Dataset Information

Clinical Outcomes of Warfarin Initiation in Advanced Chronic Kidney Disease Patients With Incident Atrial Fibrillation.

ABSTRACT:

Objectives

The aim of this study was to examine the efficacy and safety of warfarin initiation following the diagnosis of atrial fibrillation (AF) in patients with late-stage chronic kidney disease (CKD) who transitioned to dialysis.

Background

The clinical benefit of warfarin therapy for thromboprophylaxis after incident AF diagnosis in patients with late-stage CKD who are transitioning to dialysis is unknown.

Methods

In this retrospective cohort analysis, the study population was a national cohort of 22,771 U.S. veterans with incident end-stage renal disease who developed incident AF before initiating renal replacement therapy. This study examined the association of warfarin therapy following the diagnosis of incident AF with ischemic cerebrovascular accidents (CVAs) (ischemic stroke or transient ischemic attack), ischemic CVA-related hospitalization, major bleeding events (gastrointestinal or intracranial bleeding), bleeding event-related hospitalizations, and post-dialysis, all-cause mortality in multivariable adjusted Cox regression analyses that adjusted for demographic characteristics and comorbidities.

Results

The mean ± SD age of the cohort was 73.5 ± 8.8 years, 13% were African American, and the mean CHA₂DS₂-VASc score was 5.7 ± 2.1. Of the overall cohort, 6,682 (29.3%) patients were started on warfarin during the follow-up period. The hazard ratios (95% confidence intervals) for ischemic CVA, bleeding events, and death for those started on warfarin were 1.23 (1.16 to 1.30), 1.36 (1.29 to 1.44), and 0.94 (0.90 to 0.97), respectively, compared with those who received no anticoagulation. Warfarin exposure was associated with higher risk for ischemic CVA and bleeding event-related hospitalizations.

Conclusions

In patients with late-stage CKD who transitioned to dialysis, warfarin use was associated with higher risk of ischemic and bleeding events but a lower risk of mortality. Future studies such as those comparing warfarin with newer oral anticoagulant agents are needed to granularly define the net clinical benefit of anticoagulation therapy in patients with advanced CKD with incident AF.

SUBMITTER: Agarwal MA

PROVIDER: S-EPMC7872315 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background and objectivesAtrial fibrillation (AF) is common in CKD and associated with poor kidney and cardiovascular outcomes. Prediction models developed using novel methods may be useful to identify patients with CKD at highest risk of incident AF. We compared a previously published prediction model with models developed using machine learning methods in a CKD population.Design, setting, participants, & measurementsWe studied 2766 participants in the Chronic Renal Insufficiency Cohort study without prior AF with complete cardiac biomarker (N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin T) and clinical data. We evaluated the utility of machine learning methods as well as a previously validated clinical prediction model (Cohorts for Heart and Aging Research in Genomic Epidemiology [CHARGE]-AF, which included 11 predictors, using original and re-estimated coefficients) to predict incident AF. Discriminatory ability of each model was assessed using the ten-fold cross-validated C-index; calibration was evaluated graphically and with the Grønnesby and Borgan test.ResultsMean (SD) age of participants was 57 (11) years, 55% were men, 38% were Black, and mean (SD) eGFR was 45 (15) ml/min per 1.73 m2; 259 incident AF events occurred during a median of 8 years of follow-up. The CHARGE-AF prediction equation using original and re-estimated coefficients had C-indices of 0.67 (95% confidence interval, 0.64 to 0.71) and 0.67 (95% confidence interval, 0.64 to 0.70), respectively. A likelihood-based boosting model using clinical variables only had a C-index of 0.67 (95% confidence interval, 0.64 to 0.70); adding N-terminal pro-B-type natriuretic peptide, high-sensitivity troponin T, or both biomarkers improved the C-index by 0.04, 0.01, and 0.04, respectively. In addition to N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin T, the final model included age, non-Hispanic Black race/ethnicity, Hispanic race/ethnicity, cardiovascular disease, chronic obstructive pulmonary disease, myocardial infarction, peripheral vascular disease, use of angiotensin-converting enzyme inhibitor/angiotensin receptor blockers, calcium channel blockers, diuretics, height, and weight.ConclusionsUsing machine learning algorithms, a model that included 12 standard clinical variables and cardiac-specific biomarkers N-terminal pro-B-type natriuretic peptide and high-sensitivity troponin T had moderate discrimination for incident AF in a CKD population.

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