ESCITALOPRAM VS BUPROPION AS ADJUNCTIVE TREATMENT FOR ACUTE BIPOLAR I DEPRESSION: A MULTI-CENTER OPEN LABEL TRIAL
Notice bibliographique
Résumé
Abstract Background Modern anti-depressants such as escitalopram and bupropion are widely used in clinical practice settings for the treatment of acute bipolar I depression. However, the data on the efficacy of these anti-depressants is limited and conflicting. The objective of this study was to compare the efficacy and safety of escitalopram and bupropion as adjunctive antidepressants in the treatment of acute bipolar I depression. Methods Adults (>/= 18 years) with acute bipolar I depression (MADRS score>/=20) >/= 2 weeks but </= 52 weeks who were taking lithium or divalproex at therapeutic doses or a second-generation antipsychotic (risperidone, olanzapine, quetiapine, aripiprazole, or ziprasidone) alone or in combination were recruited in Canada, Korea, and India from 2009-2020. We selected bupropion XL 100-450mg/day and escitalopram 10–30 mg/day as the study's antidepressants since they are the most often used antidepressants for treating bipolar depression. The choice of antidepressant was left to the discretion of treating clinician. Patients were commenced on adjunctive therapy with one of these antidepressants and the trial lasted for up to 16 weeks. The dose of the medications was titrated based on response and tolerability. Patients were assessed every 2 weeks or more frequently depending on clinical need until 16 weeks. Institutional ethical approval was obtained at individual sites. The primary outcome was comparison of remission rates (MADRS scores </= 8) and the secondary outcomes included comparison of response rates (>50% reduction in MADRS) and switch to mania/hypomania between escitalopram and bupropion. Results The baseline variables like age, sex, race, education, and employment were not significantly different (p >0.05) between the two groups receiving escitalopram (n =122) and bupropion (n =74). Intent-to-treat analysis was used to analyse the efficacy and patients with at least one post-baseline visit was included in the analysis. The remission rates (76.2% - escitalopram vs 83.8% - Bupropion; p = 0.21) were compared using odd’ s ratio (1.68, C.I - 0.76, 3.71, p = 0.20) adjusting for age, sex, duration of current depressive episode, number of previous mood episodes, baseline MADRS score and concomitant treatment (atypical antipsychotics, mood stabilisers or a combination of both) from a logistic regression model and they were not significantly different between the two groups. The time to remission calculated using Kaplan-Meier Survival analysis was not significantly different (log rank test p = 0.6). The response rates (83.6% - escitalopram vs 90.5% - bupropion; p = 0.17) and the switch rates (6.6% - escitalopram vs 2.7% - Bupropion; p = 0.32) did not differ significantly between escitalopram and bupropion. Discussion & Conclusion Both escitalopram and bupropion had higher remission and response rates. Though the switch rates were slightly higher with escitalopram compared to bupropion, it was not statistically different. The limitations of this study were absence of placebo and blinding. This study concludes that adjunctive treatment of bipolar I depression with anti-depressants escitalopram and bupropion are comparable in terms of efficacy and switch rates.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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.
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 source (Gemma direct ou Codex distillé), 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 ».