Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Epilepsiaarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Epilepsia
Article . 2024 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
versions View all 2 versions
addClaim

Timing the clinical onset of epileptic spasms in infantile epileptic spasms syndrome: A tertiary health center's experience

Authors: Aristides Hadjinicolaou; Christina Briscoe Abath; Avantika Singh; Stephanie Donatelli; Catherine L. Salussolia; Alexander Li Cohen; Jie He; +7 Authors

Timing the clinical onset of epileptic spasms in infantile epileptic spasms syndrome: A tertiary health center's experience

Abstract

AbstractObjectiveLead time to treatment (clinical onset of epileptic spasms [ES] to initiation of appropriate treatment) is known to predict outcomes in infantile epileptic spasms syndrome (IESS). Timing the clinical onset of ES is crucial to establish lead time. We investigated how often ES onset could be established to the nearest week. We aimed to (1) ascertain the exact date or estimate the nearest week of ES onset and (2) compare clinical/demographic factors between patients where date of ES onset was determined or estimated to the nearest week and patients whose date of ES onset could not be estimated to the nearest week. Reasons for difficulties in estimating date of ES onset were explored.MethodsRetrospective chart review of new onset IESS patients (January 2019–May 2022) extracted the date or week of the clinical onset of ES. Predictors of difficulty in date of ES onset estimation to the nearest week were examined by regression analysis. Sources contributing to difficulties determining date of ES onset were assessed after grouping into categories (provider‐, caregiver‐, disease‐related).ResultsAmong 100 patients, date of ES onset was estimated to the nearest week in 47%. On univariable analysis, age at diagnosis (p = .021), development delay (p = .007), developmental regression/stagnation (p = .021), ES intermixed with other seizures (p = .011), and nonclustered ES at onset (p = .005) were associated with difficulties estimating date of ES onset. On multivariable analysis, failure to establish date of ES onset was related to ES intermixed with other seizures (p = .004) and nonclustered ES at onset (p = .003). Sources contributing to difficulties determining date of ES onset included disease‐related factors (ES characteristics, challenges interpreting electroencephalograms) and provider/caregiver‐related factors (delayed diagnosis).SignificanceDifficulties with estimation of lead time (due to difficulties timing ES onset) can impact clinical care (prognostication), as even small increments in lead time duration can have adverse developmental consequences.

Related Organizations
Keywords

Spasm, Seizures, Humans, Infant, Electroencephalography, Syndrome, Age of Onset, Spasms, Infantile, Retrospective Studies

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!