TREATMENT DISENGAGEMENT AND APD TREATMENT IN EARLY PSYCHOSIS: RESULTS FROM EPINET – THE LARGEST EP NETWORK IN THE USA
Notice bibliographique
Résumé
Abstract Background Treatment disengagement (TD) is a far too frequent event among patients with early psychosis (EP). TD contributes to poor outcomes as it has been associated with relapses and hospitalizations (1). Rates of TD are higher in EP than other forms a of psychosis and are as high as 80% during the first year of care (2). One of the most important factors associated with TD is antipsychotic drug (APD)-related side effects and dissatisfaction (3). Aims & Objectives The purpose of this paper is to examine TD and APD usage in the largest EP intervention network termed Early Psychosis Intervention Network (EPINET) which is comprised of 8 hub and spoke (clinics) networks, over 100 EP clinics and over 4,000 EP patients all in the USA. Discharge rates, reasons for discharge, and APD patterns of use, satisfaction and adverse event rates will be examined. Method Admission criteria to EPINET includes an age range of 14 to 35 and affective or nonaffective psychotic disorders with onsets within 5 years of first psychotic symptoms. All clinics employ the coordinated specialty care (CSC) treatment model and utilize a common assessment battery (CAB). The CAB is administered at enrollment (baseline) and at each sequential 6-month time point. It contains a battery of validated assessment measures and include data collection of discharges, reasons for discharge, types of APDs, and APD side effects. Results An EPINET-wide analysis revealed a 6-month (N=2391) discharge rate of 20.0%, and a 12-month (N=1852) discharge rate of 41.5%. The most commonly reported reasons for discharge (N=1,818) were: terminated services 24.7%; completed program/no longer needed services 22.7% and whereabouts unknown 15.8%. Remarkably similar discharge rates were observed in Academic-Community (AC) EPINET (one of the 8 EPINET hub networks) of 6-month (N=515) discharge rate of 19.8% and 12-month (N=457) discharge rate of 38.9%. The most commonly reported reasons for discharges (N=183) were: whereabouts unknown 26.8%; terminated services 23.5% and moved out of service area 13.7%. In AC- EPINET, 74.3% were prescribed antipsychotic medications. The most commonly prescribed oral APDs (N=283) were aripiprazole 29.3%, olanzapine 19.1% and risperidone 18.2%. There were no prescriptions for the three most recently FDA approved APDs – lumateperone, caripirazine and brexpiperozole. Clozapine use was 9.5%. Long-acting depot APDs use was 15.3%. On a APD satisfaction scale rated 0 (not at all) to10 (entirely), only 50.6% rated high satisfaction (scores 8 to 10). The most common medication side effects were changes in weight/appetite 28.1%, daytime sedation 17.4%, concentration problems 11.6%, restlessness 10.7%, and muscle tenseness 8.7%. Discussion & Conclusion The results indicate that discharges were high among EP patients with 40% rates within 12 months of CSC treatment. Only 50% of patient were highly satisfied with their APD medication treatment with weight change, and sedation being the most common side effects. These results suggest that improved treatment engagement strategies and better APD medications are need for EP care. References 1. Dixon LB et al Treatment engagement of individuals experiencing mental illness: review and update. World Psychiatry 2016; 15:13-20. 2. Kane JM et al Factors contributing to engagement during the initial stages of treatment for psychosis Qual Health Res 2012; 23;336-47. 3. Lal S et al Service engagement in first-episode psychosis: Current issues and future directions. Canadian Journal of Psychiatry 2015; 60:341
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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 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».