Development and validation of a prediction model for vertebral recompression and adjacent vertebral fracture after kyphoplasty in geriatric patients.

PURPOSE

Short-term efficacy of percutaneous kyphoplasty (PKP) for treating osteoporotic vertebral compression fracture (OVCF) in elderly patients is good, but long-term complications such as vertebral recompression (VRC) and adjacent vertebral fracture (AVF) may arise. Identifying risk factors in patients with poor prognoses, we developed a nomogram model to mitigate these potential complications.

METHODS

Patients with OVCFs who underwent PKP had their medical data retrospectively evaluated. Analysis of the sample included their pre- and postoperative conditions. Stepwise logistic regression analyses were conducted to identify independent risk factors for postoperative complications. For forecasting the likelihood of postoperative comorbidities, we offered a nomogram. The prognostic performance was assessed using the receiver operating characteristic curve (ROC), calibration curve, and decision curve analyses (DCA). Internal model validation using the Bootstrap method.

RESULTS

A total of 235 patients were included in this study. Among them, 147 patients were utilized to develop nomograms and for internal validation, while the remaining 88 patients from a different time period were designated as the external validation cohort. The results of stepwise logistic regression analysis showed that thoracolumbar (TL) fracture, posterior wall of vertebral fracture, vertebral compression > 30%, and lack of continuous anti-osteoporosis therapy after surgery as independent risks associated with poor prognosis. The nomogram exhibited outstanding predictive accuracy and clinical utility.

CONCLUSIONS

This study identified four independent predictors of poor prognosis following PKP and devised a straightforward yet efficient predictive model. This model offers valuable insights for guiding clinical decision-making in the management of elderly patients with OVCFs.