Fratangelo Roberto, Lolli Francesco, Scarpino Maenia, Grippo Antonello
UOC Neurologia, Ospedale San Giuseppe, 50053 Empoli, Italy.
Department of Biomedical, Experimental and Clinical Sciences "Mario Serio", University of Florence, 50134 Florence, Italy.
Neurol Int. 2025 Mar 24;17(4):48. doi: 10.3390/neurolint17040048.
Point-of-care electroencephalography (POC-EEG) systems are rapid-access, reduced-montage devices designed to address the limitations of conventional EEG (conv-EEG), enabling faster neurophysiological assessment in acute settings. This review evaluates their clinical impact, diagnostic performance, and feasibility in non-convulsive status epilepticus (NCSE), traumatic brain injury (TBI), stroke, and delirium. A comprehensive search of Medline, Scopus, and Embase identified 69 studies assessing 15 devices. In suspected NCSE, POC-EEG facilitates rapid seizure detection and prompt diagnosis, making it particularly effective in time-sensitive and resource-limited settings. Its after-hours availability and telemedicine integration ensure continuous coverage. AI-assisted tools enhance interpretability and accessibility, enabling use by non-experts. Despite variability in accuracy, it supports triaging, improving management, treatment decisions and outcomes while reducing hospital stays, transfers, and costs. In TBI, POC-EEG-derived quantitative EEG (qEEG) indices reliably detect structural lesions, support triage, and minimize unnecessary CT scans. They also help assess concussion severity and predict recovery. For strokes, POC-EEG aids triage by detecting large vessel occlusions (LVOs) with high feasibility in hospital and prehospital settings. In delirium, spectral analysis and AI-assisted models enhance diagnostic accuracy, broadening its clinical applications. Although POC-EEG is a promising screening tool, challenges remain in diagnostic variability, technical limitations, and AI optimization, requiring further research.
床旁脑电图(POC - EEG)系统是一种快速接入、导联减少的设备,旨在解决传统脑电图(conv - EEG)的局限性,能够在急性情况下更快地进行神经生理学评估。本综述评估了它们在非惊厥性癫痫持续状态(NCSE)、创伤性脑损伤(TBI)、中风和谵妄中的临床影响、诊断性能和可行性。通过对Medline、Scopus和Embase进行全面检索,确定了69项评估15种设备的研究。在疑似NCSE中,POC - EEG有助于快速检测癫痫发作并做出及时诊断,在时间敏感和资源有限的环境中特别有效。其非工作时间的可用性和远程医疗整合确保了持续覆盖。人工智能辅助工具提高了可解释性和可及性,使非专家也能使用。尽管准确性存在差异,但它支持分诊,改善管理、治疗决策和结果,同时减少住院时间、转诊和成本。在TBI中,POC - EEG衍生的定量脑电图(qEEG)指标能够可靠地检测结构性损伤,支持分诊并尽量减少不必要的CT扫描。它们还有助于评估脑震荡的严重程度并预测恢复情况。对于中风患者,POC - EEG通过在医院和院前环境中以高可行性检测大血管闭塞(LVO)来辅助分诊。在谵妄中,频谱分析和人工智能辅助模型提高了诊断准确性,拓宽了其临床应用。尽管POC - EEG是一种很有前景的筛查工具,但在诊断变异性、技术局限性和人工智能优化方面仍存在挑战,需要进一步研究。