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运用符号学对癫痫发作与精神性非癫痫发作进行分类:一项荟萃分析。

Using Semiology to Classify Epileptic Seizures vs Psychogenic Nonepileptic Seizures: A Meta-analysis.

作者信息

Muthusamy Subramanian, Seneviratne Udaya, Ding Catherine, Phan Thanh G

机构信息

Department of Medicine (SM, US, TGP), School of Clinical Sciences at Monash Health, Monash University, Melbourne, Victoria; and Department of Neurology (SM, US, CD, TGP), Monash Medical Centre, Clayton, Melbourne, Australia.

出版信息

Neurol Clin Pract. 2022 Jun;12(3):234-247. doi: 10.1212/CPJ.0000000000001170.

Abstract

BACKGROUND AND OBJECTIVES

A misdiagnosis of psychogenic nonepileptic seizures (PNES) and epileptic seizures (ES) is common. In the absence of the diagnostic gold standard (video EEG), clinicians rely on semiology and clinical assessment. However, questions regarding the diagnostic accuracy of different signs remain. This meta-analysis aimed to evaluate the diagnostic accuracy of semiology in PNES and ES.

METHODS

We systematically searched PubMed, PsycInfo, and Medline for original research publications published before 8 February 2021 with no restriction on search dates to identify studies that compared semiology in ES and PNES in epilepsy monitoring units. Non-English publications, review articles, studies reporting on only PNES or ES, and studies limited to patients with developmental delay were excluded. Study characteristics and proportions of event groups and patient groups demonstrating signs were extracted from each article. A bivariate analysis was conducted, and data were pooled in a random effects model for meta-analysis. The statistic was calculated to assess statistical heterogeneity. The revised Quality Assessment of Diagnostic Accuracy Studies tool was used to assess the risk of bias in included studies. The positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were calculated. A PLR >10 or an NLR <0.1 largely affected the posttest probability of a diagnosis (ES or PNES), whereas a PLR between 5 and 10 or an NLR between 0.1 and 0.2 moderately affected the posttest probability of a diagnosis (ES or PNES).

RESULTS

The meta-analysis included 14 studies comprising 800 patients with ES and 452 patients with PNES. For PNES, ictal eye closure (PLR 40.5 95% confidence interval [CI] 16.2-101.3; = 0, from 3 studies) and asynchronous limb movements (PLR 10.2; 95% CI 2.8-37.7; = 0, from 3 studies) reached a PLR threshold >5. No single sign reached a PLR threshold >5 for ES.

DISCUSSION

While all signs require an interpretation in the overall clinical context, the presence of ictal eye closure and asynchronous limb movements are reliable discriminative signs for PNES.

摘要

背景与目的

心因性非癫痫性发作(PNES)和癫痫性发作(ES)的误诊很常见。在缺乏诊断金标准(视频脑电图)的情况下,临床医生依赖症状学和临床评估。然而,关于不同体征诊断准确性的问题依然存在。这项荟萃分析旨在评估症状学在PNES和ES中的诊断准确性。

方法

我们系统检索了PubMed、PsycInfo和Medline数据库,查找2021年2月8日前发表的原始研究文献,检索日期无限制,以确定在癫痫监测单元中比较ES和PNES症状学的研究。排除非英文出版物、综述文章、仅报告PNES或ES的研究以及仅限于发育迟缓患者的研究。从每篇文章中提取研究特征以及显示体征的事件组和患者组的比例。进行双变量分析,并将数据汇总到随机效应模型中进行荟萃分析。计算Q统计量以评估统计异质性。使用修订后的诊断准确性研究质量评估工具评估纳入研究的偏倚风险。计算阳性似然比(PLR)和阴性似然比(NLR)。PLR>10或NLR<0.1对诊断(ES或PNES)的验后概率有很大影响,而PLR在5至10之间或NLR在0.1至0.2之间对诊断(ES或PNES)的验后概率有中等影响。

结果

该荟萃分析纳入了14项研究,包括800例ES患者和452例PNES患者。对于PNES,发作期闭眼(PLR 40.5,95%置信区间[CI] 16.2 - 101.3;Q = 0,来自3项研究)和肢体异步运动(PLR 10.2;95% CI 2.8 - 37.7;Q = 0,来自3项研究)达到了PLR阈值>5。对于ES,没有单一体征达到PLR阈值>5。

讨论

虽然所有体征都需要在整体临床背景下进行解读,但发作期闭眼和肢体异步运动的存在是PNES可靠的鉴别体征。

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