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

Area of Science:

• Orthopedic Surgery
• Surgical Technique Innovation

Background:

• Direct anterior approach (DAA) total hip arthroplasty (THA) presents a steep learning curve.
• A need exists for a classification system to predict challenging DAA THA cases.

Purpose of the Study:

• To propose and validate the Davidovitch direct anterior (DDA) classification system.
• To assess the DDA classification's ability to predict case complexity in DAA THA.

Main Methods:

• Retrospective review of 283 primary DAA THAs performed by fellowship-trained surgeons.
• Classification based on preoperative anteroposterior pelvis radiographs.
• Operative time used as a proxy for case difficulty, analyzed with multivariate regression.

Main Results:

• The DDA classification significantly impacted operative time, with DDA 4 cases taking longer than DDA 1 cases (P = 0.011).
• Operative times decreased across learning curve, proficient, and expert phases (P < 0.001).
• Higher BMI and cemented fixation independently increased operative time.

Conclusions:

• The novel DDA classification system effectively predicts DAA THA case difficulty, especially during the learning curve.
• The classification's impact on operative time diminishes beyond the initial learning phase.
• The DDA classification system offers potential as a preoperative tool for planning and efficiency, particularly for early-career surgeons.