Which hip morphology measures and patient factors are associated with age of onset and symptom severity in femoroacetabular impingement syndrome?

Abstract

Background: Bony morphology is central to the pathomechanism of femoroacetabular impingement syndrome (FAIS), however isolated radiographic measures poorly predict symptom onset and severity. More comprehensive morphology measurement considered together with patient factors may better predict symptom presentation. This study aimed to determine the morphological parameter(s) and patient factor(s) associated with symptom age of onset and severity in FAIS. Methods: 99 participants (age 32.9 ± 10.5 years; body mass index (BMI 24.3 ± 3.1 kg/m2; 42% females) diagnosed with FAIS received standardised plain radiographs and magnetic resonance scans. Alpha angle in four radial planes (superior to anterior), acetabular version (AV), femoral torsion, lateral centre-edge, anterior centre-edge (ACEA) and femoral neck-shaft angles were measured. Age of symptom onset (age at presentation minus duration of symptoms), international Hip Outcome Tool-33 (iHOT-33) and modified UCLA activity scores were recorded. Backward stepwise regression assessed morphological parameters and patient factors (age, sex, BMI, symptom duration, annual income, private/public healthcare system accessed) to determine variables independently associated with onset age and iHOT-33 score. Results: Earlier symptom onset was associated with larger superoanterior alpha angle ( p = 0.007), smaller AV ( p = 0.023), lower BMI ( p = 0.010) and public healthcare system access ( p = 0.041) (r2 = 0.320). Worse iHOT-33 score was associated with smaller ACEA ( p = 0.034), female sex ( p = 0.040), worse modified UCLA activity score ( p = 0.010) and public healthcare system access ( p < 0.001) (r2 = 0.340). Conclusions: Age of symptom onset was chiefly predicted by femoral and acetabular bony morphology measures, whereas symptom severity predominantly by patient factors. Factors measured explained a small amount of variance in the data; additional unmeasured factors may be more influential.