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General Orthopaedics

IMPROVED POSTOPERATIVE CLINICAL OUTCOME OF TOTAL HIP ARTHROPLASTY IS RELATED TO PATIENTS’ PREOPERATIVE EXPECTATIONS

International Society for Technology in Arthroplasty (ISTA) 31st Annual Congress, London, England, October 2018. Part 1.



Abstract

Introduction

A variety of patient reported outcome (PRO) surveys have been established and validated to evaluate the effectiveness of surgical interventions. The Hip Disability and Osteoarthritis Outcome Score (HOOS) has been validated as one method to evaluate the effectiveness of total hip arthroplasty patients and facilitates the assessment of factors that alter patient outcomes in hip arthroplasty. This retrospective study assesses the effect of psychological post-operative expectations on HOOS in total hip arthroplasty patients. In this pilot study, patient data was collected for 499 patients using the AAOS established Musculoskeletal Outcomes Data Evaluation and Management System (MODEMS) [1] and HOOS surveys.

Method

Patient data was matched using similar preoperative HOOS scores to allow for comparable room for improvement in HOOS score postoperatively. Patients were placed into groups of high performers and low performers. HOOS is based on a 0 to 100 scale, 100 as the best possible outcome. High performers were defined as those with a HOOS growth ratio of 0.8 and above with the best performers reaching a ratio of 1. Low performers were defined as those with the aforementioned ratio below a value of 0.3. Using these defined groups, we were able to compare the summation of patient specific MODEMS scores using univariate regression. The HOOS growth ratio is calculated based on the following:

HOOS growth ratio = (HOOS postop – HOOS preop)/(100-HOOS preop)

Principal component analysis (PCA) was conducted to identify the significant group of factors that could identify changes in the outcome of 41 patients (20 low performers and 21 high performers).

Results and analysis

PCA was conducted on 5 items with orthogonal rotation (varimax). The Kaiser–Meyer–Olkin measure verified the sampling adequacy for the analysis, KMO = .0.688, which is well above the acceptable limit of .5 (Field, 2009). Two components had eigenvalues over Kaiser's criterion of 1 and in combination explained 74.49% of the variance (see Fig. 1). The Scree plot demonstrated the two components that were retained in the final analysis. Component 1 represents expected outcome measured on household activity, sleep comfort, and expected relief; the second component consisted of expected outcome based on recreation activity and expected time to return to job. The outcome of the logistic regression model indicated that the factors in the first component group could significantly identify the performance of patients after surgery.

Conclusions

In this study, we used the MODEMS questionnaire to find the postoperative performance outcome of patients with THA. MODEMS has shown potential in identifying high and low performance individuals; however, the major component in this questionnaire was expected outcome measured on household activity, sleep comfort, and expected relief.


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