Integrating core muscle morphology into a predictive model for residual back pain after vertebral augmentation.

BACKGROUND

Residual back pain (RBP) after percutaneous vertebral augmentation (PVA) for osteoporotic vertebral compression fractures (OVCF) remains a significant clinical challenge. Traditional prediction models focus primarily on bone mineral density and procedural factors. This study aimed to develop and validate a novel nomogram that incorporates the morphology of core muscles, notably the gluteal muscles, for personalized RBP risk stratification.

METHODS

In this retrospective study, clinical data from 428 OVCF patients who underwent PVA at two centers were analyzed. Patients were randomly divided into training and validation cohorts (3:1 ratio). Variables included demographics, fracture characteristics, procedural details, and computed tomography-based measurements of the relative cross-sectional area (rCSA) of paravertebral (multifidus, erector spinae, psoas) and pelvic [gluteus maximus (Gmax), gluteus medius (Gmed)] muscles. Least absolute shrinkage and selection operator and multivariate logistic regression were used to select predictors and build a nomogram. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis.

RESULTS

The overall incidence of RBP was 17.5%. The final model identified eight independent predictors. Alongside established factors like greater fracture burden and lower cement volume, reduced rCSA of the Gmax and Gmed emerged as significant and strong risk factors (p = 0.012 and p < 0.001, respectively). The nomogram demonstrated excellent discrimination in the training cohort (AUC = 0.883) and good generalizability in the validation cohort (AUC=0.695). Calibration and decision curve analysis confirmed its clinical utility.

CONCLUSIONS

This study presents a practical nomogram that effectively predicts RBP risk after PVA by integrating core muscle morphology, particularly of the gluteal muscles, with conventional clinical variables. The strong association of gluteal muscle size with pain outcomes underscores the importance of a holistic muscle-bone health assessment. This tool aids in preoperative risk stratification, potentially guiding targeted prehabilitation to improve patient outcomes.