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3
User experience of a seizure risk forecasting app: A mixed methods investigation.用户对癫痫风险预测应用程序的体验:混合方法研究。
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4
Feasibility, Safety, and Performance of Full-Head Subscalp EEG Using Minimally Invasive Electrode Implantation.微创电极植入全头皮下 EEG 的可行性、安全性和性能。
Neurology. 2024 Jun 25;102(12):e209428. doi: 10.1212/WNL.0000000000209428. Epub 2024 Jun 6.
5
Prospective validation of a seizure diary forecasting falls short.前瞻性验证癫痫日记预测跌倒的效果不佳。
Epilepsia. 2024 Jun;65(6):1730-1736. doi: 10.1111/epi.17984. Epub 2024 Apr 12.
6
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A robust seizure detection and prediction method with feature selection and spatio-temporal casual neural network model.一种具有特征选择和时空因果神经网络模型的鲁棒性癫痫发作检测和预测方法。
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8
Forecasting seizure likelihood from cycles of self-reported events and heart rate: a prospective pilot study.基于自我报告事件和心率周期预测癫痫发作可能性:一项前瞻性试点研究。
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9
Seizure occurrence is linked to multiday cycles in diverse physiological signals.发作的发生与多种生理信号的多日周期有关。
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10
EEG datasets for seizure detection and prediction- A review.用于癫痫检测和预测的 EEG 数据集——综述。
Epilepsia Open. 2023 Jun;8(2):252-267. doi: 10.1002/epi4.12704. Epub 2023 Feb 16.

癫痫发作预测与预报:一项范围综述

Seizure prediction and forecasting: a scoping review.

作者信息

Cheng Joshua C, Goldenholz Daniel M

机构信息

Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.

出版信息

Curr Opin Neurol. 2025 Apr 1;38(2):135-139. doi: 10.1097/WCO.0000000000001344. Epub 2025 Jan 20.

DOI:10.1097/WCO.0000000000001344
PMID:39831588
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11882366/
Abstract

PURPOSE OF REVIEW

This scoping review summarizes key developments in the field of seizure forecasting.

RECENT FINDINGS

Developments have been made along several modalities of seizure forecasting, including long term intracranial and subcutaneous encephalogram, wearable physiologic monitoring, and seizure diaries. However, clinical translation of these tools is limited by various factors. One is the lack of validation of these tools on an external dataset. Moreover, the widespread practice of comparing models to a chance forecaster may be inadequate. Instead, the model should be able to at least surpass a moving average forecaster, which serves as a 'napkin test' (i.e., can be computed on the back of a napkin). The impact of seizure frequency on model performance should also be accounted for when comparing performance across studies. Surprisingly, despite the potential for poor quality forecasts, some individuals with epilepsy still want access to imprecise forecasts and some even alter their behavior based upon them.

SUMMARY

Promising advances have been made in the development of tools for seizure forecasting, but current tools have not yet overcome clinical translation hurdles. Future studies will need to address potentially dangerous patient behaviors as well as account for external validation, the napkin test, seizure frequency dependent metrics.

摘要

综述目的

本范围综述总结了癫痫发作预测领域的关键进展。

最新发现

癫痫发作预测在多种模式上取得了进展,包括长期颅内和皮下脑电图、可穿戴生理监测以及癫痫发作日记。然而,这些工具的临床转化受到多种因素的限制。一是这些工具在外部数据集上缺乏验证。此外,将模型与随机预测器进行比较的普遍做法可能并不充分。相反,模型应该至少能够超越移动平均预测器,移动平均预测器可作为一种“餐巾纸测试”(即可以在餐巾纸背面计算)。在跨研究比较性能时,还应考虑癫痫发作频率对模型性能的影响。令人惊讶的是,尽管预测质量可能较差,但一些癫痫患者仍然希望获得不精确的预测,甚至有些人会根据这些预测改变自己的行为。

总结

癫痫发作预测工具的开发取得了有前景的进展,但当前工具尚未克服临床转化障碍。未来的研究需要解决潜在的危险患者行为,并考虑外部验证、餐巾纸测试、癫痫发作频率相关指标。