ArticleRisk management and healthcare policy2025
A Nomogram Model Integrating Inflammation Markers for Predicting the Risk of Recurrent Sciatica After Selective Nerve Root Blocks.
Article in Risk management and healthcare policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Differentiating Sciatica from Hip Osteoarthritis: Diagnostic Challenges and the Role of the Athena Sign.Diagnostics (Basel, Switzerland) · 2026Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: 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 patients after SNRB remains a major challenge. Objective: We aimed to construct a nomogram model by integrating clinical data, imaging features and inflammation markers that could predict recurrent sciatica following SNRB in LDH patients, which fill the inflammation data gaps during model construction. Methods: In total, 121 sciatica patients were enrolled and assigned to the recurrence group (n = 41) and non-recurrence group (n = 80). By performing the logistic regression analyses, we identified risk factors serving as independent predictors and constructed the nomogram prediction model. Then, the performance and clinical practicality of the nomogram model were validated by performing the receiver operating characteristic curve (ROC) analysis, calibration curve analysis, and decision curve analysis (DCA). The bootstrap method was applied for the internal validation of the nomogram model. Results: Preoperative sensory symptoms (odds ratio [OR] [95% confidence interval (CI)]: 2.933 [1.211-7.353]), type of herniation (OR [95% CI]: 2.712 [1.261-6.109]), and systemic inflammation response index (OR [95% CI]: 2.447 [1.065-6.271]) were included in the nomogram for predicting unfavorable outcomes following sciatica. The nomogram AUC was 0.764, and the prognostic precision, validated using the bootstrap method, reached 0.756. The ROC and calibration curve analyses, and DCA also produced excellent results, exhibiting favorable predictive performance and clinical benefit. Conclusion: This study thus identified risk factors that predict unfavorable outcomes after sciatica and developed a risk prediction model based on clinical, radiologic, and inflammatory factors, thereby facilitating early predictions by clinicians and offering an individualized medical interventions for patients with recurrent sciatica in early stages.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.