Five-Year Trajectories of Prescription Opioid Use
Notice bibliographique
Résumé
Importance: There are known risks of using opioids for extended periods. However, less is known about the long-term trajectories of opioid use following initiation. Objective: To identify 5-year trajectories of prescription opioid use, and to examine the characteristics of each trajectory group. Design, Setting, and Participants: This population-based cohort study conducted in New South Wales, Australia, linked national pharmaceutical claims data to 10 national and state data sets to determine sociodemographic characteristics, clinical characteristics, drug use, and health services use. The cohort included adult residents (aged ≥18 years) of New South Wales who initiated a prescription opioid between July 1, 2003, and December 31, 2018. Statistical analyses were conducted from February to September 2022. Exposure: Dispensing of a prescription opioid, with no evidence of opioid dispensing in the preceding 365 days, identified from pharmaceutical claims data. Main Outcomes and Measures: The main outcome was the trajectories of monthly opioid use over 60 months from opioid initiation. Group-based trajectory modeling was used to classify these trajectories. Linked health care data sets were used to examine characteristics of individuals in different trajectory groups. Results: Among 3 474 490 individuals who initiated a prescription opioid (1 831 230 females [52.7%]; mean [SD] age, 49.7 [19.3] years), 5 trajectories of long-term opioid use were identified: very low use (75.4%), low use (16.6%), moderate decreasing to low use (2.6%), low increasing to moderate use (2.6%), and sustained use (2.8%). Compared with individuals in the very low use trajectory group, those in the sustained use trajectory group were older (age ≥65 years: 22.0% vs 58.4%); had more comorbidities, including cancer (4.1% vs 22.2%); had increased health services contact, including hospital admissions (36.9% vs 51.6%); had higher use of psychotropic (16.4% vs 42.4%) and other analgesic drugs (22.9% vs 47.3%) prior to opioid initiation, and were initiated on stronger opioids (20.0% vs 50.2%). Conclusions and relevance: Results of this cohort study suggest that most individuals commencing treatment with prescription opioids had relatively low and time-limited exposure to opioids over a 5-year period. The small proportion of individuals with sustained or increasing use was older with more comorbidities and use of psychotropic and other analgesic drugs, likely reflecting a higher prevalence of pain and treatment needs in these individuals.
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Comment cette classification a été obtenuedéplier
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) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 ».