Substance Use Patterns and Schizophrenia Spectrum Disorders: A Retrospective Study of Inpatients at a Community Teaching Hospital
Notice bibliographique
Résumé
BACKGROUND: Schizophrenia is one of the chronic mental illnesses, characterized by delusions, hallucinations, disorganized speech, grossly disorganized or catatonic behavior, and cognitive decline. It frequently leads to a lifetime of impairment and disability that span the entire lifespan of the patients. Several epidemiologic studies have shown that schizophrenia spectrum disorders (SSDs) contribute significantly to years lived with disability. Additionally, substance use disorders have been reported to co-occur commonly among patients with SSD (a comorbidity also known as dual diagnosis), attracting notable attention over the past few decades. This dual diagnosis often requires treatment modifications to ensure for best patient outcomes. METHODS: This study was a retrospective review of the electronic medical charts. The patients included in the study were discharged from the psychiatric unit of our hospital between July 1, 2017 and October 31, 2017. Patients were included in the study using three inclusion criteria: 1) age ≥18 years; 2) had a diagnosis of SSD at discharge; and 3) had urine drug screen performed. Sociodemographic and clinical variables were abstracted. Univariate analysis and summary statistics were performed. Bivariate and multivariate analyses were done via logistic regression models to determine the odds ratios (ORs) and corresponding P values (P). RESULTS: A total of 365 (52.2%) patients had a diagnosis of SSD at discharge. Of these, 349 met the inclusion criteria. The age ranged from 19 to 79 years, with a mean age of 42.2 years, and 76.8% of the patients used substances. Out of the 269 patients who used substances, 199 (74%) used two or more substances. Tobacco use was most prevalent (62.3%), followed by cannabis use (41.5%), alcohol use (40.2%), and cocaine use (27.4%). Patients who reported using tobacco, were more likely to have comorbid alcohol use (OR = 7.24; P = 0.000), cannabis use (OR = 2.80; P = 0.000), cocaine use (OR = 5.00; P = 0.000), and synthetic cannabis (K2) use (OR = 4.62; P = 0.048). Results of the multivariate analyses supported the other findings. CONCLUSIONS: Our study found a high association between schizophrenia spectrum disorders and substance use, with three out of four patients with SSD using a substance. This prevalence is higher than previously reported by other studies. Among those who use substances, about three in four use multiple substances. These point to some interaction between the substances and appear to be heavily influenced by significant social determinants of mental health that continue to plague the community. It is important to establish if a patient with schizophrenia has a comorbid substance use disorder, because addressing both generally leads to better patient outcomes.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| 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 | 0,000 | 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 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 ».