A Nomogram Model Integrating Inflammation Markers for Predicting the Risk of Recurrent Sciatica After Selective Nerve Root Blocks

• DOI: 10.2147/rmhp.s503360
• Publication Date: 2025-04-11T13:55:11Z
• Authors: Meng Cai; Jing Yin; Yi Jin; HongJun Liu
• Keywords: Nomogram

Lumbar disc herniation (LDH) usually c auses sciatica. Although selective nerve root block (SNRB) is an effective, highly target-oriented interventional procedure for patients with LDH, accurately predicting the risk of sciatica recurrence in such after SNRB remains a major challenge. We aimed to construct nomogram model by integrating clinical data, imaging features and inflammation markers that could predict recurrent following LDH patients, which fill data gaps during construction. In total, 121 were enrolled assigned group (n = 41) non-recurrence 80). By performing logistic regression analyses, we identified factors serving as independent predictors constructed prediction model. Then, performance practicality validated receiver operating characteristic curve (ROC) analysis, calibration decision analysis (DCA). The bootstrap method was applied internal validation Preoperative sensory symptoms (odds ratio [OR] [95% confidence interval (CI)]: 2.933 [1.211-7.353]), type (OR CI]: 2.712 [1.261-6.109]), systemic response index 2.447 [1.065-6.271]) included unfavorable outcomes AUC 0.764, prognostic precision, using method, reached 0.756. ROC DCA also produced excellent results, exhibiting favorable predictive benefit. This study thus developed based on clinical, radiologic, inflammatory factors, thereby facilitating early predictions clinicians offering individualized medical interventions stages.