中国组织工程研究 ›› 2020, Vol. 24 ›› Issue (9): 1313-1317.doi: 10.3969/j.issn.2095-4344.2403

• 人工假体 artificial prosthesis •    下一篇

MAKO机器人辅助后外侧入路全髋关节置换的学习曲线及临床早期效果

崔可赜,郭  祥,韩贵斌,陈元良,刘亦恒,钟海波   

  1. 中南大学湘雅医学院附属海口医院西院(海口骨科与糖尿病医院),海南省海口市  570208
  • 收稿日期:2019-05-09 修回日期:2019-05-22 接受日期:2019-06-29 出版日期:2020-03-28 发布日期:2020-02-11
  • 作者简介:崔可赜,男,1974年生,吉林省人,汉族,2006年吉林大学毕业,硕士,副主任医师,主要从事创伤骨科方面的研究。

Learning curve and early clinical results of total hip arthroplasty with MAKO robot assisted posterolateral approach

Cui Keze, Guo Xiang, Han Guibin, Chen Yuanliang, Liu Yiheng, Zhong Haibo   

  1. West Hospital (Haikou Orthopedics and Diabetes Hospital), Haikou Hospital, Xiangya School of Medicine, Central South University, Haikou 570208, Hainan Province, China
  • Received:2019-05-09 Revised:2019-05-22 Accepted:2019-06-29 Online:2020-03-28 Published:2020-02-11
  • About author:Cui Keze, Master, Associate chief physician, West Hospital (Haikou Orthopedics and Diabetes Hospital), Haikou Hospital, Xiangya School of Medicine, Central South University, Haikou 570208, Hainan Province, China

摘要:

文题释义:

MAKO机器人辅助:是一种半自动手术机器人系统,具有良好的反馈特性,半自动封闭型,主要依靠医生术中操作,术中可根据实际情况随时调整手术计划,髋膝关节置换以及膝关节单髁置换均可操作,是目前世界上应用最广泛的骨科半自动手术机器人系统。

学习曲线:手术医生学习一项新技术,在一定时间内,可以获得的技能或知识的速率,概括来说就是熟能生巧,连续进行有固定方式的手术工作,操作会越来越熟练,完成同样手术操作的工作时间会越来越短,术后的结果更趋于优良。

背景:随着全髋关节置换技术的不断成熟,对手术的精准程度要求越来越高,以期望患者得到更良好的置换结果;MAKO机器人辅助下的关节置换技术使手术的精准程度实现了可能,但该项技术有一定的学习曲线,早期的置换结果及并发症应是关注重点。

目的:分析MAKO机器人辅助下后外侧入路人工髋关节置换的学习曲线及临床早期效果。

方法:回顾性分析2017年3月至2018年3月中南大学湘雅医学院附属海口医院西院(海口骨科与糖尿病医院)采用MAKO机器人辅助下后外侧入路行人工髋关节置换26例患者的病例资料,其中男12例,女14例。关注学习曲线早期的髋关节置换中易发生的问题及早期临床结果。

结果与结论:手术时间56-155 min,平均(87.0±16.1)min;显性出血220-850 mL,平均(336±246)mL。髋臼外展角(41.3±2.7)°,髋臼前倾角(16.4±3.4)°,下肢长度差值为(1.0±2.0)mm,股骨偏心距差值为(1.6±0.6)mm。术中股骨距骨折1例,无感染、坐骨神经损伤及伤口相关并发症。置换后弃拐行走时间3-6周,平均(3.8±2.1)周。置换后3个月Harris评分(92.1±4.7)分。提示MAKO机器人辅助下后外侧入路全髋关节置换学习曲线的病例短期内显示疼痛改善,功能康复快,临床结果良好,手术时间随着熟练度而缩短,假体位置均在安全范围内,失血量亦在可接受范围。

ORCID: 0000-0001-7677-1328(崔可赜)

中国组织工程研究杂志出版内容重点:人工关节;骨植入物;脊柱骨折;内固定;数字化骨科;组织工程

关键词: 髋关节, 关节置换, MAKO机器人, 后外侧入路, 学习曲线, 假体, 可视化, 导航

Abstract:

BACKGROUND: With the maturity of total hip arthroplasty, the need for operative accuracy is highly increasing to get better operative results. The joint replacement technique assisted by MAKO robot makes the precision of the operation possible. However, this technology has a certain learning curve, and early replacement results and complications should be the major concern.

OBJECTIVE: To analyze the learning curve and early clinical results of total hip arthroplasty through the posterolateral approach assisted by the MAKO robot.

METHODS: From March 2017 to March 2018, 26 patients undergoing hip arthroplasty via posterolateral approach assisted by MAKO robots in West Hospital (Haikou Orthopedics and Diabetes Hospital), Haikou Hospital, Xiangya School of Medicine, Central South University, including 12 males and 14 females, were retrospectively analyzed. The problems and early clinical outcomes of hip replacement in the early learning curve were focused on.

RESULTS AND CONCLUSION: The operation time was 56-155 minutes, mean (87.0 ± 16.1) minutes. The dominant bleeding was 220-850 mL, mean (336±246) mL. The acetabular abduction angle was (41.3±2.7)°. The acetabular anteversion angle was (16.4±3.4)°. The difference in lower limb length was (1.0±2.0) mm, and the femoral offset error value was (1.6±0.6) mm. Intraoperative femoral fractures occurred in one case. No infection, sciatic nerve injury or wound-related complications occurred. The weight bearing time was 3-6 weeks, mean (3.8±2.1) weeks. Harris score was (92.1±4.7) 3 months after surgery. It is indicated that the MAKO robot-assisted total hip arthroplasty via posterolateral approach showed that patient’s postoperative pain improved; the function recovered quickly; the clinical results were good; the operation time decreased with the proficiency; the prosthesis position was within the safe range; and the blood loss was within the acceptable range.

Key words: hip joint, joint replacement, MAKO robot, posterolateral approach, learning curve, prosthesis, visualization, navigation

中图分类号: