Can Component Size in Total Knee Arthroplasty Be Predicted Preoperatively?—An Analysis of Patient Characteristics

Abstract

Accurately predicting component sizing in total knee arthroplasty (TKA) can ensure appropriate implants are readily available, avoiding complications from malsizing while also reducing cost by improving workflow efficiency through a reduction in instrumentation. This study investigated the utility of demographic variables to reliably predict TKA component sizes. A retrospective chart review of 337 patients undergoing primary TKA was performed. Patient characteristics (age, sex, race, height, weight) were recorded along with implant and shoe size. Correlation between shoe size and TKA component size was assessed using Pearson's correlation coefficient and linear regression analysis using three models: (A) standard demographic variables, (B) shoe size, and (C) combination of both models. Shoe size demonstrated the strongest correlation with femoral anteroposterior (FAP) (p < 0.001) followed by height (p < 0.001). Conversely, height exhibited the strongest correlation with tibial mediolateral (TML) (p < 0.001) followed by shoe size (p < 0.001). Model C was able to correctly predict both the femur and tibia within one and two sizes in 83.09 and 98.14% of cases, respectively. Individually, model C predicted the FAP within one and two sizes in 83.09 and 96.14% of cases, and the TML in 98.81 and 100% of cases, respectively. A patient's shoe size demonstrates a strong correlation to the TKA implant size, and when combined with standard demographic variables the predictive reliability is further increased. Here, we present a predictive model for implant sizing based solely on easily attainable demographic variables, that will be useful for preoperative planning to improve surgical efficiency.

Level of Evidence II, Diagnostic.

Keywords

total knee arthroplasty - implant size - preoperative planning - anatomic fit

Publikationsverlauf

Eingereicht: 28. Oktober 2021

Angenommen: 18. März 2022

Artikel online veröffentlicht:
12. Juli 2022

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