Articles | Volume 9, issue 5
https://doi.org/10.5194/jbji-9-231-2024
https://doi.org/10.5194/jbji-9-231-2024
Original full-length article
 | 
25 Oct 2024
Original full-length article |  | 25 Oct 2024

Predicting periprosthetic joint infection: external validation of preoperative prediction models

Seung-Jae Yoon, Paul C. Jutte, Alex Soriano, Ricardo Sousa, Wierd P. Zijlstra, and Marjan Wouthuyzen-Bakker

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Cited articles

Bilimoria, K. Y., Liu, Y., Paruch, J. L., Zhou, L., Kmiecik, T. E., Ko, C. Y., and Cohen, M. E.: Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons, J. Am. Coll. Surg., 217, 833–842e3, https://doi.org/10.1016/j.jamcollsurg.2013.07.385, 2013. 
Bourne, R. B., Maloney, W. J., and Wright, J. G.: An AOA critical issue. The outcome of the outcomes movement, J. Bone Joint Surg. Am., 86, 633–640, https://doi.org/10.2106/00004623-200403000-00026, 2004. 
Bülow, E., Hahn, U., Andersen, I. T., Rolfson, O., Pedersen, A. B., and Hailer, N. P.: Prediction of early periprosthetic joint infection after total hip arthroplasty, Clin. Epidemiol., 14, 239–253, https://doi.org/10.2147/CLEP.S347968, 2022. 
Cahill, J. L., Shadbolt, B., Scarvell, J. M., and Smith, P. N.: Quality of life after infection in total joint replacement, J. Orthop. Surg. (Hong Kong), 16, 58–65, https://doi.org/10.1177/230949900801600115, 2008. 
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Short summary
This study validated three models for predicting infection after hip and knee replacement surgery. By analyzing data from 2684 patients in the Netherlands, Portugal, and Spain, we found that the models developed by Tan, Del Toro, and Bülow effectively identified high-risk patients. These models can be used to enhance preoperative counseling and to tailor infection prevention measures individually, potentially improving outcomes and reducing healthcare costs.