Evidence map›Paper›PMID 39143558›Full record

ArticleBMC neurology2024

Optimizing electroencephalogram duration for efficient detection of epileptiform abnormalities in diverse patient groups: a retrospective study.

Yinxue Xing, Jing Wang, Xiaoqian Yin, Zhiliang Fan, Shaoqun Luan, Fan Sun

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Article in BMC neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Yinxue XingNeurology Department, Affiliated Xing Tai People Hospital of Hebei Medical University, Xingtai, China. wmda080214@163.com.
Jing WangNeurology Department, Affiliated Xing Tai People Hospital of Hebei Medical University, Xingtai, China.
Xiaoqian YinImaging Department, Affiliated Xing Tai People Hospital of Hebei Medical University, Xingtai, China.
Zhiliang FanNeurology Department, Affiliated Xing Tai People Hospital of Hebei Medical University, Xingtai, China.
Shaoqun LuanNeurology Department, Affiliated Xing Tai People Hospital of Hebei Medical University, Xingtai, China.
Fan SunNeurology Department, Affiliated Hospital of Chengde Medical University, Chengde, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is no standardized EEG duration guideline for detecting epileptiform abnormalities in patients, and research on this topic is scarce. This study aims to determine an optimal EEG duration for efficient detection of epileptiform abnormalities across different patient groups.

methodsRetrospective analysis was performed on EEG recordings and clinical data of patients with the first seizure and epilepsy. Patients were categorized based on various factors, including the interval time since the last seizure, use of anti-seizure medication (ASM), and seizure frequency. The detection ratio (DR) of epileptiform abnormalities and latency time for their discovery were calculated. Statistical analyses, including chi-square tests, logistic regression, and survival analysis were utilized to illustrate DR and latency times.

resultsIn whole-night EEG recordings, the DR was 37.6% for the first seizure group and 57.4% for the epilepsy group. Although the maximum latency times were 720 min in both two groups, DR in the first seizure group was distinctly decreased beyond 300 min. Significant factors influencing the DR included the use of ASM in the first seizure group (P < 0.05) and seizure frequency in the epilepsy group (P < 0.001). For epilepsy patients who experience a seizure at least once a month or undergo timely EEG recordings (within 24 h after a seizure), the DR significantly increases, and the maximum latency time is reduced to 600 min (P < 0.001). Additionally, the DR was significantly reduced after 240 min in epilepsy patients who had been seizure-free for more than one year.

conclusionsIn this retrospective study, we observed a maximum latency of 720 min for detecting epileptiform abnormalities in whole-night EEG recordings. Notably, epilepsy patients with a higher seizure frequency or timely EEG recordings demonstrated both a higher detection ratio and a shorter maximum latency time. For patients exhibiting a low detection ratio, such as those experiencing their first seizure or those with epilepsy who have been seizure-free for more than a year, a shorter EEG duration is recommended. These findings underscore the importance of implementing customized EEG strategies to meet the specific needs of different patient groups.

Indexed as

ElectroencephalographyEpilepsySeizuresAdolescentAdultAgedAnticonvulsantsChildFemaleHumansMaleMiddle AgedRetrospective StudiesTime FactorsYoung AdultAnticonvulsantsDuration of EEGEpileptiform abnormalityInterval time between the last seizure and EEG recordingNight’s sleepSeizure frequency

Identifiers

PMID39143558
PMCPMC11323660

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