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开发一种临床模型以预测耐药性癫痫患儿的迷走神经刺激反应。

Development of a clinical model to predict vagus nerve stimulation response in pediatric patients with drug-resistant epilepsy.

作者信息

Muthiah Nallammai, Mallela Arka N, Vodovotz Lena, Sharma Nikhil, Akwayena Emefa, Pan Evelyn, Welch William, Ibrahim George M, Abel Taylor J

机构信息

1Department of Neurological Surgery, University of Pittsburgh.

2Department of Pediatrics, Division of Child Neurology, University of Pittsburgh, Pennsylvania.

出版信息

J Neurosurg Pediatr. 2023 Feb 17;31(5):476-483. doi: 10.3171/2023.1.PEDS22312. Print 2023 May 1.

Abstract

OBJECTIVE

Epilepsy impacts 470,000 children in the United States. For patients with drug-resistant epilepsy (DRE) and unresectable seizure foci, vagus nerve stimulation (VNS) is a treatment option. Predicting response to VNS has been historically challenging. The objective of this study was to create a clinical VNS prediction tool for use in an outpatient setting.

METHODS

The authors performed an 11-year retrospective cohort analysis with 1-year follow-up. Patients < 21 years of age with DRE who underwent VNS (n = 365) were included. Logistic regressions were performed to assess clinical factors associated with VNS response (≥ 50% seizure frequency reduction after 1 year); 70% and 30% of the sample were used to train and validate the multivariable model, respectively. A prediction score was subsequently developed. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated.

RESULTS

Variables associated with VNS response were < 4-year epilepsy duration before VNS (p = 0.008) and focal motor seizures (p = 0.037). The variables included in the clinical prediction score were epilepsy duration before VNS, age at seizure onset, number of pre-VNS antiseizure medications, if VNS was the patient's first therapeutic epilepsy surgery, and predominant seizure semiology. The final AUCs were 0.7013 for the "fitted" sample and 0.6159 for the "validation" sample.

CONCLUSIONS

The authors developed a clinical model to predict VNS response in a large sample of pediatric patients treated with VNS. Despite the large sample size, clinical variables alone were not able to accurately predict VNS response. This score may be useful after further validation, although its predictive ability underscores the need for more robust biomarkers to predict treatment response.

摘要

目的

在美国,癫痫影响着47万名儿童。对于药物难治性癫痫(DRE)和不可切除癫痫病灶的患者,迷走神经刺激(VNS)是一种治疗选择。一直以来,预测VNS的反应具有挑战性。本研究的目的是创建一种用于门诊环境的临床VNS预测工具。

方法

作者进行了一项为期11年的回顾性队列分析,并进行1年的随访。纳入年龄小于21岁、接受VNS治疗的DRE患者(n = 365)。进行逻辑回归以评估与VNS反应相关的临床因素(1年后癫痫发作频率降低≥50%);分别使用70%和30%的样本训练和验证多变量模型。随后制定了一个预测评分。计算敏感性、特异性和受试者工作特征曲线下面积(AUC)。

结果

与VNS反应相关的变量是VNS前癫痫病程<4年(p = 0.008)和局灶性运动性癫痫发作(p = 0.037)。临床预测评分中包含的变量有VNS前癫痫病程、癫痫发作起始年龄、VNS前抗癫痫药物数量、VNS是否为患者首次治疗性癫痫手术以及主要癫痫发作症状学。“拟合”样本的最终AUC为0.7013,“验证”样本的最终AUC为0.6159。

结论

作者开发了一种临床模型,用于预测接受VNS治疗的大量儿科患者的VNS反应。尽管样本量很大,但仅临床变量无法准确预测VNS反应。尽管其预测能力强调需要更强大的生物标志物来预测治疗反应,但该评分在进一步验证后可能会有用。

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