Opioid Agonist Therapies and Pregnancy Outcomes for Pregnant People With Opioid Use Disorder: Protocol for a Systematic Review
Notice bibliographique
Résumé
Background Opioid use disorder (OUD) during pregnancy presents a significant risk to maternal, fetal, and neonatal health, increasing the likelihood of adverse events, such as maternal overdose, pregnancy loss, stillbirth, preterm birth, low birth weight, and neonatal abstinence syndrome. In order to reduce the risk of these outcomes, the standard of care for OUD during pregnancy in many jurisdictions within the United States and Canada is opioid agonist therapy (OAT). OAT refers to prescription medications that alleviate or eliminate opioid withdrawal symptoms, so that opioid use can be managed more safely. Although OAT has been recognized as a safe option for pregnant people with OUD, many jurisdictions do not have treatment guidelines regarding pharmacological options, dosing recommendations, side effect management, and individual preferences. There is currently a lack of systematic evidence on the impacts of different OAT regimens on pregnancy outcomes. Objective We aim to evaluate the impacts of specific OAT agents on pregnancy outcomes and inform recommendations for practitioners treating pregnant people with OUD. Methods The MEDLINE, Embase, CINAHL, and PsycINFO databases will be searched for published quantitative studies assessing pregnancy outcomes for individuals on OAT. Given the substantially increased risk of preterm birth, low birth weight, small for gestational age, and stillbirth among pregnant people with OUD, these four end points will comprise our primary outcomes. Database searches will not be restricted by date, and conference abstracts will be restricted to the past 2 years. Titles, abstracts, and full-text articles will be independently screened by 2 reviewers. Data will be extracted independently and in duplicate, using a data extraction form to reduce the risk of reviewer bias. The risk of bias within individual studies will be assessed by using the appropriate CASP (Critical Appraisal Skills Programme) checklists. For studies that consider the same research questions, interventions, or outcomes, meta-analyses will be conducted to synthesize the pooled effect size. In the event that studies cannot be compared directly, results will be synthesized in a narrative account. Between-study heterogeneity will be measured by using the τ2 statistic. If more than 10 studies are available for pooling, publication bias will be evaluated by using the Egger regression test. Results As of January 2023, a total of 3266 abstracts have been identified for screening. Data extraction is expected to commence in February 2023. Conclusions The topic of OAT and its effect on pregnancy is an understudied area that has the potential to improve health outcomes, clinical practice, education, and community advocacy. The results of our review will be used to inform clinical practice guidelines and improve health outcomes for pregnant people. Findings will be disseminated to diverse groups of stakeholders, including policy makers, clinicians, community partners, and individuals with lived experience of drug use. Trial Registration PROSPERO CRD42022332082; https://tinyurl.com/2p94pkx5 International Registered Report Identifier (IRRID) DERR1-10.2196/42417
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 | 0,040 | 0,056 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,004 |
| Méta-épidémiologie (sens large) | 0,018 | 0,017 |
| Bibliométrie | 0,014 | 0,014 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,007 | 0,008 |
| Science ouverte | 0,004 | 0,005 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,056 | 0,005 |
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 ».