Abstract

We aimed to develop a predictive model for non-satisfaction following primary total knee replacement (TKR) and to assess its transportability to another health care system. Data for model development were obtained from two UK tertiary hospitals. Model transportation data were collected from Geneva University Hospitals in Switzerland. Participants were individuals undergoing primary TKR with non-satisfaction with surgery after one year the outcome of interest. Multiple imputation and logistic regression modelling with bootstrap backward selection were used to identify predictors of outcome. Model performance was assessed by discrimination and calibration. 64 (14.2%) patients in the UK and 157 (19.9%) in Geneva were non-satisfied with their TKR. Predictors in the UK cohort were worse pre-operative pain and function, current smoking, treatment for anxiety and not having been treated with injected corticosteroids (corrected AUC = 0.65). Transportation to the Geneva cohort showed an AUC of 0.55. Importantly, two UK predictors (treated for anxiety, injected corticosteroids) were not predictive in Geneva. A better model fit was obtained when coefficients were re-estimated in the Geneva sample (AUC = 0.64). The model did not perform well when transported to a different country, but improved when it was re-estimated. This emphasises the need to re-validate the model for each setting/country.

Highlights

  • Predicting outcomes for chronic disease management represents an important challenge to modern day health systems

  • Patient satisfaction after total knee replacement (TKR) correlates with failure of surgery, and non-satisfaction has been related to poorer outcomes after knee replacement[2]

  • Additional complexity arises when satisfaction is compared between different settings, which do not serve the same profile of patients

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Summary

Introduction

Predicting outcomes for chronic disease management represents an important challenge to modern day health systems. Additional complexity arises when satisfaction is compared between different settings (health care systems), which do not serve the same profile of patients. There are several published studies predicting satisfaction after TKR, often with internal validation[4], they have not addressed the important issue of transportability[5,6] of the model, i.e. the ability of the model to function in other countries with a different health care system and/or population[7]. This important step is required to www.nature.com/scientificreports/. The aim of this study was to develop, validate and assess the transportability of a predictive model for non-satisfaction after primary TKR based on pre-operative factors and surgeon experience

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