Development of a model predicting non-satisfaction 1 year after primary total knee replacement in the UK and transportation to Switzerland

Development of a model predicting non-satisfaction 1 year after primary total knee replacement in... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Scientific Reports Springer Journals

Development of a model predicting non-satisfaction 1 year after primary total knee replacement in the UK and transportation to Switzerland

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Publisher
Nature Publishing Group UK
Copyright
Copyright © 2018 by The Author(s)
Subject
Science, Humanities and Social Sciences, multidisciplinary; Science, Humanities and Social Sciences, multidisciplinary; Science, multidisciplinary
eISSN
2045-2322
D.O.I.
10.1038/s41598-018-21713-2
Publisher site
See Article on Publisher Site

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.

Journal

Scientific ReportsSpringer Journals

Published: Feb 21, 2018

References

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