在全膝关节置换术中,人口统计学数据比数字x线摄影模板更能预测部件尺寸。

IF 4.1 Q1 ORTHOPEDICS
Stephen J Wallace, Michael P Murphy, Corey J Schiffman, William J Hopkinson, Nicholas M Brown
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引用次数: 12

摘要

背景:全膝关节置换术(TKA)的术前放射照相模板已被证明是不准确的。患者人口统计数据,如性别、身高、体重、年龄和种族,可能更能预测TKA中植入部件的大小。材料和方法:设计了一个多元线性回归模型,利用201例连续接受指数TKA的患者的人口统计学数据预测植入股骨和胫骨假体的大小。传统的二维放射学模板与基于人口统计学的回归预测在181例连续接受指数TKA的患者中准确预测术中植入物大小的能力进行了比较。外科医生对任何预测都一无所知。结果:患者的性别、身高、体重、年龄和种族/种族可预测植入TKA组件的大小。与放射学模板尺寸相比,回归模型更准确地预测股骨和胫骨植入物的尺寸(P = 0.04)。结论:基于患者特定的人口统计学数据,建立了基于人口统计学的回归模型来预测股骨和胫骨TKA植入物的尺寸。在前瞻性患者系列中,回归模型比放射学模板更准确和精确地预测植入部件的尺寸。证据级别:前瞻性队列,II级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Demographic data is more predictive of component size than digital radiographic templating in total knee arthroplasty.

Demographic data is more predictive of component size than digital radiographic templating in total knee arthroplasty.

Demographic data is more predictive of component size than digital radiographic templating in total knee arthroplasty.

Demographic data is more predictive of component size than digital radiographic templating in total knee arthroplasty.

Background: Preoperative radiographic templating for total knee arthroplasty (TKA) has been shown to be inaccurate. Patient demographic data, such as gender, height, weight, age, and race, may be more predictive of implanted component size in TKA.

Materials and methods: A multivariate linear regression model was designed to predict implanted femoral and tibial component size using demographic data along a consecutive series of 201 patients undergoing index TKA. Traditional, two-dimensional, radiographic templating was compared to demographic-based regression predictions on a prospective 181 consecutive patients undergoing index TKA in their ability to accurately predict intraoperative implanted sizes. Surgeons were blinded of any predictions.

Results: Patient gender, height, weight, age, and ethnicity/race were predictive of implanted TKA component size. The regression model more accurately predicted implanted component size compared to radiographically templated sizes for both the femoral (P = 0.04) and tibial (P < 0.01) components. The regression model exactly predicted femoral and tibial component sizes in 43.7 and 43.7% of cases, was within one size 90.1 and 95.6% of the time, and was within two sizes in every case. Radiographic templating exactly predicted 35.4 and 36.5% of cases, was within one size 86.2 and 85.1% of the time, and varied up to four sizes for both the femoral and tibial components. The regression model averaged within 0.66 and 0.61 sizes, versus 0.81 and 0.81 sizes for radiographic templating for femoral and tibial components.

Conclusions: A demographic-based regression model was created based on patient-specific demographic data to predict femoral and tibial TKA component sizes. In a prospective patient series, the regression model more accurately and precisely predicted implanted component sizes compared to radiographic templating.

Level of evidence: Prospective cohort, level II.

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