Usefulness of the Brief Pain Inventory inPatients with Opioid Addiction ReceivingMethadone Maintenance Treatment
Notice bibliographique
Résumé
BACKGROUND: Chronic pain is implicated as a risk factor for illicit opioid use among patients with opioid addiction treated with methadone. However, there exists conflicting evidence that supports and refutes this claim. These discrepancies may stem from the large variability in pain measurement reported across studies. OBJECTIVES: We aim to determine the clinical and demographic characteristics of patients reporting pain and evaluate the prognostic value of different pain classification measures in a sample of opioid addiction patients. STUDY DESIGN: Multi-center prospective cohort study. SETTING: Methadone maintenance treatment facilities for managing patients with opioid addiction. METHODS: This study includes participants from the Genetics of Opioid Addiction (GENOA) prospective cohort study. We assessed the prognostic value of different pain measures for predicting opioid relapse. Pain measures include the Brief Pain Inventory (BPI) and patients' response to a direct pain question all study participants were asked from the GENOA case report form (CRF) "are you currently experiencing or have been diagnosed with chronic pain?" Performance characteristics of the GENOA CRF pain measure was estimated with sensitivity and specificity using the BPI as the gold standard reference. Prognostic value was assessed using pain classification as the primary independent variable in an adjusted analysis using 1) the percentage of positive opioid urine screens and 2) high-risk opioid use (= 50% positive opioid urine screens) as the dependent variables in a linear and logistic regression analyses, respectively. RESULTS: Among participants eligible for inclusion (n = 444) the BPI was found to be highly sensitive, classifying a large number of GENOA participants with pain (n = 281 of the 297 classified with pain, 94.6%) in comparison to the GENOA CRF (n = 154 of 297 classified with pain, 51.8%). Participants concordantly classified as having pain according to the GENOA CRF and BPI were found to have an estimated 7.79% increase in positive opioid urine screens (estimated coefficient: 7.79; 95% CI 0.74, 14.85: P = 0.031) and a 4 times greater odds (odds ratio [OR]: 4.10 P = 0.008; 95% CI: 1.44, 11.63) of engaging in a "high risk" level of illicit opioids use. The prognostic relevance of pain classification was not maintained for the additional participants classified by the BPI (n = 143 discordant). CONCLUSION: These results suggest that while the BPI may be more sensitive in capturing pain among patients with opioid addiction, this tool is of less value for predicting the impact of pain on illicit opioid use for opioid addiction patients on methadone maintenance treatment. The GENOA CRF showed high predictive ability, whereby patients classified according to the GENOA CRF are at serious risk for opioid relapse. Using the appropriate tool to assess pain in opioid addiction may serve to improve the current detection and management of comorbid pain. LIMITATIONS: We caution the interpretation of these result since they are still reflective of participants already maintained on an opioid substitution therapy (OST), which can largely differ from patients who drop out of methadone maintenance treatment (MMT) or never seek treatment altogether.
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 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 | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| 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 ».