Surgical indications for Bernese periacetabular osteotomy (PAO) are well-established. However, the extent of postoperative functional recovery varies widely, as observed in clinical follow-ups. Thus, preoperative evaluation is crucial. This study aims to identify factors that influence functional recovery post-PAO and to develop a predictive nomogram.
Retrospective data were collected between December 2016 and March 2022 at The First Affiliated Hospital of Shandong First Medical University. The dataset included demographic and imaging data of patients who underwent PAO. The least absolute shrinkage and selection operator (LASSO) regression was utilized to identify influencing factors, which were further analyzed using multivariate logistic regression to construct a predictive nomogram for post-PAO functional recovery.
The analysis identified critical factors affecting functional recovery post-PAO, namely, the preoperative distance from the innermost surface of the femoral head to the ilioischial line, the surgical approach, preoperative acetabular depth, and the continuity of the preoperative Calve line. A nomogram was developed using these significant predictors. The model's validity was demonstrated by the receiver operating characteristic curve, with an area under the curve of 0.864. Additionally, the calibration curve confirmed the nomogram's accuracy, showing a strong correlation between observed and predicted probabilities, indicating high predictive accuracy.
This predictive nomogram effectively identifies patients most suitable for PAO, providing valuable guidance for selecting surgical candidates and determining the appropriate surgical approach.