PT  - JOURNAL ARTICLE
AU  - Slaven, Emily J.
TI  - Prediction of Functional Outcome at Six Months Following Total Hip Arthroplasty
AID  - 10.demo/ptj.20110484
DP  - 2012 Nov 01
TA  - Demo Journal of Physical Therapy
PG  - 1386--1394
VI  - 92
IP  - 11
4099  - http://demo.highwire.org/content/92/11/1386.short
4100  - http://demo.highwire.org/content/92/11/1386.full
AB  - Background Recovery of function such as the ability to walk without an assistive device after total hip arthroplasty (THA) is not always automatic.Objective This study investigated whether predetermined variables could be used to identify patients who might have functional limitations at 6 months following THA.Design A prospective, observational cohort design was used.Method Demographics and baseline measures, including age, sex, and preoperative Lower Extremity Functional Scale (LEFS) score, were collected 1 to 3 weeks prior to surgery from 40 participants who were scheduled to undergo THA. Six weeks after surgery, a second LEFS score was recorded along with each participant's body mass index and the THA procedure performed; walking speed and balance also were assessed at this time using the 10-Meter Walk Test, the Timed “Up & Go” Test, and the Functional Reach Test. At 6 months following surgery, each participant's functional outcome was determined from the final LEFS score and the need for an assistive device. Classification and regression tree (CART) analyses and logistic regression were used to establish which of the variables could predict outcome at 6 months.Results Body mass index, sex, and age were identified by CART analysis as predictors to classify participants who did not reach successful outcome status. Logistic regression revealed that sex (female) was the only individual variable that predicted outcome at 6 months. Walking speed was the only performance variable identified as a predictor for outcome using CART analysis.Limitations Only a limited number of variables were observed due to the small sample size.Conclusion It is possible to identify those patients who are at risk for an unsuccessful outcome through the use of variables such as body mass index, age, and sex.