Your browser doesn't support javascript.
loading
Computational EEG attributes predict response to therapy for epileptic spasms.
Rajaraman, Rajsekar R; Smith, Rachel J; Oana, Shingo; Daida, Atsuro; Shrey, Daniel W; Nariai, Hiroki; Lopour, Beth A; Hussain, Shaun A.
Afiliación
  • Rajaraman RR; Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA.
  • Smith RJ; Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, USA.
  • Oana S; Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA.
  • Daida A; Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA.
  • Shrey DW; Division of Pediatric Neurology, University of California, Irvine, Irvine, CA, USA; Department of Neurology, Children's Hospital of Orange County, Orange, CA, USA.
  • Nariai H; Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA.
  • Lopour BA; Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA.
  • Hussain SA; Division of Pediatric Neurology, UCLA Mattel Children's Hospital and University of California, Los Angeles, Los Angeles, CA, USA. Electronic address: shussain@mednet.ucla.edu.
Clin Neurophysiol ; 163: 39-46, 2024 Jul.
Article en En | MEDLINE | ID: mdl-38703698
ABSTRACT

OBJECTIVE:

We set out to evaluate whether response to treatment for epileptic spasms is associated with specific candidate computational EEG biomarkers, independent of clinical attributes.

METHODS:

We identified 50 children with epileptic spasms, with pre- and post-treatment overnight video-EEG. After EEG samples were preprocessed in an automated fashion to remove artifacts, we calculated amplitude, power spectrum, functional connectivity, entropy, and long-range temporal correlations (LRTCs). To evaluate the extent to which each feature is independently associated with response and relapse, we conducted logistic and proportional hazards regression, respectively.

RESULTS:

After statistical adjustment for the duration of epileptic spasms prior to treatment, we observed an association between response and stronger baseline and post-treatment LRTCs (P = 0.042 and P = 0.004, respectively), and higher post-treatment entropy (P = 0.003). On an exploratory basis, freedom from relapse was associated with stronger post-treatment LRTCs (P = 0.006) and higher post-treatment entropy (P = 0.044).

CONCLUSION:

This study suggests that multiple EEG features-especially LRTCs and entropy-may predict response and relapse.

SIGNIFICANCE:

This study represents a step toward a more precise approach to measure and predict response to treatment for epileptic spasms.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Espasmos Infantiles / Electroencefalografía Límite: Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Revista: Clin Neurophysiol Asunto de la revista: NEUROLOGIA / PSICOFISIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Espasmos Infantiles / Electroencefalografía Límite: Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Revista: Clin Neurophysiol Asunto de la revista: NEUROLOGIA / PSICOFISIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos