{"title":"DOES LEARNING CURVE AFFECT THE ACCURACY IN RESECTION ALIGNMENT DURING NAVIGATED TOTAL KNEE ARTHROPLASTY","authors":"Y. Dai, C. Hamad, A. Jung, L. Angibaud","doi":"10.29007/rxll","DOIUrl":null,"url":null,"abstract":"Computer-assisted orthopaedic surgery (CAOS) has been demonstrated to increase accuracy to component alignment of total knee arthroplasty compared to conventional techniques. The purpose of this study was to assess if learning affects resection alignment using a specific CAOS system. Nine surgeons, each with >80 TKA experience using a contemporary CAOS system were selected. Prior to the study, six surgeons had already experienced with CAOS TKA (experienced), while the rest three were new to the technology (novice). The following surgical parameters were investigated: 1) planned resection, resection parameters defined by the surgeon prior to the bone cuts; 2) checked resection, digitalisation of the realised resection surfaces. Deviations in the alignment between planned and checked resections were compared between the first 20 cases (in learning curve) and the last 20 cases (well past learning curve) within each surgeon. Any significance detected (p 1° difference in means indicated clinically meaningful impact on alignment by the learning phase. Both pooled and surgeon-specific analysis exhibited no clinically meaningful significant difference between the first 20 and the last 20 cases from both experienced and novice surgeon groups. The resections in both the first 20 and the last 20 cases demonstrated acceptable rates of over 95% in alignment ( This study demonstrated that independent of the surgeon9s prior CAOS experiences, the CAOS system investigated can provide an accurate and precise solution to assist in achieving surgical resection goals with no clinically meaningful compromise in alignment accuracy and outliers during the learning phase.","PeriodicalId":15048,"journal":{"name":"Journal of Bone and Joint Surgery-british Volume","volume":"37 1","pages":"10-10"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Bone and Joint Surgery-british Volume","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29007/rxll","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Computer-assisted orthopaedic surgery (CAOS) has been demonstrated to increase accuracy to component alignment of total knee arthroplasty compared to conventional techniques. The purpose of this study was to assess if learning affects resection alignment using a specific CAOS system. Nine surgeons, each with >80 TKA experience using a contemporary CAOS system were selected. Prior to the study, six surgeons had already experienced with CAOS TKA (experienced), while the rest three were new to the technology (novice). The following surgical parameters were investigated: 1) planned resection, resection parameters defined by the surgeon prior to the bone cuts; 2) checked resection, digitalisation of the realised resection surfaces. Deviations in the alignment between planned and checked resections were compared between the first 20 cases (in learning curve) and the last 20 cases (well past learning curve) within each surgeon. Any significance detected (p 1° difference in means indicated clinically meaningful impact on alignment by the learning phase. Both pooled and surgeon-specific analysis exhibited no clinically meaningful significant difference between the first 20 and the last 20 cases from both experienced and novice surgeon groups. The resections in both the first 20 and the last 20 cases demonstrated acceptable rates of over 95% in alignment ( This study demonstrated that independent of the surgeon9s prior CAOS experiences, the CAOS system investigated can provide an accurate and precise solution to assist in achieving surgical resection goals with no clinically meaningful compromise in alignment accuracy and outliers during the learning phase.