Add like
Add dislike
Add to saved papers

Using hierarchical linear modeling to explore predictors of pain after total hip and knee arthroplasty as a consequence of osteoarthritis.

Hierarchical linear modeling was used to establish differences in, and the average pattern of, recovery of the pain subscale of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and 2 composite performance-specific measures of pain as well as to determine if significant individual variations exist in the growth curves for each measure. Predictors of postoperative pain were also of interest. One hundred forty-seven patients undergoing unilateral primary hip or knee arthroplasty completed 4 performance measures-self-paced 40-m walk, timed up and go, stair test, and 6-minute walk-and the WOMAC prearthroplasty and at multiple points in time between 2 and 27 weeks postarthroplasty. Although patients reported different levels of postoperative pain initially, similar recovery patterns were noted. Predictive variables were found to be site of joint arthroplasty and WOMAC prearthroplasty pain scores for the WOMAC pain subscale, the site of joint arthroplasty and sex for the first composite pain score, and sex for the second composite.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app