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Record W3194974278 · doi:10.1111/epi.17043

Benzodiazepine administration patterns before escalation to second‐line medications in pediatric refractory convulsive status epilepticus

2021· article· en· W3194974278 on OpenAlexaffabout
Theodore Sheehan, Marta Amengual‐Gual, Alejandra Vasquez, Nicholas S. Abend, Anne E. Anderson, Brian Appavu, Ravindra Arya, Cristina Barcia Aguilar, J. Nicholas Brenton, Jessica L. Carpenter, Kevin Chapman, Justice Clark, Raquel Farias‐Moeller, William D. Gaillard, Marina Gaínza‐Lein, Tracy A. Glauser, Joshua Goldstein, Howard P. Goodkin, Réjean M. Guerriero, Linda Huh, Michele Jackson, Kush Kapur, Robert J. Kahoud, Yi‐Chen Lai, Tiffani L. McDonough, Mohamad A. Mikati, Lindsey A. Morgan, Edward J. Novotny, Adam P. Ostendorf, Eric T. Payne, Katrina Peariso, Juan Piantino, Latania Reece, James J. Riviello, Tristan T. Sands, Kumar Sannagowdara, Renée A. Shellhaas, Garnett Smith, Robert C. Tasker, Dmitry Tchapyjnikov, Alexis Topjian, Mark S. Wainwright, Angus A. Wilfong, Korwyn Williams, Bo Zhang, Tobias Loddenkemper

Bibliographic record

VenueEpilepsia · 2021
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsAlberta Children's HospitalBC Children's HospitalUniversity of British Columbia
FundersPediatric Epilepsy Research FoundationEpilepsy Foundation
KeywordsMedicineInterquartile rangeBenzodiazepineConfidence intervalStatus epilepticusRefractory (planetary science)Rate ratioPediatricsIncidence (geometry)AnesthesiaInternal medicineEpilepsyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: This study was undertaken to evaluate benzodiazepine (BZD) administration patterns before transitioning to non-BZD antiseizure medication (ASM) in pediatric patients with refractory convulsive status epilepticus (rSE). METHODS: This retrospective multicenter study in the United States and Canada used prospectively collected observational data from children admitted with rSE between 2011 and 2020. Outcome variables were the number of BZDs given before the first non-BZD ASM, and the number of BZDs administered after 30 and 45 min from seizure onset and before escalating to non-BZD ASM. RESULTS: We included 293 patients with a median (interquartile range) age of 3.8 (1.3-9.3) years. Thirty-six percent received more than two BZDs before escalating, and the later the treatment initiation was after seizure onset, the less likely patients were to receive multiple BZD doses before transitioning (incidence rate ratio [IRR] = .998, 95% confidence interval [CI] = .997-.999 per minute, p = .01). Patients received BZDs beyond 30 and 45 min in 57.3% and 44.0% of cases, respectively. Patients with out-of-hospital seizure onset were more likely to receive more doses of BZDs beyond 30 min (IRR = 2.43, 95% CI = 1.73-3.46, p < .0001) and beyond 45 min (IRR = 3.75, 95% CI = 2.40-6.03, p < .0001) compared to patients with in-hospital seizure onset. Intermittent SE was a risk factor for more BZDs administered beyond 45 min compared to continuous SE (IRR = 1.44, 95% CI = 1.01-2.06, p = .04). Forty-seven percent of patients (n = 94) with out-of-hospital onset did not receive treatment before hospital arrival. Among patients with out-of-hospital onset who received at least two BZDs before hospital arrival (n = 54), 48.1% received additional BZDs at hospital arrival. SIGNIFICANCE: Failure to escalate from BZDs to non-BZD ASMs occurs mainly in out-of-hospital rSE onset. Delays in the implementation of medical guidelines may be reduced by initiating treatment before hospital arrival and facilitating a transition to non-BZD ASMs after two BZD doses during handoffs between prehospital and in-hospital settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.319
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2021
Admission routes2
Has abstractyes

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