Withdrawal symptoms predict prescription opioid dependence in chronic pain patients.


Journal

Drug and alcohol dependence
ISSN: 1879-0046
Titre abrégé: Drug Alcohol Depend
Pays: Ireland
ID NLM: 7513587

Informations de publication

Date de publication:
01 02 2019
Historique:
received: 24 10 2018
accepted: 12 11 2018
pubmed: 19 12 2018
medline: 27 6 2019
entrez: 19 12 2018
Statut: ppublish

Résumé

The last version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) includes substantial changes for prescription opioid-use disorder (POUD). After its removal as a criterion, the goal of this study was to estimate the prevalence of withdrawal symptoms in long-term users of prescription opioids and its association with the new DSM-5 POUD classification. Data were collected from 215 long-term consumers of opioid medication who were chronic non-cancer pain patients. Participants completed sociodemographic, Adjective Rating Scale for Withdrawal (ARSW), opioid treatment characteristics, POUD criteria (DSM-5), and pain intensity measurements. 26.6% of the participants were classified with moderate to severe POUD. Higher intensity of withdrawal symptoms was found in patients with moderate/severe POUD, younger age, and higher pain intensity (p < .01). Anxiolytics (p < .01) and antidepressants use (p < .05) and percentage of smokers (p < .05) were significantly higher in patients with severe withdrawal. Logistic regression analyses suggested moderate [odds ratio (OR) = 3.25] and severe (OR = 10.52) withdrawal as the strongest predictor of POUD. Age, anxiolytics use, and smoking were also associated with POUD, but multilevel analysis showed that these variables do not moderate the association between withdrawal intensity and POUD. Escalation of withdrawal intensity during opioid treatment can be used to identify patients with POUD. Further studies are needed to assess the clinical implications of these findings during long-term opioid therapy for chronic pain.

Sections du résumé

BACKGROUND
The last version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) includes substantial changes for prescription opioid-use disorder (POUD). After its removal as a criterion, the goal of this study was to estimate the prevalence of withdrawal symptoms in long-term users of prescription opioids and its association with the new DSM-5 POUD classification.
METHODS
Data were collected from 215 long-term consumers of opioid medication who were chronic non-cancer pain patients. Participants completed sociodemographic, Adjective Rating Scale for Withdrawal (ARSW), opioid treatment characteristics, POUD criteria (DSM-5), and pain intensity measurements.
RESULTS
26.6% of the participants were classified with moderate to severe POUD. Higher intensity of withdrawal symptoms was found in patients with moderate/severe POUD, younger age, and higher pain intensity (p < .01). Anxiolytics (p < .01) and antidepressants use (p < .05) and percentage of smokers (p < .05) were significantly higher in patients with severe withdrawal. Logistic regression analyses suggested moderate [odds ratio (OR) = 3.25] and severe (OR = 10.52) withdrawal as the strongest predictor of POUD. Age, anxiolytics use, and smoking were also associated with POUD, but multilevel analysis showed that these variables do not moderate the association between withdrawal intensity and POUD.
CONCLUSION
Escalation of withdrawal intensity during opioid treatment can be used to identify patients with POUD. Further studies are needed to assess the clinical implications of these findings during long-term opioid therapy for chronic pain.

Identifiants

pubmed: 30562677
pii: S0376-8716(18)30821-4
doi: 10.1016/j.drugalcdep.2018.11.013
pii:
doi:

Substances chimiques

Analgesics, Opioid 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

27-32

Informations de copyright

Copyright © 2018 Elsevier B.V. All rights reserved.

Auteurs

Ainhoa Coloma-Carmona (A)

Center for Applied Psychology, Miguel Hernández University, Avenida Universidad, s/n, 03202, Elche, Spain. Electronic address: ainhoa.coloma@umh.es.

José L Carballo (JL)

Center for Applied Psychology, Miguel Hernández University, Avenida Universidad, s/n, 03202, Elche, Spain. Electronic address: jcarballo@umh.es.

Jesús Rodríguez-Marín (J)

Center for Applied Psychology, Miguel Hernández University, Avenida Universidad, s/n, 03202, Elche, Spain. Electronic address: rod.marin@umh.es.

Ana Pérez-Carbonell (A)

University General Hospital of Elche, Camino de la Almazara, 11, 03203, Elche, Spain. Electronic address: perez_anacar@gva.es.

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