Can Demographic Variables Accurately Predict Component Sizing in Primary Total Knee Arthroplasty? Robert A. Sershon, MD a, * , Paul Maxwell Courtney, MD a , Brett D. Rosenthal, MD b , Scott M. Sporer, MD a , Brett R. Levine, MD a a Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois b Northwestern University, Chicago, Illinois article info Article history: Received 21 November 2016 Received in revised form 12 April 2017 Accepted 1 May 2017 Available online xxx Keywords: primary total knee arthroplasty templating demographics preoperative planning electronic application abstract Background: As health care reform drives providers to reduce costs and improve efficiencies without compromising patient care, preoperative planning has become imperative. The purpose of this study is to determine whether height, weight, and gender can accurately predict total knee arthroplasty (TKA) sizing. Methods: A consecutive series of 3491 primary TKAs performed by 2 surgeons was reviewed. Height, weight, gender, implant, preoperative templating sizes, and final implant sizes were collected. Implant- specific dimensions were collected from vendors. Using height, weight, and gender, a multivariate linear regression was performed with and without the inclusion of preoperative templating. Accuracy of the model was reported for commonly used implants. Results: There was a significant linear correlation between height, weight, and gender for femoral (R 2 ¼ 0.504; P < .001) and tibial sizes (R 2 ¼ 0.610; P < .001). Adding preoperative templating to the regression analysis increased the overall model fit for both the femoral (R 2 ¼ 0.756; P < .001) and tibial sizes (R 2 ¼ 0.780; P < .001). Femoral and tibial sizes were accurately predicted within 1 size of the final implant 71%-92% and 81%-97% using demographics alone or 85%-99% and 90%-99% using both templating and demographics, respectively. Conclusion: This novel TKA templating model allows final implants to be predicted to within 1 size. The model allows for simplified preoperative planning and potential implementation into a cost-savings program that limits inventory and trays required for each case. © 2017 Elsevier Inc. All rights reserved. Preoperative templating in total knee arthroplasty (TKA) pro- vides surgeons the ability to anticipate final implant size and pre- pare for potential intraoperative difficulties or roadblocks that may occur along the way, such as severe deformity correction and the need for special equipment or nonstandard implants [1e3]. Accu- rate templating has become essential for surgical planning, partic- ularly in community or outpatient settings where resources are more limited. Inaccurate or poor preoperative planning may result in the absence of the most appropriate implant for the patient at the time of surgery. This carries substantial morbidity and economic burden, and minimizing such scenarios is essential [4,5]. As we enter the new era of value-based health care, delivery of patient care in an accurate and affordable manner will prove paramount [6,7]. Traditional templating methods have demon- strated variable degrees of accuracy in regard to predicting final implant size and re-establishing coronal alignment, resulting in a push toward more reliable but potentially more costly and time-involved patient-specific instrumentation (PSI) [8e12]. The variability of standard templating and cost associated with preop- erative computed tomography/magnetic resonance imaging in PSI has left surgeons to seek an accurate, time-efficient, and cost- effective method of templating in TKA. Whether component sizes can be predicted preoperatively by demographic variables alone has yet to be addressed in the literature. We propose a novel method of templating in TKA based on a formula utilizing patient height, weight, and gender. The purpose of One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to http://dx.doi.org/10.1016/j.arth.2017.05.007 . * Reprint requests: Robert A. Sershon, MD, Department of Orthopaedic Surgery, Rush University Medical Center, 1611 West Harrison Street, Suite 300, Chicago, IL 60612. Contents lists available at ScienceDirect The Journal of Arthroplasty journal homepage: www.arthroplastyjournal.org http://dx.doi.org/10.1016/j.arth.2017.05.007 0883-5403/© 2017 Elsevier Inc. All rights reserved. The Journal of Arthroplasty xxx (2017) 1e5