 2022. We estimated the number of cases required to achieve stable operating times for robotic donor RH using cumulative sum (CUSUM) analysis. The complication rates were similar between the two centers (22.8% vs. 26.7%; p=0.74). Most complications were graded as minor (70.4%). Analysis of the total operative time demonstrated that the learning curves reached a peak at the 17th case in Center 1 and the 9th case in Center 2. The average operation times for cases 1-17 versus 18-99 in Center 1 were 603 versus 438 minutes (p<0.001), and cases 1-9 versus 10-15 in Center 2 were 532 versus 418 minutes (p=0.002). Complication rates were lower after the learning curves were achieved, although this did not reach statistical significance. A comparison of outcomes between centers suggests that a standardized approach to this complex operation can be successfully transferred.

Learning Curve for Robotic Colorectal Surgery.

With the increasing adoption of robotic surgery in clinical practice, institutions intending to adopt this technology should understand the learning curve in order to develop strategies to help its surgeons and operating theater teams overcome it in a safe manner without compromising on patient care. Various statistical methods exist for the analysis of learning curves, of which a cumulative sum (CUSUM) analysis is more commonly described in the literature. Variables used for analysis can be classified into measures of the surgical process (e.g., operative time and pathological quality) and measures of patient outcome (e.g., postoperative complications). Heterogeneity exists in how performance thresholds are defined during the interpretation of learning curves. Factors that influence the learning curve include prior surgical experience in colorectal surgery, being in a mature robotic surgical unit, case mix and case complexity, robotic surgical simulation, spending time as a bedside first assistant, and being in a structured training program with proctorship.

Short-Term Surgical Outcomes After Robotic Liver Surgery: A Propensity-Score Matched Analysis With Conventional Open Liver Surgery at a High-Volume Centre in Denmark.

The aim of this study was to investigate the perioperative outcomes of robotic liver surgery (RLS) and Open liver surgery (OLS) in a centre with a high number of operations. A 1:1 propensity score matched (PSM) analysis of a retrospective database of RLS and OLS was performed. Cumulative sum (CUSUM) analysis was performed to identify learning curves. After PSM analysis, operative time was significantly longer in the RLS group (p<0.001). Estimated blood loss was significantly lower in the RLS group (p<0.001). Transfusion rates were significantly lower in the RLS group. The length of hospital stay was shorter in the RLS group (3.5vs6.3days, p<0.001). Readmission rates were significantly lower in the RLS group (p<0.049). CUSUM analysis showed a learning curve for at least 8 low-intermediate RLS procedures and 27 advanced-Expert RLS procedures. RLS has many advantages, including being safe to perform, less blood loss and faster postoperative recovery compared with OLS.

A multi-docking strategy for robotic LAR and deep pelvic surgery with the Hugo RAS system: experience from a tertiary referral center.

In June 2023, our institution adopted the Medtronic Hugo RAS system for colorectal procedures. This system's independent robotic arms enable personalized docking configurations. This study presents our refined multi-docking strategy for robotic low anterior resection (LAR) and deep pelvic procedures, designed to maximize the Hugo RAS system's potential in rectal surgery, and evaluates the associated learning curve. This retrospective analysis included 31 robotic LAR procedures performed with the Hugo RAS system using our novel multi-docking strategy. Docking times were the primary outcome. The Mann-Kendall test, Spearman's correlation, and cumulative sum (CUSUM) analysis were used to assess the learning curve and efficiency gains associated with the strategy. Docking times showed a significant negative trend (p < 0.01), indicating improved efficiency with experience. CUSUM analysis confirmed a distinct learning curve, with proficiency achieved around the 15th procedure. The median docking time was 6min, comparable to other robotic platforms after proficiency. This study demonstrates the feasibility and effectiveness of a multi-docking strategy in robotic LAR using the Hugo RAS system. Our personalized approach, capitalizing on the system's unique features, resulted in efficient docking times and streamlined surgical workflow. This approach may be particularly beneficial for surgeons transitioning from laparoscopic to robotic surgery, facilitating a smoother adoption of the new technology. Further research is needed to validate the generalizability of these findings across different surgical settings and experience levels.

Learning curve in robotic liver surgery: easily achievable, evolving from laparoscopic background and team-based

PurposeLimited and heterogeneous literature data necessitate a focused examination of the learning curve in robotic liver resections. This study aims to assess the learning curve of two surgeons from the same team with differing laparoscopic backgrounds. MethodSince February 2021, San Raffaele Hospital in Milan has implemented a robotic liver surgery program, performing 250 resections by three trained console surgeons. Using cumulative sum (CUSUM) analysis, the learning curve was evaluated for a Pioneer Surgeon (PS) with around 1200 laparoscopic cases and a New Generation Surgeon (NGS) with approximately 100 laparoscopic cases. Cases were stratified by complexity (38 low, 74 intermediate, 85 high). ResultsBoth PS and NGS demonstrated a learning curve for operative time after 15 low-complexity and 10 intermediate-complexity cases, with high-complexity learning curves apparent after 10 cases for PS and 18 cases for NGS. Conversion rates remained unaffected, and neither surgeon experienced increased blood loss or postoperative complications. A “team learning curve” effect in terms of operative time emerged after 12 cases, suggesting the importance of a cohesive surgical team. DiscussionThe robotic platform facilitated a relatively brief learning curve for low and intermediate complexity cases, irrespective of laparoscopic background, underscoring the benefits of team collaboration.

Overcoming the Learning Curve in Robot-Assisted Spinal Surgery—How Does It Compare to O-Arm Navigation?

Background: Robotic systems have the potential to significantly enhance the accuracy and outcomes of spinal surgery. Adopting this new technology requires an examination of its learning curve and influencing factors. This study analyzes the learning curve associated with using the Mazor X Stealth Edition system for pedicle screw placement and performs a matched-pair analysis to compare operative durations between robot-assisted and navigation-based surgeries, evaluating the efficiency of the robotic system. Methods: We collected retrospective operative data from patients who underwent robot-assisted pedicle screw placements between December 2020 and June 2024 and conducted a cumulative sum (CuSUM) analysis to assess the learning curve, focusing on the robotic system’s setup duration. Additionally, we compared a group of patients who underwent robot-assisted pedicle screw placements with a pair-matched group who underwent O-arm-based navigation-assisted pedicle screw placements. Results: There was a notable decrease in the robotic setup duration, with a significant shift in trend observed after the first 20 cases. While the initial setup time was 24 minutes, it reduced to 17 minutes in later cases, reflecting a marked improvement in efficiency as the surgeon gained more experience with the robot. Conclusion: Our findings indicate there were no added difficulties using the robotic system compared to the navigation system. Moreover, the learning curve for the robotic system can be quickly surmounted, and it offers clear advantages over previous systems, making it a valuable tool for pedicle screw application.

Learning curve for a five-step procedure, transthoracic single-port assisted laparoscopic transabdominal diaphragmatic approach, for Siewert type II adenocarcinoma of the esophagogastric junction

Objective: To investigate the learning curve for a five-step procedure, namely, a transthoracic single-port assisted laparoscopic transabdominal diaphragmatic approach, for Siewert type II adenocarcinoma of the esophagogastric junction. Methods: In this retrospective cohort study, we analyzed relevant clinical data of 66 patients with Siewert type II adenocarcinoma of the esophagogastric junction who had undergone the five-step procedure performed by the same surgeon in the Gastrointestinal Surgery Department of Guangdong Provincial Hospital of Chinese Medicine from May 2017 to April 2023. The learning curve were plotted using cumulative summation analysis and selected indicators, including intraoperative blood loss, duration of surgery, time to first flatus, time to first tolerance of liquid food, length of hospital stay, and incidence of perioperative complications at different stages were compared. The data were analyzed using SPSS 24.0 statistical software. Numerical data are presented as cases (%) and data were analyzed using the χ2 test or Fisher's exact test. Normally distributed measurement data are presented as x±s, and independent sample t-testing was performed for inter group comparison. Non-normally distributed measurement data are presented as M(Q1, Q3) and the Mann-Whitney U test was used for inter group comparison. Results: The five-step procedure had been successfully completed without switching to open surgery in all 66 study patients. There were no perioperative deaths, blood loss was 100 (50, 200) mL and duration of surgery 329.4±87.3 minutes. The equation of optimal fit for the duration of surgery was y=0.031x3-4.4757x2+164.97x-264.4 (P<0.001, R2=0.9797). The cumulative summation learning curve reached a vertex when 25 surgical procedures had accumulated. Using 25 cases as the cut-off, we divided the learning curves into learning and proficiency periods and patients into learning (25) and proficiency period groups (41). There were no statistically significant differences between the two groups of patients in sex, age, body mass index, American Society of Anesthesiologists score, history of abdominal surgery, comorbidities, preoperative neoadjuvant therapy, maximum tumor diameter, surgical procedure, or T and N stage of tumor (P>0.05). The following factors differed significantly (all P<0.05) between the learning and proficiency stages: in the latter there was less intraoperative blood loss (100 [50, 100] ml vs. 200 [100, 200] ml, U=-3.940, P<0.001), shorter duration of surgery ([289.8±50.7] minutes vs. [394.4±96.0] minutes, t=5.034, P<0.001), more mediastinal lymph nodes removed (5 [2, 8] vs. 2 [1, 5], U=-2.518, P=0.012), earlier time to first flatus (2 [2, 3] days vs. 4 [3, 6] days, U=-4.016, P<0.001), earlier time to first tolerance of liquid food (5 [4, 6] days vs. 7 [6, 8] days, U=-2.922, P=0.003), shorter duration of hospital stay (8 [8, 10] vs. 10 [9, 12] days, U=-2.028, P=0.043). The incidence of surgical complications did not differ significantly between the two groups (P=0.238). Conclusion: Satisfactory results can be achieved with the five-step procedure for patients with Siewert type II adenocarcinoma of the esophagogastric junction once 25 procedures have been performed.

The Role of ICG-Guided Fluorescent Mode in Boosting the Learning Curve of Laparoscopic Cholecystectomy.

Background: The most common therapy for gallstones is laparoscopic cholecystectomy (LC). How to help young residents avoid bile duct injuries (BDI) during surgery and grasp LC seems to be a paradox. Methods: We retrospectively reviewed 145 cases of LC operated by two residents under indocyanine green (ICG)-guided mode or normal LC procedures to illustrate the role of ICG mode in boosting the LC learning curve. The clinic data were analyzed by logistic regression, receiver operator curve tests, Cumulative Sum (CUSUM), and Risk-Adjusted Cumulative Sum (RA-CUSUM) analysis. Results: The operation failure rate is similar. However, operation time under ICG mode is shorter than that under normal mode. The peak at the 49th case represented the normal resident's complete mastery of the surgery, while the peak point of ICG mode appeared at the 36th case in the fitting curve. The most significant cumulative risk (peak point) of operation failure of LC was at the 35th case in ICG LC mode, while it appeared in the 49th in normal LC mode. Conclusions: Owing to the advantage of real-time imaging and the stable success rate of cholangiography, ICG-guided LC helps residents shorten the operation time, boost the learning curve, and manage to control the operation failure rate.

Improvement and application of back random response detection: Based on cumulative sum and change point analysis.

In educational and psychological assessments, benefiting from back random response (BRR) is a major type of rapid guessing in misfitting item score patterns. Person-fit statistics (PFS) based on cumulative sum (CUSUM) and change point analysis (CPA) from statistical process control (SPC) are better than other PFS for detecting aberrant response. In this study, we developed new person-fit statistics based on three algorithms from CPA procedure and CUSUM method for detection of person misfit with dichotomous or polytomous items. By means of simulated data, the effectiveness of the new statistics to detect test-takers with BRR was investigated.

Learning curve comparison between switching approach and switching implant in cementless short stem total hip arthroplasty.

Implementing new approaches or new implants is always related with a certain learning curve in total hip arthroplasty (THA). Currently, many surgeons are switching to minimally invasive approaches combined with short stems for performing THA. Therefore, we aimed to asses and compare the learning curve of switching from an anterolateral Watson Jones approach (ALA) to a direct anterior approach (DAA) with the learning curve of switching from a neck-resecting to a partially neck-sparing short stem in cementless THA. The first 150 consecutive THA performed through a DAA (Group A) and the first 150 consecutive THA using a partially neck-sparing short stem (Group B) performed by a single surgeon were evaluated within this retrospective cohort study. All cases were screened for surgery related adverse events (AE). Furthermore, the operative time of each surgery was evaluated and the learning curve assessed performing a cumulative sum (CUSUM) analysis. Overall, significantly more AE occurred in Group A compared to Group B (18.0% vs. 10.0%; p = 0.046). The sub-analysis of the AE revealed higher rates of periprosthetic joint infections (2.7% vs. 0.7%; p = 0.176), periprosthetic fractures (4.0% vs. 2.0%; p = 0.310) and overall revisions (4.7% vs. 1.3% p = 0.091) within Group A without statistical significance. The CUSUM analysis revealed a consistent reduction of operative time after 97 cases in Group A and 79 cases in Group B. A significantly higher overall rate of AE was detected while switching approach compared to switching implant for performing THA. However, according to the results of this study, surgeons should be aware of the learning curve of the adoption to a new implant with different fixation philosophy as well.

Learning curve and safety of the implementation of laparoscopic complete mesocolic excision with intracorporeal anastomosis for right-sided colon cancer: results from a propensity score-matched study.

Retrospective studies and randomized controlled trials support the safety of laparoscopic complete mesocolic excision (CME) for the treatment of right-sided colon cancer (RSCC). Few studies, however, examine the learning curve of this operation and its impact on safety during an implementation period. We aim to evaluate the learning curve and safety of the implementation of laparoscopic CME with intracorporeal anastomosis for RSCC. Consecutive patients undergoing a laparoscopic right colectomy with intracorporeal anastomosis for RSCC between January 2016 and June 2023 were included. Clinical, perioperative, and histopathological variables were collected. Correlation and cumulative sum (CUSUM) analyses between the operating time and case number were performed. Breakpoints of the learning curve were estimated using the broken-line model. CME and conventional laparoscopic right colectomy outcomes were compared after propensity score matching (PSM). Two hundred and ninety patients underwent laparoscopic right colectomy during study period. One hundred and eight met inclusion criteria. After PSM, 56 non-CME and 28 CME patients were compared. CME group had a non-statistically significant tendency to a longer operating time (201 versus 195min; p = 0.657) and a shorter hospital stay (3 versus 4days; p = 0.279). No significant differences were found in total complication rates or their profile. Correlation analysis identified a significant trend toward operating time reduction with increasing case numbers (Pearson correlation coefficient = - 0.624; p = 0.001). According to the CUSUM analysis, an institutional learning curve was deemed completed after 13 cases and the broken-line model identified three phases: learning (1-6 cases), consolidation (7-13 cases), and mastery (after 13 cases). The learning curve of laparoscopic CME for RSCC can be achieved after 13 cases in centers with experience in advanced laparoscopic surgery and surgeons with familiarity with this technique. Its implementation within this setting seems to be as safe as performing a conventional right colectomy.

263. LEARNING CURVE ANALYSIS USING CUMULATIVE SUM TECHNIQUES FOR ROBOT-ASSISTED MINIMALLY INVASIVE ESOPHAGECTOMY

Abstract Introduction Robot-assisted minimally invasive esophagectomy (RAMIE) has improved the technical difficulty of the conventional minimally invasive esophagectomy, by more precisely operated forceps and stability of the surgical fields. Although it is widely accepted that RAMIE demands excellence in robotic surgery, it is unclear how many cases were needed to reach the proficiency. This study aimed to investigate the learnings curve of two surgeons, with respect to perioperative findings. Methods Patients who underwent RAMIE using a Da Vinci Xi Surgical System between November 2018 and February 2024 were included. Surgeon A introduced RAMIE and Surgeon B started the training of RAMIE after standardization. Both surgeons were certified by the Japan Society for Endoscopic Surgery and qualified surgeon by the Japan Esophageal Society. A cumulative sum (CUSUM) analyses were performed for console time for thoracic procedure to generate the learning curves of each surgeon. The cases before the changepoint of the CUSUM curve was defined as phase I (learning phase), and after the changepoint as phase II (proficiency phase). The perioperative outcomes were compared between the phases. Results Surgeon A and B performed 63 and 33 cases, respectively. Surgeon B started RAMIE under guidance of Surgeon A, who had already experienced 39 cases at that time. CUSUM curve showed that Surgeon B required fewer cases to reach the phase II (proficiency phase) than Surgeon A (16 cases for Surgeon B vs. 27 cases for Surgeon A). There was no significant difference between the phase I and II in patient characteristics including age, sex, tumor location, neoadjuvant chemotherapy, and clinical TNM stages and the extent of lymph node dissection. Total operation time significantly decreased from phase I to phase II: 796 min [730-824] vs. 708 min [627-764]; P&amp;lt;0.01 for Surgeon A, 806 min [751-853] vs. 686 min [635-707]; P&amp;lt;0.01 for Surgeon B. During Phase I, console time of Surgeon B was significantly longer than console time of Surgeon A (408 min [354-432] vs. 360 min [325-385], P&amp;lt;0.01). However, in Phase II, the difference in time attenuated (281 min [255-299] vs. 266 min [244-316], P=0.68). There was no significant difference in intraoperative blood loss or the incidence of postoperative complications including recurrent laryngeal nerve palsy, anastomotic leakage and pneumonia. Conclusion It is suggested that training in standardized surgical procedures for RAMIE under the guidance of an experienced surgeon could accelerate the pace of learning.

Enlightenment of robotic gastrectomy from 527 patients with gastric cancer in the minimally invasive era: 5 years of optimizing surgical performance in a high-volume center - a retrospective cohort study.

Learning curves have been used in the field of robotic gastrectomy (RG). However, it should be noted that the previous study did not comprehensively investigate all changes related to the learning curve. This study aims to establish a learning curve for radical RG and evaluate its effect on the short-term outcomes of patients with gastric cancer. The clinicopathological data of 527 patients who underwent RG between August 2016 and June 2021 were retrospectively analyzed. Learning curves related to the operation time and postoperative hospital stay were determined separately using cumulative sum (CUSUM) analysis. Then, the impact of the learning curve on surgical efficacy was analyzed. Combining the CUSUM curve break points and technical optimization time points, the entire cohort was divided into three phases (patients 1-100, 101-250, and 251-527). The postoperative complication rate and postoperative recovery time tended to decrease significantly with phase advancement ( P <0.05). More extraperigastric examined lymph nodes (LN) were retrieved in phase III than in phase I (I vs. III, 15.12±6.90 vs. 17.40±7.05, P =0.005). The rate of LN noncompliance decreased with phase advancement. Textbook outcome (TO) analysis showed that the learning phase was an independent factor in TO attainment ( P <0.05). With learning phase advancement, the short-term outcomes were significantly improved. It is possible that our optimization of surgical procedures could have contributed to this improvement. The findings of this study facilitate the safe dissemination of RG in the minimally invasive era.

Cumulative sum (CUSUM) analysis to assess caudal block performance among anesthesia residents.

Cumulative sum (CUSUM) analysis to assess caudal block performance among anesthesia residents.