Association Between Socio-Demographic andHealth Functioning Variables Among Patientswith Opioid Use Disorder Introduced byPrescription: A Prospective Cohort Study
Notice bibliographique
Résumé
Background: Prescription opioid misuse in Canada has become a serious public health concern and has contributed to Canada’s opioid crisis. There are thousands of Canadians who are currently receiving treatment for opioid use disorder, which is a chronic relapsing disorder with enormous impact on individuals and society. Objectives: The aim of this study was to compare the clinical and demographic differences between cohorts of patients who were introduced to opioids through a prescription and those introduced to opioids for non-medical purposes. Study Design: This was an observational, prospective cohort study. Setting: The study took place in 19 Canadian Addiction Treatment Centres across Ontario. Methods: We included a total of 976 participants who were diagnosed with Opioid Use Disorder and currently receiving methadone maintenance treatment. We excluded participants who were on any other type of prescription opioid or who were missing their 6-month follow-up urine screens. We measured the participants’ initial source of introduction to opioids along with other variables using the Maudsley Addiction Profile. We also measured illicit opioid use using urine screens at baseline and at 6-months follow-up. Results: Almost half the sample (n = 469) were initiated to opioids via prescription. Women were more likely to be initiated to opioids via a prescription (OR = 1.385, 95% CI 1.027-1.866, P = .033). Those initiated via prescription were also more likely to have post-secondary education, older age of onset of opioid use, less likely to have hepatitis C and less likely to have use cannabis. Chronic pain was significantly associated with initiation to opioids through prescription (OR = 2.720, 95% CI 1.998-3.722, P < .0001). Analyses by gender revealed that men initiated by prescription were less likely to have liver disease and less likely to use cannabis, while women initiated by prescription had a higher methadone dose. Limitations: This project was limited by its study design being observational in nature; no causal relationships can be inferred. Also, the data did not allow determination of the role that the prescribed opioids played in developing opioid use disorder. Conclusions: Our results have revealed that almost half of this methadone maintenance treatment (MMT) population has been introduced to opioids through a prescription. Given that the increasing prescribing rates of opioids has an impact on this at-risk population, alternative treatments for pain should be considered to help decrease this opioid epidemic in Canada. Key words: Opioid use disorder, chronic pain relief, methadone maintenance treatment, prescriptions, male, female
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».