ObjectiveTo study the learning curve of minimal invasive coronary artery bypass grafting (MICS CABG) and the influence on the perioperative clinical effects by analyzing operation time.MethodsFrom March 2012 to November 2020, 212 patients underwent MICS CABG by the same surgeon. Among them, 59 patients (52 males and average age of 62.89±8.27 years) with single vessel bypass grafting were as a single-vessel group and 153 patients (138 males, average age of 59.80±9.22 years) with multi-vessel bypass grafting were as a multi-vessel group. Two sets of operation time-operation sequence scatter plots were made and learning curve was analyzed by cumulative summation (CUSUM) and regression method of operation time. The surgical data of each group before and after the inflection point of the learning curve were compared with the main clinical outcome events within 30 days after surgery.ResultsThere was no death, perioperative myocardial infarction and stroke in 212 MICS CABG patients and no transfer to cardiopulmonary bypass or redo thoracotomy. The learning curve conformed to the cubic fitting formula. In the single-vessel group, CUSUM (x operation number)=–1.93+93.45×x–2.33×x2+0.01×x3, P=0.000, R2=0.986, the tipping point was 27 patients. In the multi-vessel group, CUSUM (x)=y=2.87+1.15×x–1.29× x2+3.463×x3, P=0.000, R2=0.993, and the tipping point was 59 patients. The two sets of case data were compared before and after the learning curve and there was no statistical difference in main clinical outcomes within 30 days (mortality, acute myocardial infarction, stroke, perioperative blood transfusion rate), ventilator tube, and intensive care unit retention.ConclusionThe learning curve of MICS CABG conforms to the cubic formula, and the process transitions from single to multiple vessels bypass. To enter the mature stage of the learning phase, a certain number of patients need to be done. Reasonable surgical procedures and quality control measures can ensure the safety during the learning phase.
ObjectiveTo investigate how to shorten the learning curve of the laparoscopic pancreaticoduodenectomy (LPD). MethodsClinical data of 5 patients who underwent the LPD in our hospital from May 2015 to November 2015 were retrospectively analyzed. ResultsThe mean age of 58.8 years old. There were four patients who were diagnosed with periampullary tumor, one patient was distal bile duct carcinoma. The median operative time was 588 min, the average blood loss was 290 mL, the time of feeding was 5 days, the mean hospital stay was 25 days. One case died of cardiovascular event on postoperative day 1. One patient had postoperative bleeding after LPD, who recovered smoothly after reoperation for hemostasis laparoscopiclly. Conciusions LPD needs basic learning curve. The key of this procedure are appropriate treatment of pancreatic head and digestive tract reconstruction. Rich operative experience of surgeon in pancreaticoduodenectomy, optimization of the operation process, skilled in laparoscopic procedures, appropriate cases, appropriate perioperative management, and steady surgical team are also important factor for the success of LPD and shorten learning curve.
ObjectiveTo compare the differences in the learning curve and surgeon's perception for pulmonary lobectomy performed by a single surgeon using the da Vinci surgical robot versus a domestically-made robotic system. Methods A retrospective analysis was conducted on the clinical data of the first 70 consecutive patients who underwent lobectomy with the da Vinci robot and the first 70 with a domestic robot. All procedures were performed by a single thoracic surgeon at Gansu Provincial Hospital who initiated the use of both systems concurrently between 2021 and 2024. Data were analyzed using SPSS 26.0, and learning curves for both groups were plotted and analyzed using the cumulative sum (CUSUM) method. Results The da Vinci group included 41 males and 29 females with a mean age of (66.0±6.83) years and the domestic robot group included 42 males and 28 females;with a mean age of (65.09±6.14) years. For the da Vinci group, the mean operative time was (196.14±29.63) min. The CUSUM learning curve was best fitted by a cubic equation (R2=0.986; CUSUM=0.012X3−1.799X2+69.149X−59.239, where X was the surgical volume), which peaked at the 26th case, delineating the learning and mastery phases. Statistically significant differences were observed between these phases in operation time, setup time, console time, intraoperative blood loss, postoperative day 1 drainage, and number of lymph nodes dissected (all P<0.01). For the domestic robot group, the mean operative time was (187.57±24.62) min. Its CUSUM learning curve also followed a cubic fit (R2=0.910; CUSUM=0.008X3−1.152X2+40.465X+91.940), peaking at the 18th case. Significant improvements between the learning and mastery phases were also found for the same surgical metrics (all P<0.05). The surgeon's perception score was significantly higher for the da Vinci system compared to the domestic system (4.21±0.88 vs. 3.29±1.02, P<0.05). ConclusionCUSUM analysis effectively distinguishes the learning and mastery phases for both systems. The learning curve for da Vinci robotic lobectomy is overcome after 26 cases, whereas the domestic robot required 18 cases. In the mastery phase, operative time, setup time, intraoperative blood loss, and postoperative day 1 drainage are significantly lower, while the number of lymph nodes dissected is significantly higher compared to the learning phase for both systems. There are no significant differences in short-term efficacy or safety between the two groups. However, the da Vinci system provids a superior surgeon experience.
ObjectiveTo explore the learning curve of endoscopic thyroidectomy using the gasless unilateral axillary approach for papillary thyroid microcarcinoma.MethodsWe retrospectively analyzed the clinical data of 51 patients diagnosed with papillary thyroid microcarcinoma who underwent an endoscopic thyroidectomy using a gasless unilateral axillary approach by the same surgeon from November 2019 to September 2020 in the Department of Thyroid and Parathyroid Surgery, West China Hospital, Sichuan University. The cumulative sum (CUSUM) analysis was used to determine the learning curve of the technology, and the CUSUM learning curve was modeled by the best fit. The operative time, intraoperative blood loss, number of lymph nodes dissected, incidence of complications and postoperative hospital stay in different phases of the learning curve were compared.ResultsThe CUSUM fitting curve reached the top at the 18th case. As a cut-off point, the learning curve was divided into two stages: the learning improvement period and the proficiency period. The operative time of patients in the proficiency stage was significantly shorter than that in the learning improvement stage (P<0.05), and there were no statistically significant differences in other data of patients in the two stages (P>0.05).ConclusionThe CUSUM analysis method is used to accurately analyze the learning curve of endoscopic thyroidectomy using the gasless unilateral axillary approach for papillary thyroid microcarcinoma, indicating that the cumulative number of operations required to master this technique is 18 cases.
ObjectiveTo explore the learning curve of single pore video-assisted thoracoscopic surgery (VATS) for the treatment of pulmonary bullae. MethodsFrom July 2010 to October 2011, sixty consecutive patients with pulmo-nary bulla undergoing single pore VATS by the same group of surgeons in the Department of Thoracic and Cardiovascular Surgery, Songgang People's Hospital. According to the sequence of the operations, all the patients were divided into group A, B, and C with 20 patients in each group. Operation time, intraoperative blood loss, postoperative hospital stay and thoracic drainage duration were compared between the 3 groups to evaluate surgical outcomes in different stages. Operation time and postoperative hospital stay were the main indexes of the learning curve. ResultsThere was no statistical difference in age, gender or incidence of pneumothorax between the 3 groups (P > 0.05). Operation time of group A (42.7±9.4 minutes) was significantly longer than those of group B (21.3±6.7 minutes) and group C (20.8±7.5 minutes) (P < 0.01). Postoperative hospital stay of group A (10.6±2.2 days) was significantly longer than those of group B (7.6±1.2 days) and group C (7.4±1.2 days) (P < 0.05). There was no statistical difference in other indexes among the 3 groups (P > 0.05). ConclusionThe learning curve of single pore VATS for the treatment of pulmonary bullae is approximately 20 cases.
Objective To explore the clinical efficacy and learning curve of robot-assisted thymectomy via subxiphoid approach. MethodsThe clinical data of patients with robot-assisted thymectomy surgery via subxiphoid approach performed by the same surgical team in the Department of Thoracic Surgery of Shanghai Pulmonary Hospital from February 2021 to August 2022 were retrospectively analyzed. The cumulative sum (CUSUM) analysis and best fit curve were used to analyze the learning curve of this surgery. The general information and perioperative indicators of patients at different learning stages were compared to explore the impact of different learning stages on clinical efficacy of patients. ResultsA total of 67 patients were enrolled, including 31 males and 36 females, aged 57.10 (54.60, 59.60) years. The operation time was 117.00 (87.00, 150.00) min. The best fitting equation of CUSUM learning curve was y=0.021 2x3–3.192 5x2 +120.17x–84.444 (x was the number of surgical cases), which had a high R2 value of 0.977 8, and the fitting curve reached the top at the 25th case. Based on this, the learning curve was divided into a learning period and a proficiency period. The operation time and intraoperative blood loss in the proficiency stage were significantly shorter or less than those in the learning stage (P＜0.001), and there was no statistical difference in thoracic drainage time and volume between the two stages (P＞0.05). ConclusionThe learning process of robot-assisted thymectomy via subxiphoid approach is safe, and this technique can be skillfully mastered after 25 cases.
ObjectiveTo evaluate the learning curve of CT-guided medical glue localization for pulmonary nodule before video-assisted thoracic surgery (VATS). MethodsThe clinical data of the patients with pulmonary nodules who underwent CT-guided medical glue localization before VATS in our hospital from July 2018 to March 2021 were retrospectively analyzed. The patients were divided into 3 groups: a group A (from July 2018 to August 2019), a group B (from September 2019 to June 2020) and a group C (from July 2020 to March 2021). The localization time, morbidity, complete resection rate and other indexes were compared among the three groups. ResultsA total of 77 patients were enrolled, including 24 males and 53 females aged 57.4±10.1 years. There were 25 patients in the group A, 21 patients in the group B, and 31 patients in the group C. 77 pulmonary nodules were localized. There was no significant difference among the groups in the basic data (P＞0.05). The localization time in the group C was 10.6±2.0 min, which was statistically shorter than that in the group A (15.4±4.4 min) and group B (12.9±4.3 min) (P＜0.01). The incidence of complications in the group C was lower than that in the group A and group B (25.8% vs. 52.0% vs. 47.6%, P=0.04). The success rate of localization of the three groups was not statistically different (P=0.12). ConclusionThere is a learning curve in CT-guided medical glue localization for single pulmonary nodule before VATS. After the first 46 cases, the operation time can be shortened, and the incidence of complications can be decreased.
Objective To investigate the learning curve for da Vinci robot-assisted mediastinal tumor resection (DRMTR). Methods A total of 50 consecutive patients received DRMTR between March 2011 and September 2012 in our hospital. Clinical data of the 50 patients were collected and analyzed. There were 23 males, 27 females aged 46.9(17–80) years. The learning curve was evaluated by using the cumulative sum (CUSUM) analysis. Results The mean operation time was 124.6 min. The CUSUM learning curve was best modeled as a third-order polynomial curve with the equation: CUSUM=0.046×case-number3–4.681×case-number2+127.508×case-number–237.940, which had a highR2 value of 0.868. The fitting curve reached the top after the 19th case, which suggested that the surgeons master the technique after they finished 19 cases. As a cut-off point, the 19th case divided the learning curve into two phases, in which there was statistical diffference in operation time (P<0.01), intraoperative blood loss (P<0.01), the postoperative duration of chest tube drainage (P<0.01 ) and the rate of postoperative complications (P<0.05 ). Conclusion The DRMTR identified by CUSUM analysis represents two characteristic stages of DRMTR: the learning stage and the mastery stage. It is suggested from our data that the surgeons need finish about 19 cases to master DRMTR.
ObjectiveTo investigate the influence of the degree of acetabular deformity and the learning-curve on the acetabular cup positions in total hip arthroplasty (THA) for adults with developmental dysplasia of hip (DDH). MethodsBetween January 2008 and December 2015, 130 patients (144 hips) with DDH underwent primary THA, and the clinical data were analyzed retrospectively. Fifty-three patients (59 hips) were admitted before 2012, and 77 patients (85 hips) were treated after 2012. There were 32 males and 98 females, aged from 31 to 83 years (mean, 61). Unilateral replacement was performed in 116 cases and bilateral replacement in 14 cases. Of 144 hips, 48 hips were rated as Crowe type I, 57 hips as type II, and 39 hips as type of III/IV. The standard pelvic radiograph was taken within 1 week after operation. The mediCAD software was adopted to measure the angle of anteversion and abduction, bony coverage, and the distance between true rotating center and optimal rotating center to the connection of teardrops and the horizontal distance between two centers to evaluate the qualified rate of acetabular cup positions. ResultsCompared with the patients with the same type in 2013-2015 group, the anteversion angle and qualified rate of acetabular cup position significantly decreased in patients with Crowe I (P < 0.05); the horizontal distance significantly increased and qualified rate of acetabular cup position significantly decreased in patients with Crowe II (P < 0.05); and the anteversion angle significantly decreased and the horizontal distance significantly increased in patients with Crowe III/IV (P < 0.05) in 2008-2012 group. But no significant difference was shown in the other indexes (P > 0.05). In all Crowe types, the vertical distance between the true rotating center and the optimal rotating center increased with the degree of acetabular deformity in both 2008-2012 group and 2013-2015 group, showing significant difference (P < 0.05), but no significant difference was found in the other indexes (P > 0.05). ConclusionFor adults with acetabular dysplasia, there are high potential risks for unsatisfactory acetabular cup positions during primary THA. So it is necessary to evaluate acetabular deformities and to sum up operative experience so as to improve the accuracy of cups installation.
ObjectiveTo analyze the learning curve of Da Vinci robotic segmentectomy. MethodsCumulative sum analysis (CUSUM) was used to analyze the learning curve of Da Vinci robotic segmentectomy performed by the General Hospital of Northern Theater Command from February 2018 to December 2020. The learning curve was obtained by fitting, and R2 was used to judge the goodness of fitting. The clinical data of patients in different stages of learning curve were compared and analyzed. Results The first 50 patients who received Da Vinci robotic segmentectomy were included, including 24 males and 26 females, with an average age of 61.9±10.6 years. The operation time decreased gradually with the accumulation of operation patients. The goodness of fitting coefficient reached the maximum value when R2=0.907 (P<0.001), CUSUM (n) =0.009×n3−0.953×n2+24.968×n−7.033 (n was the number of patients). The fitting curve achieved vertex crossing when the number of patients reached 17. Based on this, 50 patients were divided into two stages: a learning and improving stage and a mastering stage. There were statistical differences in the operation time, intraoperative blood loss, postoperative drainage volume, number of lymph node dissection, postoperative catheter time, postoperative hospital stay, and postoperative complications between the two stages (P<0.05). ConclusionIt shows that the technical competency for assuring feasible perioperative outcomes can be achieved when the cumulative number of surgical patients reaches 17.