Patterns of anticoagulant prescribing and renal function changes in patients with atrial fibrillation
Notice bibliographique
Résumé
Abstract Background The prevalence of atrial fibrillation (AF) is nearly three times higher in patients with chronic kidney disease (CKD) than the general population. These patients have an increased risk of stroke and systemic thromboembolism (SSE) as well as bleeding. The role for direct oral anticoagulants (DOACs) in those with advanced CKD and AF remains controversial. Studies show that patients on DOACs for AF with advanced CKD have similar risk of SSE and bleeding compared to those on warfarin, but these failed to account for changes in renal function over time. Purpose We sought to evaluate the pattern of oral anticoagulant prescribing, class switching, discontinuation and renal function trajectory in patients with AF in the last decade, coinciding with the development of DOACs. Methods Using linked administrative databases, we assessed patients 66 years of age and older with a new diagnosis of non-valvular AF between April 1, 2012 and March 31, 2020 who were started on oral anticoagulation within 90 days of diagnosis. Participants required a baseline serum creatinine (Cr) measurement in the year preceding AF diagnosis. Cr values were used to calculate the estimated glomerular filtration rate (eGFR) using the CKD Epidemiology Collaboration equation. Kidney function was tracked at baseline and longitudinally among patients prescribed DOACs versus warfarin using the Laboratories Information System. Anticoagulant class switching was tracked and discontinuation was defined if a new prescription for anticoagulation was not filled after 90 days of their last prescription ending. Results A total of 57,574 participants were included in the study; 48,662 were started on DOACs and 8,912 were started on warfarin. In April 2012, 83.8% of patients were prescribed warfarin; however, the proportion of first prescriptions significantly evolved over time to DOACs (Figure 1). Of those started on DOACs, 13,383 (27.5%) discontinued therapy, 34,918 (71.8%) remained on therapy and 361 (0.7%) switched to warfarin. The rate of discontinuation among those started on warfarin was higher with 4,144 (46.5%) stopping, 3,172 (35.6%) continuing therapy and 1,596 (17.9%) switching to DOACs. Most patients (75.6%) who switched to DOACs from warfarin remained on DOACs until the occurrence of dialysis, renal transplantation, death, or the last follow-up date (March 31, 2020). At baseline, the mean eGFR in the warfarin group was 56.2 compared with 66.3 mL/min/1.73 m2 in the DOAC group (p<0.01). Over the course of study, more than half of the subjects in both groups had a 20% or more decline in eGFR (Figure 2). Conclusion Given the degree of renal function decline and frequency of anticoagulant class switching in our cohort, existing observational studies comparing DOACs to warfarin in patients with AF and CKD may be limited. In order to better compare DOACs to warfarin in this population, time-varying covariates like renal function should be included in modelling. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): CIHR Foundation Grant
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 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 ».