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Record W4291020321 · doi:10.1111/epi.17391

International consensus recommendations for management of new onset refractory status epilepticus (NORSE) including febrile infection‐related epilepsy syndrome (FIRES): Summary and clinical tools

2022· article· en· W4291020321 on OpenAlexaff
Ronny Wickström, Olga Taraschenko, Robertino Dilena, Eric T. Payne, Nicola Specchio, Rima Nabbout, Sookyong Koh, Nicolas Gaspard, Lawrence J. Hirsch

Bibliographic record

VenueEpilepsia · 2022
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsAlberta Children's Hospital
FundersNational Institute of General Medical SciencesEpilepsy SocietyNational Institutes of HealthFondazione IRCCS Ca' Granda Ospedale Maggiore PoliclinicoNational Center for Advancing Translational SciencesAmerican Epilepsy Society
KeywordsDelphi methodMedicineIntensive care medicineEpilepsy syndromesEpilepsyStatus epilepticusEpilepsia partialis continuaPediatricsDelphiFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop consensus-based recommendations for the management of adult and pediatric patients with NORSE/FIRES based on best available evidence and expert opinion. METHODS: The Delphi methodology was followed. A facilitator group of 9 experts was established, who defined the scope, users and suggestions for recommendations. Following a review of the current literature, recommendation statements concerning diagnosis, treatment and research directions were generated which were then voted on a scale of 1 (strongly disagree) to 9 (strongly agree) by a panel of 48 experts in the field. Consensus that a statement was appropriate was reached if the median score was greater than or equal to 7, and inappropriate if the median score was less than or equal to 3. RESULTS: Overall, 85 recommendation statements achieved consensus. The recommendations are divided into five sections: 1) disease characteristics, 2) diagnostic testing and sampling, 3) acute treatment, 4) treatment in the post-acute phase, and 5) research, registries and future directions in NORSE/FIRES. These are summarized in this article along with two practical clinical flowsheets: one for diagnosis and evaluation and one for acute treatment. A corresponding evidence-based analysis of all 85 recommendations alongside responses by the Delphi panel is presented in a companion article. SIGNIFICANCE: The recommendations generated by this consensus can be used as a guide for the diagnosis, evaluation, and management of patients with NORSE/FIRES, and for planning of future research.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.087
GPT teacher head0.393
Teacher spread0.305 · 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 teacher head, not a consensus.

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

Citations142
Published2022
Admission routes1
Has abstractyes

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