Discontinuation and tapering of prescribed opioids and risk of overdose among people on long-term opioid therapy for pain with and without opioid use disorder in British Columbia, Canada: A retrospective cohort study
Notice bibliographique
Résumé
BACKGROUND: The overdose crisis in North America has prompted system-level efforts to restrict opioid prescribing for chronic pain. However, little is known about how discontinuing or tapering prescribed opioids for chronic pain shapes overdose risk, including possible differential effects among people with and without concurrent opioid use disorder (OUD). We examined associations between discontinuation and tapering of prescribed opioids and risk of overdose among people on long-term opioid therapy for pain, stratified by diagnosed OUD and prescribed opioid agonist therapy (OAT) status. METHODS AND FINDINGS: For this retrospective cohort study, we used a 20% random sample of residents in the provincial health insurance client roster in British Columbia (BC), Canada, contained in the BC Provincial Overdose Cohort. The study sample included persons aged 14 to 74 years on long-term opioid therapy for pain (≥90 days with ≥90% of days on therapy) between October 2014 and June 2018 (n = 14,037). At baseline, 7,256 (51.7%) persons were female, the median age was 55 years (quartile 1-3: 47-63), 227 (1.6%) persons had been diagnosed with OUD (in the past 3 years) and recently (i.e., in the past 90 days) been prescribed OAT, and 483 (3.4%) had been diagnosed with OUD but not recently prescribed OAT. The median follow-up duration per person was 3.7 years (quartile 1-3: 2.6-4.0). Marginal structural Cox regression with inverse probability of treatment weighting (IPTW) was used to estimate the effect of prescribed opioid treatment for pain status (discontinuation versus tapered therapy versus continued therapy [reference]) on risk of overdose (fatal or nonfatal), stratified by the following groups: people without diagnosed OUD, people with diagnosed OUD receiving OAT, and people with diagnosed OUD not receiving OAT. In marginal structural models with IPTW adjusted for a range of demographic, prescription, comorbidity, and social-structural exposures, discontinuing opioids (i.e., ≥7-day gap[s] in therapy) was associated with increased overdose risk among people without OUD (adjusted hazard ratio [AHR] = 1.44; 95% confidence interval [CI] 1.12, 1.83; p = 0.004), people with OUD not receiving OAT (AHR = 3.18; 95% CI 1.87, 5.40; p < 0.001), and people with OUD receiving OAT (AHR = 2.52; 95% CI 1.68, 3.78; p < 0.001). Opioid tapering (i.e., ≥2 sequential decreases of ≥5% in average daily morphine milligram equivalents) was associated with decreased overdose risk among people with OUD not receiving OAT (AHR = 0.31; 95% CI 0.14, 0.67; p = 0.003). The main study limitations are that the outcome measure did not capture overdose events that did not result in a healthcare encounter or death, medication dispensation may not reflect medication adherence, residual confounding may have influenced findings, and findings may not be generalizable to persons on opioid therapy in other settings. CONCLUSIONS: Discontinuing prescribed opioids was associated with increased overdose risk, particularly among people with OUD. Prescribed opioid tapering was associated with reduced overdose risk among people with OUD not receiving OAT. These findings highlight the need to avoid abrupt discontinuation of opioids for pain. Enhanced guidance is needed to support prescribers in implementing opioid therapy tapering strategies with consideration of OUD and OAT status.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,001 | 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 ».