Therapy interruptions and drug interactions during acute hospitalization in patients taking direct acting antivirals for chronic hepatitis C virus infection: a retrospective cross-sectional study
Notice bibliographique
Résumé
Background: Direct acting antivirals (DAA) are highly effective antivirals targeting hepatitis C virus (HCV) with real-world efficacy exceeding 90%. However, DAAs are susceptible to drug interactions; and suboptimal treatment adherence has been associated with treatment failure. DAA therapy has historically been studied in the ambulatory setting, challenges associated with acute hospitalization during DAA therapy has not been previously evaluated. We investigated the frequency of therapy interruptions, and drug interactions in patients admitted to hospital while on DAA therapy. We examined drug interaction type, severity, and mitigation strategies by clinicians. Methods: We designed a retrospective cross-sectional study including all patients hospitalized while receiving active DAA therapy between January 1st, 2015 and June 30th, 2018. Eligibility criteria included all adults older than 18 years of age and receiving active DAA therapy as an outpatient. Baseline demographics were extracted electronically; therapy interruptions and drug interactions were identified through medical chart review. Treatment success was obtained through linking our database to the provincial virology laboratory database. Results: Fifty-seven hospitalizations occurred in 54 unique patients who were receiving DAA therapy. HCV therapy was interrupted in nearly one third of all hospitalizations (18/57) with the majority of cases (14/18) representing an unintentional therapy cessation. Median duration of therapy interruption was 1 day (IQR 0–1 day, range 0–46 days) Logistical delays in obtaining the patient’s own supply of DAAs was the most common reason for un-intentional therapy interruptions. Nearly two-thirds of patients were prescribed at least one new interacting medication during their hospital admission. Most drug interactions (78.7%) were not discovered nor addressed by clinicians. However, all patients except one (98%) achieved sustained virological response at week 24 (SVR24). Conclusions: DAA therapy interruptions and drug interactions were common in hospitalized patients. Clinician education, clinical decision support tools and availability of DAAs on hospital formularies can mitigate drug interactions and supply chain issues in order to optimize care for patients admitted to hospitals while receiving HCV DAA therapy.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».