Developing a blueprint to optimize surgical instrument sets for primary total knee arthroplasty using data from the Dutch Arthroplasty Register, contributing to the reduction of the orthopaedic carbon footprint.
Approval date: December 2024
Starting date: February 6th 2025
PW van Egmond, P Lodder, J van Egmond
Research proposal abstract
We will conduct a retrospective study using data from primary total and partial knee arthroplasties recorded in the Dutch Arthroplasty Register between January 2019 and January 2024. Patient anthropometric data (height, weight, BMI, and sex) will be combined with implant-specific information (brand, procedure date, type, and implant sizes) to build a prediction model to predict implant size for the most commonly used knee implants in the Netherlands.
Additionally, we will demonstrate a prospective example showing how this data can reduce the number of surgical trays needed at the chief investigator's institution. By utilizing prediction models and frequency data, we aim to streamline surgical tray configurations without compromising intra-operative options. Rather than predicting exact sizes, we will focus on optimizing size ranges within trays. Moreover, as shoe size is known to correlate strongly with implant size, we will explore its potential value in a prediction model, although it is currently not collected by any Arthroplasty Register. Retrospective data will be used to evaluate whether including shoe size could further reduce the number of surgical trays.
The developed prediction models and the method for optimizing surgical trays will be made freely accessible to the Dutch orthopaedic community to support broader implementation.