Predictors of outcomes of total knee replacement surgery

Judge, Andy, Arden, Nigel K., Cooper, Cyrus, Javaid, M. Kassim, Carr, Andrew J., Field, Richard E. and Dieppe, Paul A. (2012) Predictors of outcomes of total knee replacement surgery. Rheumatology, 51 (10), 1804-1813. (doi:10.1093/rheumatology/kes075). (PMID:22532699)

Abstract

Objective: to identify pre-operative predictors of patient-reported outcomes of primary total knee replacement (TKR) surgery.

Methods: the Elective Orthopaedic Centre database is a large prospective cohort of 1991 patients receiving primary TKR in south-west London from 2005 to 2008. The primary outcome is the 6-month post-operative Oxford Knee Score (OKS). To classify whether patients had a clinically important outcome, we calculated a patient acceptable symptom state (PASS) for the 6-month OKS related to satisfaction with surgery. Potential predictor variables were pre-operative OKS, age, sex, BMI, deprivation, surgical side, diagnosis, operation type, American Society of Anesthesiologists grade and EQ5D anxiety/depression. Regression modelling was used to identify predictors of outcome.

Results: the strongest determinants of outcome include pre-operative pain/function—those with less severe pre-operative disease obtain the best outcomes; diagnosis in relation to pain outcome—patients with RA did better than those with OA; deprivation—those living in poorer areas had worse outcomes; and anxiety/depression—worse pre-operative anxiety/depression led to worse pain. Differences were observed between predictors of pain and functional outcomes. Diagnosis of RA and anxiety/depression were associated with pain, whereas age and gender were specifically associated with function. BMI was not a clinically important predictor of outcome.

Conclusion: this study identified clinically important predictors of attained pain/function post-TKR. Predictors of pain were not necessarily the same as functional outcomes, which may be important in the context of a patient’s expectations of surgery. Other predictive factors need to be identified to improve our ability to recognize patients at risk of poor TKR outcomes

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Contributors

Author: Cyrus Cooper

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