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Enregistrement W3133904959 · doi:10.1111/add.15460

Linking opioid use disorder treatment from hospital to community

2021· letter· en· W3133904959 sur OpenAlexafffund
Thomas D. Brothers, Dan Lewer, Ashish P. Thakrar

Notice bibliographique

RevueAddiction · 2021
Typeletter
Langueen
DomaineMedicine
ThématiqueOpioid Use Disorder Treatment
Établissements canadiensDalhousie University
Organismes subventionnairesNational Institute on Drug AbuseFaculty of Medicine, Dalhousie UniversityCanadian Institutes of Health ResearchNational Institute for Health and Care Research
Mots-clésBuprenorphineMedicineMethadoneOpioid use disorderOpiate Substitution TreatmentMedical prescriptionIntensive care medicineOpioidPsychiatryInternal medicineNursing

Résumé

récupéré en direct d'OpenAlex

We read with interest Jo and colleagues’ study of hospitalized patients with injection drug use-associated infective endocarditis and osteomyelitis who received methadone or buprenorphine [1]. These invasive infections are increasingly common [2-6], and in-hospital initiation of medications for opioid use disorder (MOUD) is both a crucial component of secondary prevention [7-12] and the standard of care for treating opioid use disorder [13-17]. While the paper refers to ‘initiation of MOUD’ having limited effect, the investigators did not actually assess the effect of in-hospital initiation of buprenorphine or methadone maintenance treatment for opioid use disorder; they identified patients receiving either medication for any indication, including for opioid withdrawal [1]. We worry that soft-pedaling this distinction may mislead patients, clinicians and policymakers into thinking that MOUD treatment has relatively little impact in the hospital setting. Jo and colleagues reported on 1407 patients with opioid use disorder (OUD) hospitalized with endocarditis or osteomyelitis who did not have an active MOUD prescription at the time of admission [1]. They described that ‘269 (19.1%) patients were initiated on MOUD during their hospitalization’, and they defined ‘initiation on MOUD’ as receipt of any dose of methadone or buprenorphine while hospitalized. This definition of MOUD, however, does not account for whether hospital providers titrated these medications to therapeutic doses or intended them as maintenance treatment [18]. We do not think that a few doses of methadone for withdrawal, for example, should qualify as ‘initiating MOUD’ treatment [15]. Unfortunately, dosages of methadone and buprenorphine were not reported in the study; these might have been used as a proxy for providers’ intentions to continue these medications long-term. Table 2 shows that only 44 patients (3.1% of the total sample and 16.4% of those who received any dose of MOUD) were continued on MOUD at discharge, indicating that most patients only received these medications short-term, probably to relieve symptoms of opioid withdrawal [1]. As the authors note, a randomized controlled trial has shown continuation of MOUD after in-hospital initiation is much more effective at engaging patients in treatment compared to simply outpatient referral after withdrawal management [19]. It is unclear why withdrawal management in-hospital would be expected to affect 30 day re-hospitalization rates beyond reducing patient self-discharges. Further, infections such as endocarditis and osteomyelitis vary greatly in severity, as does opioid use disorder and opioid withdrawal. Provision of methadone or buprenorphine during hospital could be associated with any of these factors, which could introduce confounding into this study. It is plausible, for example, that patients given opioid agonists had a greater degree of opioid withdrawal and therefore a greater likelihood of self-discharge, or more severe infections and a greater risk of re-admission. Overall, while this is an important and under-researched topic, we do not interpret this study as assessing the effect of OUD treatment started in hospital. We would therefore challenge the use of the terms ‘initiation’ and ‘MOUD’ in the title and paper, and wish to highlight for readers the limitations of this study's design. None. Thomas Brothers: Conceptualization; Project administration; writing-original draft; writing-review & editing. Dan Lewer: Conceptualization; writing-review & editing. Ashish Thakrar: Conceptualization; writing-review & editing.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,564
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,022
Tête enseignante GPT0,263
Écart entre enseignants0,241 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission2
Résumé présentoui

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