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Risk v Benefits: The Use of Selective Serotonin Reuptake Inhibitors in Children

2011· article· en· W2517440738 sur OpenAlexaffvenueabout
Kim Wilton

Notice bibliographique

RevueDalhousie journal of legal studies · 2011
Typearticle
Langueen
DomainePsychology
ThématiqueChild and Adolescent Psychosocial and Emotional Development
Établissements canadiensDalhousie University
Organismes subventionnairesnon disponible
Mots-clésSertralineEscitalopramCitalopramFluoxetineAnxietyParoxetinePsychiatryFluvoxamineDepression (economics)AntidepressantChildhood DepressionPsychologyAnxiety disorderMedicineInternal medicineSerotonin
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Selective Serotonin Reuptake Inhibitors (SSRIs) are a class of antidepressant medications that came on the market in the late eighties and early nineties. SSRIs were found to be clinically effective in treating clinical depression, and anxiety disorders in adults and had less cumbersome side effects compared to the older Tricyclic antidepressants. The first drug in this class introduced was fluoxetine (Prozac), which was soon followed by paroxetine (Paxil), sertraline (Zoloft), citalopram (Celexa), fluvoxamine (Luvox), and escitalopram (Lexapro). Today the uses of SSRIs have broadened to include treatment for “Post-Traumatic Stress Disorder, pre-menstrual dysphoric disorder, urinary incontinence” and many other seemingly unrelated conditions. In North America, “it is estimated that 2% of children and up to 8% of adolescents suffer from a depressive disorder. In addition, at least 10% of youth suffer from anxiety disorders.” Given the prevalence of childhood depression and anxiety disorders, it is not surprising that in the 1990’s and early 2000’s, SSRIs became the treatment of choice in fighting childhood depression and anxiety. Not only were SSRIs prescribed to adolescents and prepubescent children, they were commonly prescribed to kindergarten aged children and even infants less than a year old. However, SSRIs were not clinically tested for use in children and adolescents, nor were they approved for use in children and adolescents. SSRIs were prescribed to children and adolescents “off-label” by physicians, meaning SSRIs had not received approval for use in these age groups by Health Canada. In the first part of the 21st century, concerns began to arise concerning the use of these drugs in children and adolescents as reports began to emerge demonstrating that in many cases SSRIs were associated with an increase in suicidal behavior and thoughts in children and adolescents. Despite being subjected to regulatory warnings from Health Canada and intense media coverage, SSRIs are still widely prescribed to children and adolescents. In this paper, I will review how SSRIs are currently regulated for use as a treatment for depression and anxiety in children and adolescents in Canada by examining the roles of the different actors involved, including: drug manufacturers, regulatory bodies, professional associations, physicians, parents and the patients themselves. In Part II of this paper I will discuss the 2004 warnings issued by regulatory agencies in Canada, the USA and the UK, against the use of SSRIs in children and adolescents; in Part III I will analyze the current off-label status of SSRIs for children and adolescents and the current system used by physicians to prescribe SSRIs to children and adolescents; and in Part IV I will discuss the problems that exist with the current system by examining the roles of each of the abovementioned actors. Finally, in Part V, I will make suggestions as to how the current system can be reformed and improved. The continued off-label use of SSRIs in children is not only dangerous for short-term use in children and adolescents, but could also have dangerous long-term effects as the consequences of SSRIs on child and adolescent development is unknown. The current regulatory system fails to protect this vulnerable population and exposes them to unwarranted and unnecessary risks. A new system is needed in which drug manufacturers are more accountable, regulatory warnings are more forceful, the ability of physicians to prescribe off-label is curtailed, and patients and their parents are more informed about treatment options.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,013
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,018
Score d'incertitude au seuil0,061

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,013
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0020,002
Science ouverte0,0000,002
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0180,001

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 Opus0,071
Tête enseignante GPT0,288
Écart entre enseignants0,217 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2011
Routes d'admission3
Résumé présentoui

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