Evidence map›Paper›PMID 42319472›Full record

ArticleNeurosurgical review2026

Nomogram prediction model for pain recurrence in patients with trigeminal neuralgia after microvascular decompression.

Tao Sun, Longshuang He, Qinghao Huang, Wentao Wang, Ning Li, Yunpeng Chen, Jinlong Liu, Chao Yang

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Article in Neurosurgical review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Tao SunDepartment of Neurosurgery, First Affiliated Hospital of Sun Yat-Sen University, No 58th, Zhongshan Er Road, Yuexiu District, Guangzhou, 510080, China.
Longshuang HeDepartment of Neurosurgery, First Affiliated Hospital of Guangdong Pharmaceutical University, No 19th, Nonglinxia Road, Yuexiu District, Guangzhou, 510080, China.
Qinghao HuangDepartment of Neurosurgery, First Affiliated Hospital of Sun Yat-Sen University, No 58th, Zhongshan Er Road, Yuexiu District, Guangzhou, 510080, China.
Wentao WangDepartment of Neurosurgery, First Affiliated Hospital of Guangdong Pharmaceutical University, No 19th, Nonglinxia Road, Yuexiu District, Guangzhou, 510080, China.
Ning LiDepartment of Neurosurgery, First Affiliated Hospital of Sun Yat-Sen University, No 58th, Zhongshan Er Road, Yuexiu District, Guangzhou, 510080, China.
Yunpeng ChenDepartment of Neurosurgery, Guangxi Hospital Division of The First Affiliated Hospital, Sun Yat-sen University, No 3rd Fozi Ling Road, Qingxiu District, Nanning, 530022, China.
Jinlong LiuDepartment of Neurosurgery, First Affiliated Hospital of Sun Yat-Sen University, No 58th, Zhongshan Er Road, Yuexiu District, Guangzhou, 510080, China.
Chao YangDepartment of Neurosurgery, First Affiliated Hospital of Sun Yat-Sen University, No 58th, Zhongshan Er Road, Yuexiu District, Guangzhou, 510080, China. ychao@mail.sysu.edu.cn.

Funding

Guangxi Key Research and Development Program GuikeAB24010092Guangxi Medical and Health Appropriate Technology Development and Promotion and Application Project S2023002
6 · The paper itself

Abstract

Microvascular decompression (MVD) is the first-line surgical treatment for trigeminal neuralgia (TN). However, some patients experience recurrence despite achieving immediate pain relief after MVD. This study aimed to identify the risk factors for TN recurrence and to develop a predictive nomogram model. We enrolled patients with TN who achieved immediate pain relief after MVD with at least 2 years of follow-up. Logistic regression analysis was used to explore the risk factors of long-term pain recurrence, based on the results of multivariate logistic regression analysis, a nomogram model for predicting pain recurrence was developed. Receiver operating characteristic curve (ROC) was used to analyze the prediction efficiency of the nomogram model, and calibration curve was used to analyze the accuracy of the nomogram model. Eventually, 264 patients were included in this study, during a mean follow-up of 43.06 ± 16.99 months, 23 patients experienced pain recurrence. Regression analysis suggested that younger age, longer pain duration, and atypical pain were the independent risk factors for long-term pain recurrence. The nomogram demonstrated excellent discriminatory power, with an area under the curve (AUC) of 0.958. The calibration curve analysis indicated good agreement between the predicted and observed probabilities. Favorable long-term outcomes could be achieved in TN patients with immediate pain relief after MVD, patients with younger age, longer pain duration and atypical pain may be at higher risk for pain recurrence.

Indexed as

Microvascular Decompression SurgeryNomogramsTrigeminal NeuralgiaAgedFemaleFollow-Up StudiesHumansMaleMiddle AgedRecurrenceRisk FactorsROC CurveTreatment OutcomeMicrovascular decompressionNomogram modelPain recurrenceRisk factorTrigeminal neuralgia

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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.