Psychotropic Medication Usage in Individuals with Fetal Alcohol Spectrum Disorders (FASD) and Psychiatric Co-morbidities in Canada
Notice bibliographique
Résumé
Background and objective Individuals with Fetal Alcohol Spectrum Disorder (FASD) tend to be prescribed a high number of psycho-tropic medications to treat high rates of comorbid psychiatric disorders. A lack of guidance regarding best practices for prescribing psychotropic medications to individuals with FASD probably accounts for this reliance on polypharmacy. The objective of this study is to describe the types of medications prescribed to individuals with prenatal alcohol exposure, comparing rates between individuals diagnosed with FASD and individuals without FASD as well as how medications are prescribed based on age, sex, and comorbid psychiatric disorders. Material and methods Data were drawn from Canada's national FASD database. This database includes information collected during an FASD assessment related to diagnostic outcomes, secondary challenges, and medical and mental health information. Descriptive statistics were calculated for four diagnostic groups (FASD with sentinel facial features [FASD + SFF], FASD without sentinel facial features [FASD - SFF], at risk for FASD [“at risk”], and no FASD). Group demographics were compared using Chi-Square, Fisher's Exact Test, and ANOVA, as appropriate. Differences in the proportion of individuals between these four diagnostic groups were calculated using each of the following six classes of psychotropic medications—antipsychotics, antidepressants/anxiolytic, anticonvulsants/mood stabilizers, stimulants, melatonin, and others—using ANOVA. Considering just the individuals with FASD by combining the FASD + SFF and FASD - SFF groups, independent sample tests were used to compare differences in the proportion of males and females prescribed different medications. Chi-Square and Fisher's Exact Test were used to compare the proportion of individuals using psychotropic medications, according to category, within the FASD group based on the presence or absence of 13 comorbid psychiatric disorders. Results The overall sample included 2349 participants (mean value = 18.1 years, SD = 10.3). The sample included 1453 participants with an FASD diagnosis (n = 218, FASD + SFF, mean = 23.7 years, SD = 15.8, and n = 1235, FASD - SFF, mean = 19.5 years, SD = 10.0 years) and 896 participants who were assessed but did not receive an FASD diagnosis (n = 653, no FASD, mean = 16.1 years and n = 261, “at risk” for FASD, mean = 12.2 years). The FASD groups had a significantly higher rates of anxiety disorders, depressive disorders, and the presence of at least one comorbid psychiatric disorder compared to the no FASD and the “at risk” groups. Both FASD groups had a higher proportion of individuals taking antipsychotic and antidepressant/anxiolytic medications compared to the no FASD and “at risk” groups. Females with FASD were more often prescribed antidepressants/anxiolytics compared to males with FASD, while males with FASD were more often prescribed stimulants than females with FASD. The prevalence of antidepressants/anxiolytics, stimulants, and melatonin use by individuals with FASD differed across the lifespan. The prevalence of the prescription of six medication categories was found to differ according to psychiatric disorder. Conclusion Compared to individuals assessed as not fulfilling criteria for FASD, those with FASD had higher rates of psychiatric disorders and were prescribed significantly more antidepressants/anxiolytics and antipsychotics. The class and rate of prescriptions may support efforts in devising treatment guidelines for a complex disorder with known high comorbidity such as FASD.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».