A1141. PREDICTING SHORT TERM OUTCOME OF PRIMARY TOTAL HIP ARTHROPLASTY: A PROSPECTIVE MULTIVARIATE REGRESSION ANALYSIS OF 12 INDEPENDENT FACTORS

Abstract

Not all patients receive enhanced mobility and return to comfortable, independent living after Total Hip Arthroplasty (THA). It would be beneficial to both surgeons and patients to be able to predict short term outcomes for THA. The purpose of this study was to investigate factors affecting the short term outcome of primary THA and develop a multivariate regression model that can predict such outcomes.

This was a prospective study of 101 patients, who underwent primary THA. All patients were followed for a minimum of 1 year. 12 independent variables, including age, gender, diagnosis, presence of preoperative comorbidities, BMI, preoperative WOMAC physical component (PC) score, type of anesthesia, type of fixation, surgical time, estimated blood loss, use of a postoperative drain, and length of stay were analyzed using correlation and multivariate regression analyses. Multivariate regression models were validated using an independent cohort.

Correlation analyses showed three variables significantly influence short term THA outcome. These include preoperative WOMAC PC score (PC) (p< 0.01), gender (G) (p= 0.01) and the presence of preoperative comorbidities (CMB) (p= 0.02). By multivariate regression analysis, the following regression model was obtained: Outcome = PC*0.45 −G*9 + CMB*8 + 62.

This model exhibited positive correlation (R2=.25) when compared to a separate cohort of 27 patients undergoing THA not included in the original equation derivation.

Our multivariate regression analysis has yielded statistical, multivariate confirmation or non-confirmation of common, predictive THA factors that have previously been reported in the literature. This study provides a concrete, statistically significant measure indicating that preoperative WOMAC PC score, gender, and the presence of preoperative comorbidities are predictive factors for short term primary THA outcome. Finally, our multivariate regression equation can be used to predict the general short term patient outcome following primary THA.