Outcomes of an integrated care pathway for concurrent major depressive and alcohol use disorders: a multisite prospective cohort study
Notice bibliographique
Résumé
In 2013, an Integrated Care Pathway (ICP) for concurrent Major Depressive (MDD) and Alcohol Use (AUD) Disorders was developed at the Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada. The ICP was further implemented at 8 other clinical sites across Ontario (the DA VINCI Project) in 2015–2017. The goal of this study was to systematically describe and analyze the main clinical outcomes of the project. Data on a non-randomized cohort of patients receiving ICP-based treatment were collected prospectively at nine clinical sites in a variety of clinical settings. Statistical methods: descriptive statistics, t-test, chi-square, ANOVA, generalized linear models. Two hundred forty-six patients were enrolled, 58.8% males, mean age was 45.6 years, 170 patients received treatment at academic health centres (AHC), 49 – at community hospitals (CH) and 27 – in family health teams (FHT). There were no major differences in anamnestic parameters and depression severity between the three settings, but there were differences in baseline drinking patterns between subgroups (F = 4.271, df = 2, p = 0.015). Overall completion rate was 70.7% with no significant variation between settings (χ2 = 3.35, df = 2, p = 0.19). Treatment duration in AHC was the longest, and completion rates were the highest. There was a statistically significant and clinically meaningful reduction in the number of drinking days per week (1.81, t = 8.78, p < 0.001). The cohort overall demonstrated significant and meaningful reduction in severity of cravings (Penn Alcohol Craving Scale: 4.42, t = 8.63, p < 0.001) and depressive symptoms (Quick Inventory of Depressive Symptomatology: 4.25, t = 11.26, p < 0.001). While some of the baseline patient characteristics and treatment parameters varied between the settings, the variation in clinical outcomes was mostly insignificant, though clinical improvement was more pronounced in academic setting and with individual therapy. The study demonstrated that ICP is a feasible and effective treatment for concurrent AUD and MDD that delivers meaningful clinical improvement in a variety of settings. A randomized controlled study is needed to properly compare the treatment outcomes between ICP model and treatment as usual and to further explore the role of various factors on treatment outcomes.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».