Abstract

Background: Developmental dysplasia of the hip can cause pain and premature osteoarthritis. The risk factors and timing for disease progression in adolescents and young adults has not been fully defined. This study aimed to determine the incidence and risk factors for contralateral hip pain and surgery after periacetabular osteotomy (PAO) on an index dysplastic hip.

Methods: Patients undergoing unilateral PAO were followed for at least two years and categorized into contralateral pain or no-pain groups and surgery or no-surgery groups. Pain was defined with the modified Harris Hip Score. Univariate analysis tested group differences in demographics, radiographic measures, and range-of-motion. Kaplan-Meier survival analysis assessed pain development and contralateral hip surgery over time. Multivariate regression identified risk factors of pain and surgery. Pain and surgery predictors were secondarily assessed in subcategories of Dysplastic, Borderline, and Non-dysplastic hips, and in five-degree increments of lateral center edge angle (LCEA) and acetabular inclination (AI).

Results: 184 patients were followed for 4.6±1.6 years [range 2.0-8.8], during which 51% (93/184) reported hip pain and 33% (60/184) underwent contralateral surgery. Kaplan-Meier analysis predicted 5-year survivorship of 49% for pain development and 66% for contralateral surgery. Painful hips exhibited more severe dysplasia compared to no-pain hips (LCEA 16.5º vs 20.3º, p<0.001; AI 13.2º vs 10.0º p<0.001). AI was the sole predictor of pain, with every 1° AI increase raising the risk by 11%. Surgical hips also had more severe dysplasia (LCEA 14.9º vs 20.0º, p<0.001; AI 14.7º vs 10.2º p<0.001) and were younger (21.6 vs 24.1 years, p=0.022). AI and a maximum alpha angle ≥55° were predictors of contralateral surgery.

Conclusions: At 5 years after index hip PAO, 51% of contralateral hips experience pain and 34% are expected to need surgery. More severe dysplasia, based on LCEA and AI, increases the risk of contralateral hip pain and surgery, with AI being a predictor of both outcomes. Knowing these risks can inform patient counseling and treatment planning.

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