Functional seizures: Cluster analysis may predict the associated risk factors

Asadi‐Pooya, Ali A.; Farazdaghi, Mohsen

doi:10.1016/j.yebeh.2021.108485

Cited by 3 publications

(2 citation statements)

References 23 publications

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“…The results of cluster analysis of high potassium glass with cluster type 3 by K-means algorithm are shown in Table 1 [7]. The visual analysis of classification results is shown in Figure 5.…”

Section: Results Of K-means Clustering Algorithmmentioning

confidence: 99%

Composition Analysis and Identification of Ancient Glass Products

Li¹

2023

HSET

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Based on the research on the rules of the classification of the two kinds of glass as the goal, take glass types as the dependent variable, the chemical composition content is the independent variable, and establish a model of decision tree classification, is based on chemical component content of glass type classification rule, then to analyze the chemical composition of each category, according to the laws of the elbow to calculate the clustering analysis, the optimal class number of k, the K-means clustering algorithm was used to subclassify the glass into K classes and quantify the types. The type was taken as the dependent variable, and the content of each chemical component was taken as the independent variable for decision tree classification. The sub-classification results based on the content of each chemical component and the chemical variables with significant effect on the sub-classification results were obtained. Perturbation was introduced to the chemical variables that had a significant effect on the subclassification results, and the subclassification changes after perturbation were studied to verify the sensitivity of the classification results. The results showed that the accuracy and sensitivity of the model were good.

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Section: Results Of K-means Clustering Algorithmmentioning

confidence: 99%

Composition Analysis and Identification of Ancient Glass Products

Li¹

2023

HSET

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“…Functional seizures (FS) comprise as much as 10% of patients seen at comprehensive epilepsy centers; they happen in a heterogeneous patient population and their underlying etiology is not fully clear yet (Asadi‐Pooya, 2021 ,; 2017 ; Popkirov et al., 2019 ). While each patient's ictal behavior can be unique, clustering analyses have demonstrated key behavioral subtypes including motor functional seizures and akinetic functional seizures (Asadi‐Pooya & Farazdaghi, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Are brain MRI abnormalities associated with the semiology of functional seizures?

et al. 2023

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Purpose To investigate whether radiologically apparent brain magnetic resonance imaging (MRI) abnormalities are associated with the functional seizure (FS) semiology. Methods All patients with a diagnosis of FS at the epilepsy centers at Shiraz University of Medical Sciences, Iran; Aichi Medical University Hospital, Japan; University of Michigan, USA; University of California, Los Angeles, USA; Emory University School of Medicine, USA; and Hospital el Cruce, Argentina, were studied. Results One hundred patients were included; 77 (77%) had motor functional seizures. Lobar location of brain abnormality did not have an association with the semiology (p = .83). There was no significant difference between ictal behaviors in patients with frontal or parietal lesions compared to those with temporal or occipital lesions. Conclusion There were no associations between functional seizure ictal behaviors and locations of the radiologically apparent brain MRI abnormalities. Further studies are needed to evaluate the underpinnings of varying behaviors in FS.

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Prevalence of ictal injuries in functional (psychogenic nonepileptic) seizures: A systematic review and meta‐analysis

Moreira,

Knochenhauer,

Froehner

et al. 2023

Epilepsia

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ObjectiveIctal injuries have long been considered typical signs of epileptic seizures. However, studies have shown that patients with functional seizures (FS) – also named psychogenic non‐epileptic seizures – can also present these signs, misleading physicians and delaying a correct diagnosis. This systematic review aimed to assess the prevalence of injuries from FS.MethodsA literature search was performed in PubMed, Embase, LILACS, Scopus, Web of Science, PsycINFO, Google Scholar, OpenGrey, and ProQuest. Observational studies were included. The risk of bias was assessed using the JBI checklist for studies reporting prevalence data. RStudio was used for meta‐analyses. Cumulative evidence was evaluated according to GRADE criteria.ResultsFrom the 2,607 identified records, 41 studies were included in the qualitative synthesis, and 28 were included in meta‐analyses. A meta‐analysis of 13 studies, including 1,673 individuals, resulted in an overall lifetime prevalence of injuries due to FS per person of 25% (95% CI 19%‐32%; I2 = 88%). Considering a limited period (VEEG monitoring days), a meta‐analysis of 13 studies, including 848 individuals, resulted in an injury prevalence due to FS per person of 0.7% (95% CI 0%‐3%; I2 = 73%). Also, a meta‐analysis of 8 studies, including 1,000 individuals, resulted in a prevalence of injuries per FS of 0.1% (95% CI 0%‐0.98%; I2 = 49%). The certainty in cumulative evidence assessed by GRADE was rated “very low” for lifetime prevalence of injuries per person, “low” for prevalence per person during VEEG monitoring, and “moderate” for prevalence per number of FS.SignificanceOverall pooled lifetime prevalence of injuries due to FS per person was 25%. In comparison, the prevalence of injuries per person during VEEG monitoring and per functional seizure was 0.7% and 0.1%, consecutively. The evidence of the occurrence of injuries due to FS breaks the paradigm that epileptic seizures can cause injuries, but FS cannot. Registration: PROSPERO ID# CRD42020209300

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Functional seizures: Cluster analysis may predict the associated risk factors

Cited by 3 publications

References 23 publications

Composition Analysis and Identification of Ancient Glass Products

Composition Analysis and Identification of Ancient Glass Products

Are brain MRI abnormalities associated with the semiology of functional seizures?

Prevalence of ictal injuries in functional (psychogenic nonepileptic) seizures: A systematic review and meta‐analysis

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