Fatih Sendag, Burak Zeybek, Ali Akdemir, Banu Ozgurel, Kemal Oztekin
{"title":"妇科良性疾病机器人子宫切除术的学习曲线分析。","authors":"Fatih Sendag, Burak Zeybek, Ali Akdemir, Banu Ozgurel, Kemal Oztekin","doi":"10.1002/rcs.1567","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The objective was to evaluate the learning curve for performing a robotic hysterectomy to treat benign gynaecological disease.</p><p><strong>Methods: </strong>Thirty-six patients underwent robotic hysterectomy for benign indications. A systematic chart review of consecutive cases was conducted. The collected data included age, BMI, operating time, set-up time, docking time, uterine weight, blood loss, intraoperative complications, postoperative complications, conversions to laparotomy and length of hospital stay.</p><p><strong>Results: </strong>The mean operating, set-up and docking times were 169 ± 54.5, 52.9 ± 12.4 and 7.8 ± 7.6 min, respectively. The learning curve analysis revealed a decrease in both docking and operating times, with both curves plateauing after case 9.</p><p><strong>Conclusions: </strong>The learning curve analysis revealed a decrease in docking time and operating time after case 9, suggesting that there might be a fast, learning curve for experienced laparoscopic surgeons to master robotic hysterectomy, and that the docking process does not have a significant negative influence on the overall operating time.</p>","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"10 3","pages":"275-9"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/rcs.1567","citationCount":"13","resultStr":"{\"title\":\"Analysis of the learning curve for robotic hysterectomy for benign gynaecological disease.\",\"authors\":\"Fatih Sendag, Burak Zeybek, Ali Akdemir, Banu Ozgurel, Kemal Oztekin\",\"doi\":\"10.1002/rcs.1567\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The objective was to evaluate the learning curve for performing a robotic hysterectomy to treat benign gynaecological disease.</p><p><strong>Methods: </strong>Thirty-six patients underwent robotic hysterectomy for benign indications. A systematic chart review of consecutive cases was conducted. The collected data included age, BMI, operating time, set-up time, docking time, uterine weight, blood loss, intraoperative complications, postoperative complications, conversions to laparotomy and length of hospital stay.</p><p><strong>Results: </strong>The mean operating, set-up and docking times were 169 ± 54.5, 52.9 ± 12.4 and 7.8 ± 7.6 min, respectively. The learning curve analysis revealed a decrease in both docking and operating times, with both curves plateauing after case 9.</p><p><strong>Conclusions: </strong>The learning curve analysis revealed a decrease in docking time and operating time after case 9, suggesting that there might be a fast, learning curve for experienced laparoscopic surgeons to master robotic hysterectomy, and that the docking process does not have a significant negative influence on the overall operating time.</p>\",\"PeriodicalId\":75029,\"journal\":{\"name\":\"The international journal of medical robotics + computer assisted surgery : MRCAS\",\"volume\":\"10 3\",\"pages\":\"275-9\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/rcs.1567\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The international journal of medical robotics + computer assisted surgery : MRCAS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/rcs.1567\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2013/12/27 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The international journal of medical robotics + computer assisted surgery : MRCAS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/rcs.1567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2013/12/27 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of the learning curve for robotic hysterectomy for benign gynaecological disease.
Background: The objective was to evaluate the learning curve for performing a robotic hysterectomy to treat benign gynaecological disease.
Methods: Thirty-six patients underwent robotic hysterectomy for benign indications. A systematic chart review of consecutive cases was conducted. The collected data included age, BMI, operating time, set-up time, docking time, uterine weight, blood loss, intraoperative complications, postoperative complications, conversions to laparotomy and length of hospital stay.
Results: The mean operating, set-up and docking times were 169 ± 54.5, 52.9 ± 12.4 and 7.8 ± 7.6 min, respectively. The learning curve analysis revealed a decrease in both docking and operating times, with both curves plateauing after case 9.
Conclusions: The learning curve analysis revealed a decrease in docking time and operating time after case 9, suggesting that there might be a fast, learning curve for experienced laparoscopic surgeons to master robotic hysterectomy, and that the docking process does not have a significant negative influence on the overall operating time.