Construction of prediction models for prolonged length of postoperative hospital stay in patients undergoing primary total hip arthroplasty via direct anterior approach

BMI, operation time, ASA classification, postoperative extra opioid use, PONV, postoperative transfusion, preoperative ALB, and previous contralateral THA history can be used as predictive factors. The LASSO regression-based model for predicting prolonged hospital stay after primary DAA-THA demonstrates accurate predictive performance and strong clinical utility. It can assist clinicians in stratifying patient risk effectively, thereby supporting enhanced recovery protocols.