Total volume of cam deformity alone predicts outcome in arthroscopy for femoroacetabular impingement

Purpose Rates for arthroscopic surgery for femoroacetabular impingement (FAI) are rising and there is growing concern related to the effectiveness and costs associated with this treatment. There is a general lack of consensus as to the criteria for surgical selection of patients. The purpose of this study was to determine whether patient outcome following arthroscopic surgery for FAI could be predicted based on the size and location of deformity. The specific questions were: (1) what is the morphology of FAI in terms of size and location of deformity in a cohort of patients selected for surgery? (2) Do morphological factors predict postoperative improvement in hip scores? (3) Do morphological factors predict preoperative hip scores? (4) Are there clusters of morphological factors which explain postsurgical improvement in hip scores? Materials and methods Computer tomography (CT) surgical plans of 90 hips in 79 patients who had undergone primary hip arthroscopy for FAI were retrospectively reviewed. Four parameters for the femur and acetabulum were created: total depth of deformity, maximal depth, extent and the position of maximal deformity. This data were compared with prospectively acquired preoperative and postoperative patient outcome data using generalised linear models. Results The cohort comprised 33 males and 46 females aged 37.9 (18-61). The majority (74%) had mixed morphology, 23% isolated cam, and 3% isolated pincer. Overall, the bone depth was greatest and more extensive on the femur. Increased total additional cam deformity alone predicted poorer postoperative outcome (p = 0.045). None of the morphological factors were related to preoperative scores and there was no association between the meta-variables and postoperative outcome. Conclusions The results of this study indicate that a greater total volume of cam deformity led to poorer postoperative patient outcome scores at 1 year. This information provides the surgeon with more accurate patient-specific data for prediction of expected outcomes.