Reasons for Switching from Warfarin to a Direct Oral Anticoagulant: A Retrospective Study
Notice bibliographique
Résumé
Abstract Background: Direct oral anticoagulants (DOACs) are slowly replacing warfarin for the prevention of stroke in atrial fibrillation and treatment and secondary prevention of venous thromboembolism. Patients with poor time in therapeutic range (TTR) are often switched to a DOAC. Poor TTR can be due to drug interactions but if the reason is poor compliance, outcomes could be worse using a DOAC without monitoring. Methods: To understand the compliance patterns we performed a retrospective chart review in patients from the anticoagulation clinic at Hamilton General Hospital that were switched from warfarin to a DOAC from April 2013 to April 2018. Patients who were taking warfarin for ≥ 2 months for any indication, except for mechanical valve prosthesis, and who were switched to a DOAC were included. We excluded patients who had a DOAC-to-DOAC switch, patients who had no reported TTR available, and those who were temporarily on warfarin after cardiac surgery. The documented reasons for a switch from warfarin to a DOAC were compared between patients with TTR ≤ 60% and >60%. Non-adherence to international normalized ratio (INR) monitoring was considered if >20% of tests were not done or delayed for more than 2 days. Results: A total of 643 eligible patients were initially screened and 288 patients were excluded: 179 had no available TTR, 93 were temporarily on warfarin after cardiac surgery, 11 were not actually switched from warfarin to a DOAC, and 5 had a DOAC-to-DOAC switch. The remaining 355 patients were included in the analysis: 223 had a TTR ≤ 60% and 132 patients had a TTR >60%. There were no differences in the median age or gender distribution. The most common indication for anticoagulation was atrial fibrillation in both groups. The median TTR was 43% in the TTR ≤ 60% group and 71% in the TTR >60% group. The median duration on anticoagulation with warfarin was significantly longer for the TTR >60% group compared with the TTR ≤ 60% group (42 months versus 19 months; P <0.001). Apixaban was the most common DOAC of choice for the switch in both groups. The most common documented reasons for a switch in the group with a TTR >60% were: switch by another physician for unknown reason (n=36), bleeding (n=30), and patient preference (n=20). The most common reasons for a switch in those with a TTR ≤ 60% were: unstable INR readings (n=42), drug interactions (n=33), and bleeding (n=30). There was no significant difference in the rate of non-adherence with the scheduled INR monitoring (42% in the group with a TTR >60% versus 49% in those with a TTR ≤ 60%). Conclusion: We found that about half of the patients on chronic anticoagulation with warfarin and switched to a DOAC were non-adherent with the scheduled INR monitoring. This, in combination with low TTR, should alert the physician of possible non-compliance with taking DOACs. Further prospective studies are needed to examine the DOAC adherence rate and clinical outcomes in this specific population. Disclosures Schulman: Boehringer-Ingelheim: Honoraria, Research Funding; Daiichi-Sankyo: Honoraria; Sanofi: Honoraria; Bayer: 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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| 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 ».