Analysis of related factors affecting the postoperative clinical outcome of cervical ossification of the posterior longitudinal ligament.

Purpose: To establish a risk prediction model for postoperative outcomes in patients with ossification of the posterior longitudinal ligament (OPLL), identify key risk factors, and provide a theoretical basis for personalized treatment.

Methods: Clinical data of 384 OPLL patients undergoing cervical spine surgery were retrospectively analyzed. Potential predictors were screened using univariate analysis, and independent risk factors were determined through multivariate logistic regression. A dynamic nomogram was constructed, and its performance was evaluated with the concordance index (C-index), receiver operating characteristic (ROC) curve, Hosmer-Lemeshow test, and decision curve analysis (DCA).

Results: Four independent risk factors were identified and incorporated into the prediction model. The model demonstrated high accuracy and stability, with C-index values of 0.880 (training cohort) and 0.915 (validation cohort). ROC curve analysis confirmed excellent discrimination, while calibration and DCA showed good clinical applicability.

Conclusion: Advanced age, history of trauma, surgical approach, and spinal cord T2 hyperintensity on imaging are independent predictors of postoperative outcomes in OPLL patients. The developed nomogram provides a reliable tool for individualized risk assessment and clinical decision-making. These findings warrant further validation in multicenter cohorts.