计算机辅助全膝关节置换术：适合初学者还是专家？对不同经验水平的外科医生治疗的三组患者进行的前瞻性研究。
Is computer-assisted total knee replacement for beginners or experts? Prospective study among three groups of patients treated by surgeons with different levels of experience.
机构信息
Ist Orthopedic Department, C.T.O. Hospital, Via Bignami 1, 20100, Milan, Italy.
出版信息
J Orthop Traumatol. 2012 Dec;13(4):203-10. doi: 10.1007/s10195-012-0205-z. Epub 2012 Jul 18.
BACKGROUND
Computer-assisted total knee replacement (TKR) has been shown to improve radiographic alignment and therefore the clinical outcome. Outliers with greater than 3° of varus or valgus malalignment in TKR can suffer higher failure rates. The aim of this study was to determine the impact of experience with both computer navigation and knee replacement surgery on the frequency of errors in intraoperative bone cuts and implant alignment, as well as the actual learning curve.
MATERIALS AND METHODS
Three homogeneous groups who underwent computer-assisted TKR were included in the study: group A [surgery performed by a surgeon experienced in both TKR and computer-assisted surgery (CAS)], B [surgery performed by a surgeon experienced in TKR but not CAS], and C [surgery performed by a general orthopedic surgeon]. In other words, all of the surgeons had different levels of experience in TKR and CAS, and each group was treated by only one of the surgeons. Cutting errors, number of re-cuts, complications, and mean surgical times were recorded. Frontal femoral component angle, frontal tibial component angle, hip-knee-ankle angle, and component slopes were evaluated.
RESULTS
The number of cutting errors varied significantly: the lowest number was recorded for TKR performed by the surgeon with experience in CAS. Superior results were achieved in relation to final mechanical axis alignment by the surgeon experienced in CAS compared to the other surgeons. However, the total number of outliers showed no statistically significant difference among the three surgeons. After 11 cases, there were no differences in the number of re-cuts between groups A and C, and after 9 cases there were no differences in surgical time between groups A and B.
CONCLUSION
A beginner can reproduce the results of an expert TKR surgeon by means of navigation (i.e., CAS) after a learning curve of 16 cases; this represents the break-even point after which no statistically significant difference is observed between the expert surgeon and the beginner utilizing CAS.
背景
计算机辅助全膝关节置换术（TKR）已被证明可改善放射学对线，从而改善临床结果。TKR 中存在超过 3°的内翻或外翻对线不良的离群值的患者可能会遭受更高的失败率。本研究的目的是确定计算机导航和膝关节置换手术经验对术中骨切割和植入物对线误差的频率，以及实际学习曲线的影响。
材料和方法
本研究纳入了三组接受计算机辅助 TKR 的患者：A 组（由同时具有 TKR 和计算机辅助手术经验的外科医生进行手术）、B 组（由具有 TKR 经验但无计算机辅助手术经验的外科医生进行手术）和 C 组（由普通骨科医生进行手术）。换句话说，所有外科医生在 TKR 和计算机辅助手术方面的经验水平不同，每组手术都由其中一位外科医生进行。记录了切割误差、重新切割次数、并发症和平均手术时间。评估了股骨前组件角、胫骨前组件角、髋膝踝角和组件斜率。
结果
切割误差的数量差异显著：具有计算机辅助手术经验的外科医生进行的 TKR 记录的误差数量最低。具有计算机辅助手术经验的外科医生在最终机械轴对线方面取得了优于其他外科医生的结果。然而，三组外科医生的离群值总数没有统计学上的显著差异。A 组和 C 组在进行 11 例手术后，重新切割次数没有差异，A 组和 B 组在进行 9 例手术后，手术时间没有差异。
结论
初学者可以通过导航（即计算机辅助手术）在 16 例病例的学习曲线后复制专家 TKR 外科医生的结果；这是专家外科医生和初学者使用计算机辅助手术之间没有统计学差异的平衡点。
Zotero 插件