Internal rotational patellar resection and patella alta induced patellar maltracking in total knee arthroplasty: intraoperative measurement of the patellofemoral pressure.

Sanshiro Yasuma, Sakurako Kato, Takuya Usami, Yusuke Hattori, Yuji Joyo, Hiroo Shiraga, Masahiro Nozaki, Hideki Murakami, Yuko Waguri-Nagaya
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Abstract

Background: Anterior knee pain due to patellar maltracking following total knee arthroplasty (TKA) reduces patients' satisfaction. This study aimed to determine the patellofemoral pressure (PFP) in patients with favorable patellar tracking (FT) and impaired patellar tracking (IT) following TKA, the factors causing patellar maltracking, and the effect of lateral retinacular release (LRR) on patients with IT.

Methods: Forty-four patients with varus knee osteoarthritis undergoing cruciate-retaining TKA were enrolled. After component implantation, patients with a separation of ≥ 2 mm of the patellar medial facet from the medial femoral trochlea throughout knee range of motion were classified into the IT group; meanwhile, the others were classified into the FT group. PFP was measured intraoperatively in three phases: (1) with the resurfaced patella (RP); (2) with the resurfaced patella and knee (RPK); and (3) when LRR was performed in IT (post-LRR). The PFPs at 0°, 90°, 120°, and 135° knee flexion were compared between FT and IT using the Mann-Whitney U test. Pairwise comparison of the PFP in IT between RPK and post-LRR was performed using the Wilcoxon signed-rank test. Correlations between PFP and pre- and postoperative radiographic parameters, such as hip-knee-ankle angle, lateral distal femoral angle, medial proximal tibial angle, anterior femoral offset, Insall-Salvati ratio (ISR), patellar tilt, and patellar resection angle (PRA), were evaluated using Spearman's rank correlation coefficients.

Results: High lateral PFP in the knee flexion position led to patellar maltracking. Patients with IT (n = 24) had higher lateral and lower medial PFP than did patients with FT (n = 20) at 90°, 120°, and 135° knee flexion in RP and RPK. LRR in IT reduced the lateral PFP in the knee flexion position. PRA and ISR were correlated with the lateral PFP at no less than 90° in RP and RPK.

Conclusions: This study demonstrated that internal rotational patellar resection, which resulted in a thick medial patellar remnant and a thin lateral counterpart, and patella alta were the causative factors of high lateral PFP, which induced patellar maltracking after TKA. Surgeons should avoid internal rotational patellar resection to achieve FT and perform LRR in patients with patellar maltracking.

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全膝关节置换术中的髌骨内旋切除术和髌骨上移诱发的髌骨追踪不良:术中髌股压力测量。
背景:全膝关节置换术(TKA)后因髌骨追踪不良引起的膝关节前部疼痛降低了患者的满意度。本研究旨在确定TKA术后髌骨跟踪良好(FT)和髌骨跟踪受损(IT)患者的髌股压力(PFP)、导致髌骨跟踪不良的因素以及外侧网膜松解术(LRR)对IT患者的影响:方法:44 名膝关节外翻骨关节炎患者接受了十字韧带固定 TKA。组件植入后,在整个膝关节活动范围内,髌骨内侧面与股骨内侧套骨分离≥2 mm的患者被分为IT组;其他患者被分为FT组。术中分三个阶段测量PFP:(1)髌骨复位时(RP);(2)髌骨和膝关节复位时(RPK);(3)在IT组进行LRR时(LRR后)。使用 Mann-Whitney U 检验比较了 FT 和 IT 在膝关节屈曲 0°、90°、120° 和 135°时的 PFP。采用 Wilcoxon 符号秩检验对 RPK 和 LRR 后 IT 的 PFP 进行配对比较。使用斯皮尔曼等级相关系数评估了PFP与髋膝踝角度、股骨外侧远端角度、胫骨内侧近端角度、股骨前偏移、Insall-Salvati比率(ISR)、髌骨倾斜度和髌骨切除角度(PRA)等术前和术后影像学参数之间的相关性:结果:膝关节屈曲位的外侧PFP过高会导致髌骨追踪不良。在 RP 和 RPK 膝关节屈曲 90°、120° 和 135°时,与 FT 患者(20 人)相比,IT 患者(24 人)的外侧 PFP 更高而内侧 PFP 更低。在膝关节屈曲位时,IT 的 LRR 降低了外侧 PFP。PRA和ISR与RP和RPK在不低于90°时的外侧PFP相关:本研究表明,内旋转髌骨切除术导致髌骨内侧残余较厚,而外侧残余较薄,髌骨alta是导致高外侧PFP的致病因素,从而诱发TKA术后的髌骨追踪不良。外科医生应避免内旋髌骨切除术以实现FT,并对髌骨追踪不良的患者实施LRR。
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来源期刊
CiteScore
6.50
自引率
0.00%
发文量
42
审稿时长
19 weeks
期刊最新文献
Comparison of different cementing techniques for cement penetration under tibial component in total knee arthroplasty: a retrospective observational study. Tryptophanyl tRNA synthetase is an alternative synovial biomarker for diagnosis of septic arthritis in knee joint. It is challenging to reproduce both anatomical and functional aspects of anterolateral reconstruction: postoperative 3D-CT analysis of the femoral tunnel position. Internal rotational patellar resection and patella alta induced patellar maltracking in total knee arthroplasty: intraoperative measurement of the patellofemoral pressure. Accurate, automated classification of radiographic knee osteoarthritis severity using a novel method of deep learning: Plug-in modules.
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