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Enregistrement W2176461213 · doi:10.1002/14651858.cd003031.pub3

Prophylactic drug management for febrile seizures in children

2017· review· en· W2176461213 sur OpenAlexaff
Martin Offringa, Richard Newton, Martinus A. Cozijnsen, Sarah J Nevitt

Notice bibliographique

RevueCochrane Database of Systematic Reviews · 2017
Typereview
Langueen
DomaineMedicine
ThématiqueEpilepsy research and treatment
Établissements canadiensSickKids FoundationHospital for Sick Children
Organismes subventionnairesnon disponible
Mots-clésMedicineAntipyreticBlindingMEDLINECochrane LibraryAdverse effectPlaceboPediatricsRandomized controlled trialIntervention (counseling)Systematic reviewDosingIntensive care medicineAnalgesicAlternative medicineAnesthesiaInternal medicinePsychiatry

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Febrile seizures occurring in a child older than one month during an episode of fever affect 2% to 4% of children in Great Britain and the United States and recur in 30%. Rapid-acting antiepileptics and antipyretics given during subsequent fever episodes have been used to avoid the adverse effects of continuous antiepileptic drugs. OBJECTIVES: To evaluate primarily the effectiveness and safety of antiepileptic and antipyretic drugs used prophylactically to treat children with febrile seizures; but also to evaluate any other drug intervention where there was a sound biological rationale for its use. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2016, Issue 7); MEDLINE (1966 to July 2016); Embase (1966 to July 2016); Database of Abstracts of Reviews of Effectiveness (DARE) (July 2016). We imposed no language restrictions. We also contacted researchers in the field to identify continuing or unpublished studies. SELECTION CRITERIA: Trials using randomised or quasi-randomised participant allocation that compared the use of antiepileptic, antipyretic or other plausible agents with each other, placebo or no treatment. DATA COLLECTION AND ANALYSIS: Two review authors (RN and MO) independently applied predefined criteria to select trials for inclusion and extracted the predefined relevant data, recording methods for randomisation, blinding and exclusions. For the 2016 update a third author (MC) checked all original inclusions, data analyses, and updated the search. Outcomes assessed were seizure recurrence at 6, 12, 18, 24, 36, and 48 months and at age 5 to 6 years in the intervention and non-intervention groups, and adverse medication effects. We assessed the presence of publication bias using funnel plots. MAIN RESULTS: We included 40 articles describing 30 randomised trials with 4256 randomised participants. We analysed 13 interventions of continuous or intermittent prophylaxis and their control treatments. Methodological quality was moderate to poor in most studies. We found no significant benefit for intermittent phenobarbitone, phenytoin, valproate, pyridoxine, ibuprofen or zinc sulfate versus placebo or no treatment; nor for diclofenac versus placebo followed by ibuprofen, acetaminophen or placebo; nor for continuous phenobarbitone versus diazepam, intermittent rectal diazepam versus intermittent valproate, or oral diazepam versus clobazam.There was a significant reduction of recurrent febrile seizures with intermittent diazepam versus placebo or no treatment, with a risk ratio (RR) of 0.64 (95% confidence interval (CI) 0.48 to 0.85 at six months), RR of 0.69 (95% CI 0.56 to 0.84) at 12 months, RR 0.37 (95% CI 0.23 to 0.60) at 18 months, RR 0.73 (95% CI 0.56 to 0.95) at 24 months, RR 0.58 (95% CI 0.40 to 0.85) at 36 months, RR 0.36 (95% CI 0.15 to 0.89) at 48 months, with no benefit at 60 to 72 months. Phenobarbitone versus placebo or no treatment reduced seizures at 6, 12 and 24 months but not at 18 or 72 month follow-up (RR 0.59 (95% CI 0.42 to 0.83) at 6 months; RR 0.54 (95% CI 0.42 to 0.70) at 12 months; and RR 0.69 (95% CI 0.53 to 0.89) at 24 months). Intermittent clobazam compared to placebo at six months resulted in a RR of 0.36 (95% CI 0.20 to 0.64), an effect found against an extremely high (83.3%) recurrence rate in the controls, which is a result that needs replication.The recording of adverse effects was variable. Lower comprehension scores in phenobarbitone-treated children were found in two studies. In general, adverse effects were recorded in up to 30% of children in the phenobarbitone-treated group and in up to 36% in benzodiazepine-treated groups. We found evidence of publication bias in the meta-analyses of comparisons for phenobarbitone versus placebo (eight studies) at 12 months but not at six months (six studies); and valproate versus placebo (four studies) at 12 months, with too few studies to identify publication bias for the other comparisons.Most of the reviewed antiepileptic drug trials are of a methodological quality graded as low or very low. Methods of randomisation and allocation concealment often do not meet current standards; and treatment versus no treatment is more commonly seen than treatment versus placebo, leading to obvious risks of bias. Trials of antipyretics and zinc were of higher quality. AUTHORS' CONCLUSIONS: We found reduced recurrence rates for children with febrile seizures for intermittent diazepam and continuous phenobarbitone, with adverse effects in up to 30%. Apparent benefit for clobazam treatment in one trial needs to be replicated to be judged reliable. Given the benign nature of recurrent febrile seizures, and the high prevalence of adverse effects of these drugs, parents and families should be supported with adequate contact details of medical services and information on recurrence, first aid management and, most importantly, the benign nature of the phenomenon.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,137
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0100,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,160
Tête enseignante GPT0,447
Écart entre enseignants0,287 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations105
Publié2017
Routes d'admission1
Résumé présentoui

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