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.