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KMID : 1144520200320010063
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Knee Surgery & Related Research
2020 Volume.32 No. 1 p.63 ~ p.63
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Demographic data is more predictive of component size than digital radiographic templating in total knee arthroplasty
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Wallace Stephen J.
Murphy Michael P.
Schiffman Corey J.
Hopkinson William J.
Brown Nicholas M.
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Abstract
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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?
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.
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KEYWORD
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Total knee arthroplasty, Multivariate linear regression, Demographic data, Predicting implant size
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