Novel Classification System to Predict Case Difficulty in Direct Anterior Approach Total Hip Arthroplasty.

Abstract

Although the learning curve for direct anterior approach (DAA) total hip arthroplasty (THA) is steep, no classification exists to predict technically challenging cases. We propose and validate a new Davidovitch direct anterior (DDA) classification system for predicting DAA THA case complexity. We retrospectively reviewed primary DAA THAs by two fellowship-trained surgeons (October 2019 to June 2025). Exclusions included fracture, contralateral hardware, incomplete pelvis radiographs, or less than one year of follow-up. Cases were grouped into learning curve, proficient, and expert phases. Classification was based on preoperative antero-posterior pelvic radiographs. Operative time served as a proxy for case difficulty. Univariate and multivariate regressions assessed the effects of classification, surgeon experience, fixation method, and body mass index (BMI). Multivariate analyses of 283 cases, including DDA classification, surgeon experience, fixation method, and BMI, demonstrated that operative times were significantly longer for DDA 4 versus DDA 1 cases (P = 0.011). Operative time decreased across learning curve, proficient, and expert phases (P < 0.001). Higher BMI (P < 0.001) and cemented fixation (P = 0.004) independently increased operative time. There were 13 overall complications and two revision THAs within 90 days. This novel radiographic classification system predicted case difficulty in DAA THA, as DDA 4 cases took longer than DDA 1 cases, particularly during the learning curve. Beyond the learning curve, the impact of DDA classification on operative time diminished. This classification system has the potential to serve as a valuable preoperative tool for operative planning and workday efficiency, particularly for early career surgeons on their learning curve.