ROSA膝关节系统在机器人辅助全膝关节置换术中快速减少手术时间和高度准确的对齐和股骨假体大小预测。

IF 3.2 Q2 ORTHOPEDICS Journal of Experimental Orthopaedics Pub Date : 2025-01-27 DOI:10.1002/jeo2.70148

Stefano Petrillo, Giorgio Moretti, Niccolò Bordignon, Sergio Romagnoli

{"title":"ROSA膝关节系统在机器人辅助全膝关节置换术中快速减少手术时间和高度准确的对齐和股骨假体大小预测。","authors":"Stefano Petrillo, Giorgio Moretti, Niccolò Bordignon, Sergio Romagnoli","doi":"10.1002/jeo2.70148","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Purpose</h3>\n \n <p>Robotic-assisted total knee arthroplasty (RA-TKA) has gained popularity for its potential ability to improve surgical precision and patient outcomes, despite concerns about its long learning curve and increased operative times. The aim of this study is to evaluate the learning curve of the ROSA® Knee System, the relationship between each phase of the learning curve and the accuracy of the robotic system in femoral component size and knee alignment prediction.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>A single surgeon retrospective analysis of total operative time (TOT) and total robotic time was conducted. The first 60 cases of RA-TKA performed between July 2023 and March 2024 were included. Six (10%) patients were excluded due to incomplete surgical reports. A cumulative sum analysis was used to identify the learning and proficiency phases of the surgeon's learning curve. Moreover, femoral component size prediction accuracy and the difference between planned and achieved knee alignment were analyzed.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The projected learning curve showed a significant reduction in TOT after 10 cases, with mean time decreasing from 62.6 ± 7.92 min in the learning phase to 49.9 ± 8.10 min in the proficiency phase (<i>p</i> = 0.0008). The robotic procedure accounted for 48% and 42% of the TOT in the learning and proficiency phases, respectively. Prediction in femoral component size was accurate in 92.6% of cases. The difference between planned and achieved knee alignment was not statistically significant (1.1° ± 0.9°).</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>The ROSA® Knee System allows a rapid learning curve in RA-TKA, with a significant reduction in operative time after the first 10 cases. An experienced orthopaedic surgeon specialized in knee arthroplasty can quickly reach a proficiency phase, maintaining high accuracy in alignment and femoral component sizing. These findings suggest that the ROSA® system is an effective and reliable tool for CR RA-TKA, offering precise and reproducible outcomes.</p>\n </section>\n \n <section>\n \n <h3> Level of Evidence</h3>\n \n <p>IV.</p>\n </section>\n </div>","PeriodicalId":36909,"journal":{"name":"Journal of Experimental Orthopaedics","volume":"12 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770475/pdf/","citationCount":"0","resultStr":"{\"title\":\"Rapid reduction in surgical time and high level of accuracy in alignment and femoral component size prediction in robotic-assisted total knee arthroplasty with ROSA Knee System\",\"authors\":\"Stefano Petrillo, Giorgio Moretti, Niccolò Bordignon, Sergio Romagnoli\",\"doi\":\"10.1002/jeo2.70148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Purpose</h3>\\n \\n <p>Robotic-assisted total knee arthroplasty (RA-TKA) has gained popularity for its potential ability to improve surgical precision and patient outcomes, despite concerns about its long learning curve and increased operative times. The aim of this study is to evaluate the learning curve of the ROSA® Knee System, the relationship between each phase of the learning curve and the accuracy of the robotic system in femoral component size and knee alignment prediction.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>A single surgeon retrospective analysis of total operative time (TOT) and total robotic time was conducted. The first 60 cases of RA-TKA performed between July 2023 and March 2024 were included. Six (10%) patients were excluded due to incomplete surgical reports. A cumulative sum analysis was used to identify the learning and proficiency phases of the surgeon's learning curve. Moreover, femoral component size prediction accuracy and the difference between planned and achieved knee alignment were analyzed.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>The projected learning curve showed a significant reduction in TOT after 10 cases, with mean time decreasing from 62.6 ± 7.92 min in the learning phase to 49.9 ± 8.10 min in the proficiency phase (<i>p</i> = 0.0008). The robotic procedure accounted for 48% and 42% of the TOT in the learning and proficiency phases, respectively. Prediction in femoral component size was accurate in 92.6% of cases. The difference between planned and achieved knee alignment was not statistically significant (1.1° ± 0.9°).</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>The ROSA® Knee System allows a rapid learning curve in RA-TKA, with a significant reduction in operative time after the first 10 cases. An experienced orthopaedic surgeon specialized in knee arthroplasty can quickly reach a proficiency phase, maintaining high accuracy in alignment and femoral component sizing. These findings suggest that the ROSA® system is an effective and reliable tool for CR RA-TKA, offering precise and reproducible outcomes.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Level of Evidence</h3>\\n \\n <p>IV.</p>\\n </section>\\n </div>\",\"PeriodicalId\":36909,\"journal\":{\"name\":\"Journal of Experimental Orthopaedics\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-01-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11770475/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Experimental Orthopaedics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://esskajournals.onlinelibrary.wiley.com/doi/10.1002/jeo2.70148\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ORTHOPEDICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Experimental Orthopaedics","FirstCategoryId":"1085","ListUrlMain":"https://esskajournals.onlinelibrary.wiley.com/doi/10.1002/jeo2.70148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ORTHOPEDICS","Score":null,"Total":0}

引用次数: 0

摘要

目的：机器人辅助全膝关节置换术（RA-TKA）因其提高手术精度和患者预后的潜在能力而受到欢迎，尽管人们担心其学习曲线长和手术时间增加。本研究的目的是评估ROSA®膝关节系统的学习曲线，学习曲线的每个阶段与机器人系统在股骨假体大小和膝关节对齐预测方面的准确性之间的关系。方法：对单个外科医生的总手术时间（TOT）和总机器人时间进行回顾性分析。纳入2023年7月至2024年3月间进行RA-TKA的前60例。6例（10%）患者因手术报告不完整而被排除。累积和分析用于确定外科医生学习曲线的学习和熟练阶段。此外，还分析了股骨假体尺寸预测的准确性以及计划与实现的膝关节对齐之间的差异。结果：10例患者的预测学习曲线显示TOT显著降低，平均时间由学习阶段的62.6±7.92 min降至熟练阶段的49.9±8.10 min （p = 0.0008）。在学习和熟练阶段，机器人程序分别占总时间的48%和42%。股骨假体大小的预测准确率为92.6%。计划膝关节对齐与实现膝关节对齐的差异无统计学意义（1.1°±0.9°）。结论：ROSA®膝关节系统允许RA-TKA快速学习曲线，在前10例后显着减少手术时间。经验丰富的骨科医生在膝关节置换术方面可以迅速达到熟练阶段，保持高度准确的对齐和股骨假体尺寸。这些结果表明，ROSA®系统是一种有效可靠的CR RA-TKA工具，提供精确和可重复的结果。证据等级：四级。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

摘要图片

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Rapid reduction in surgical time and high level of accuracy in alignment and femoral component size prediction in robotic-assisted total knee arthroplasty with ROSA Knee System

Purpose

Robotic-assisted total knee arthroplasty (RA-TKA) has gained popularity for its potential ability to improve surgical precision and patient outcomes, despite concerns about its long learning curve and increased operative times. The aim of this study is to evaluate the learning curve of the ROSA® Knee System, the relationship between each phase of the learning curve and the accuracy of the robotic system in femoral component size and knee alignment prediction.

Methods

A single surgeon retrospective analysis of total operative time (TOT) and total robotic time was conducted. The first 60 cases of RA-TKA performed between July 2023 and March 2024 were included. Six (10%) patients were excluded due to incomplete surgical reports. A cumulative sum analysis was used to identify the learning and proficiency phases of the surgeon's learning curve. Moreover, femoral component size prediction accuracy and the difference between planned and achieved knee alignment were analyzed.

Results

The projected learning curve showed a significant reduction in TOT after 10 cases, with mean time decreasing from 62.6 ± 7.92 min in the learning phase to 49.9 ± 8.10 min in the proficiency phase (p = 0.0008). The robotic procedure accounted for 48% and 42% of the TOT in the learning and proficiency phases, respectively. Prediction in femoral component size was accurate in 92.6% of cases. The difference between planned and achieved knee alignment was not statistically significant (1.1° ± 0.9°).

Conclusions

The ROSA® Knee System allows a rapid learning curve in RA-TKA, with a significant reduction in operative time after the first 10 cases. An experienced orthopaedic surgeon specialized in knee arthroplasty can quickly reach a proficiency phase, maintaining high accuracy in alignment and femoral component sizing. These findings suggest that the ROSA® system is an effective and reliable tool for CR RA-TKA, offering precise and reproducible outcomes.