The value of radiographic features in predicting postoperative facial nerve function in vestibular schwannoma patients: A retrospective study and nomogram analysis

被引:1
作者
Shi, Xudong [1 ,2 ]
Liu, Yuyang [3 ]
Zhang, Zehan [4 ]
Tao, Bingyan [5 ]
Zhang, Ding [1 ,2 ]
Jiang, Qingyu [1 ,2 ]
Chen, Guilin [1 ,2 ]
Ma, Hengchao [1 ,2 ]
Feng, Yaping
Xie, Jiaxin [3 ]
Zheng, Xuan [1 ]
Zhang, Jun [1 ,6 ]
机构
[1] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 1, Dept Neurosurg, Beijing, Peoples R China
[2] Chinese PLA, Med Sch, Beijing, Peoples R China
[3] 920th Hosp Joint Logist Support Force, Dept Neurosurg, Kunming, Peoples R China
[4] Air Force Hosp Southern Theater Command, Dept Neurosurg, Guangzhou, Peoples R China
[5] 961th Hosp Joint Logist Support Force, Dept Neurosurg, Qiqihar, Peoples R China
[6] Chinese Peoples Liberat Army Gen Hosp, Dept Neurosurg, 28 Fuxing Rd, Beijing 100853, Peoples R China
关键词
facial paralysis; nomogram; predict; vestibular schwannoma; FUNDAL FLUID CAP; RADIOSURGICAL TREATMENT; HEARING PRESERVATION; BRAIN; INTERFACE;
D O I
10.1111/cns.14526
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Objective: The purpose of this study was to identify significant prognostic factors associated with facial paralysis after vestibular schwannoma (VS) surgery and develop a novel nomogram for predicting facial nerve (FN) outcomes.Methods: Retrospective data were retrieved from 355 patients who underwent microsurgery via the retrosigmoid approach for VS between December 2017 and December 2022. Univariate and multivariate logistic regression analysis were used to construct a radiographic features-based nomogram to predict the risk of facial paralysis after surgery.Results: Following a thorough screening process, a total of 185 participants were included. The univariate and multivariate logistic regression analysis revealed that tumor size (p = 0.005), fundal fluid cap (FFC) sign (p = 0.014), cerebrospinal fluid cleft (CSFC) sign (p < 0.001), and expansion of affected side of internal auditory canal (IAC) (p = 0.033) were independent factors. A nomogram model was constructed based on these indicators. When applied to the validation cohort, the nomogram demonstrated good discrimination and favorable calibration. Then we generated a web-based calculator to facilitate clinical application.Conclusion: Tumor size, FFC and CSFC sign, and the expansion of the IAC, serve as good predictors of postoperative FN outcomes. Based on these factors, the nomogram model demonstrates good predictive performance.
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页数:12
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