Page 98 - The value of total hip and knee arthroplasties for patients

Chapter 6
Abstract
Background:
Previous studies have suggested there is an association between preoperative expectations about the outcome and outcomes of total knee and total hip arthroplasty (THA/TKA). However, expectations have been rarely examined on their clinical relevance relative to other well-known predictive factors. Furthermore expectations can be measured on a more generic level (eg: does one expect their symptoms to improve after surgery) or on a more specific level (eg. Does one expect to be able to squat again after surgery). Aim of this study was to examine whether patients’ general and specific preoperative outcome expectations predict function and pain 12-months after TKA/THA, when assessed as one of the candidate predictive variables alongside other relevant clinical and sociodemographic variables. Moreover, we explored whether a more generic or a more specific assessment of expectations would better predict outcome.
Methods:
A prospective cohort study on consecutive TKA/THA patients, with assessments done preoperatively and 12-months postoperative. Primary outcomes were the Knee injury and Osteoarthritis Outcome Score (KOOS) and Hip injury and Osteoarthritis Outcome Score (KOOS) activities of daily living (ADL) and pain subscale scores at 12-months.The pain subscales consist of 9-(KOOS) and 10-(HOOS) items and the ADL of 17 items. Patients’ preoperative outcome expectations were measured with the Credibility Expectancy Questionnaire (CEQ), which contains three items scored on a 0-9 scale and sum score 0-27 and the Hospital for Special Surgery expectations surveys (HSS expectation surveys) for 17 (TKA) or 18 (THA) outcomes on 0-4 scale. Other candidate predictors: preoperative pain and function as measured with HOOS/KOOS, sex, age, education level, Body Mass Index, Kellgren/Lawrence score, preoperative mental health and treatment credibility as measured with CEQ. Eight prediction models were constructed using multivariate linear regression analysis with a backward selection procedure.
96