Comparing Medication Adherence Tools for the Direct Oral Anticoagulants Rivaroxaban and Apixaban
Notice bibliographique
Résumé
Abstract Introduction: Predictable pharmacokinetics and fixed dosing regimens of direct oral anticoagulants (DOACs) have simplified venous thromboembolism (VTE) treatment. Rivaroxaban and apixaban both target Factor Xa, yet an important difference lies in their dosing frequency. The impact of twice daily vs once daily DOAC dosing on adherence, and the potential differences on clinical efficacy and safety are unknown. Medication adherence was evaluated in the COBRRA (COmparison of Bleeding Risk between Rivaroxaban and Apixaban) Pilot study (NCT02559856). Aim: We compared anticoagulation adherence in patients with acute VTE using three different medication adherence assessment tools of variable cost. Methods: Patients with acute VTE were randomized to apixaban (10 mg twice daily for one week, then 5 mg twice daily) or rivaroxaban (15 mg twice daily for 3 weeks, then 20 mg daily). Participants at the sponsor site (The Ottawa Hospital) had anticoagulation adherence measured using eCAP™, medication diaries, and pill counts. eCAP™ is an electronic prescription bottle cap that records each time the vial is opened to take a tablet. The information was downloaded to a desktop reader at follow up visits to determine medication adherence. Medication diaries were completed by patients and recorded date and time of taking anticoagulant. Pill counts were conducted by the research coordinator at follow up visits and adherence was determined using the following calculation: number of pills taken/number of pills dispensed. Anticoagulation adherence was assessed at day 30 and end of treatment. Measurements of Results: Forty patients were enrolled and data is available for 39. Twenty patients were randomized to apixaban with mean age 59 years; 19 patients were randomized to rivaroxaban and had mean age of 64 years. In patients receiving twice daily apixaban, all adherence tools demonstrated similar anticoagulation adherence rates at day 30 follow up with mean of 95.7% for eCAP™, 97% for diaries, and 97.8% by pill count. End of treatment measures were also similar: 91.1%, 98%, and 90.4%, respectively. All three tools showed comparable adherence rates at 30 days with mean of 99.3% by eCAP™, 97.5% with diaries, and 99.4% by pill counts in patients on rivaroxaban treatment. By end of treatment, anticoagulation adherence rates were similar between different measurement tools: 95.8%, 97.5%, and 99.5%, respectively (Table 1). Conclusions: In patients with acute VTE, anticoagulation adherence rates were comparable regardless of the adherence assessment tool used. We also demonstrated that simple tools such as medication diaries and pill counts are comparable to expensive electronic device measures. Download : Download high-res image (155KB) Download : Download full-size image Disclosures Castellucci: BMS: Honoraria; Bayer: Honoraria; Leo Pharma: Honoraria; Boehringer-Ingelheim: Honoraria; Pfizer: Honoraria. Le Gal: Bayer: Honoraria; BMS: Honoraria.
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 | 0,007 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| 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) | 0,003 | 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 ».