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Updated: Jul 5, 2025

Microvascular Decompression: Salient Surgical Principles and Technical Nuances
Published on: July 5, 2011
A nomogram based on clinical multivariate factors predicts delayed cure after microvascular decompression for
Keyu Chen1, Lei Shen1, Jingyi Yang1
1Department of Neurosurgery, Wuhan University Zhongnan Hospital, Wuhan, 430071, China.
Background:
The course of disease after microvascular decompression (MVD) in patients with hemifacial spasm (HFS) is variable. The purpose of this study was to develop and validate a nomogram to predict the probability of delayed cure after microvascular decompression in patients with hemifacial spasms based on clinical multivariate factors.
Methods:
A retrospective data collection was performed on 290 patients with HFS undergoing MVD at our center from January 2017 to January 2022. The patients were randomly assigned to the training cohort (n = 232) and validation cohort (n = 58) at a ratio of 8:2. Retrospective analysis was performed of information on clinical, radiological, and intraoperative findings and clinical outcomes. Univariate and multivariate analyses were performed in the training cohort, and a nomogram was constructed using a stepwise logistic regression approach. The receiver operating characteristic (ROC) was calculated to evaluate the reliability of the nomogram model. Decision curve analysis (DCA) was used to assess the clinical application value of the nomogram model.
Results:
In the training cohorts, 73 patients (73/232) had a delayed cure. In the validation cohorts, 18 patients (18/58) had a delayed cure. We developed a novel nomogram model to predict the risk of delayed cure after MVD in HFS patients based on the presence of vertebral artery compression, venous compression, absence of LSR, degree of facial nerve indentation, degree of neurovascular compression, and internal auditory canal vascular looThe area under the curve (AUC) of the nomogram model was 0.9483 in the training cohort and 0.9382 in the validation cohort. The calibration curve showed good correspondence between the predicted and actual probabilities in the training and validation groups. The decision curve showed that the nomogram model had good performance in clinical applications.
Conclusions:
We developed and validated a preoperative and intraoperative multivariate factors nomogram to predict the possibility of delayed cure after MVD in HFS patients, which may help clinicians in the comprehensive management of HFS.
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