Dataset Information

P Wave Indices-Advancing Our Understanding of Atrial Fibrillation-Related Cardiovascular Outcomes.

ABSTRACT: Atrial fibrillation (AF) is associated with an increased risk of ischemic stroke, heart failure, cognitive decline, dementia, myocardial infarction, sudden cardiac death (SCD), and all-cause death. Although these associations are firmly established, our understanding of the underlying mechanisms remains incomplete. Accumulating evidence suggests that left atrial (LA) abnormality or atrial cardiomyopathy may explain the relationship of AF to the aforementioned outcomes. P-wave indices (PWIs) reflect underlying atrial remodeling. In this mini review, we define representative PWIs, discuss state-of-the-art knowledge on the relationship between abnormal PWIs and AF-related cardiovascular outcomes (focusing on ischemic stroke and sudden cardiac death), and propose directions for future research. Our ultimate goal is to present a practical way forward to advance the emerging field of LA abnormality or atrial cardiomyopathy.

SUBMITTER: Chen LY

PROVIDER: S-EPMC6509260 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

P Wave Indices-Advancing Our Understanding of Atrial Fibrillation-Related Cardiovascular Outcomes.

Chen Lin Y LY Soliman Elsayed Z EZ

Frontiers in cardiovascular medicine 20190503

Atrial fibrillation (AF) is associated with an increased risk of ischemic stroke, heart failure, cognitive decline, dementia, myocardial infarction, sudden cardiac death (SCD), and all-cause death. Although these associations are firmly established, our understanding of the underlying mechanisms remains incomplete. Accumulating evidence suggests that left atrial (LA) abnormality or atrial cardiomyopathy may explain the relationship of AF to the aforementioned outcomes. P-wave indices (PWIs) refl ...[more]

PMID: 31131284

Similar Datasets

Project description:Atrial fibrillation (AF) has heterogeneous patterns of presentation concerning symptoms, duration of episodes, AF burden, and the tendency to progress towards the terminal step of permanent AF. AF is associated with a risk of stroke/thromboembolism traditionally considered dependent on patient-level risk factors rather than AF type, AF burden, or other characterizations. However, the time spent in AF appears related to an incremental risk of stroke, as suggested by the higher risk of stroke in patients with clinical AF vs. subclinical episodes and in patients with non-paroxysmal AF vs. paroxysmal AF. In patients with device-detected atrial tachyarrhythmias, AF burden is a dynamic process with potential transitions from a lower to a higher maximum daily arrhythmia burden, thus justifying monitoring its temporal evolution. In clinical terms, the appearance of the first episode of AF, the characterization of the arrhythmia in a specific AF type, the progression of AF, and the response to rhythm control therapies, as well as the clinical outcomes, are all conditioned by underlying heart disease, risk factors, and comorbidities. Improved understanding is needed on how to monitor and modulate the effect of factors that condition AF susceptibility and modulate AF-associated outcomes. The increasing use of wearables and apps in practice and clinical research may be useful to predict and quantify AF burden and assess AF susceptibility at the individual patient level. This may help us reveal why AF stops and starts again, or why AF episodes, or burden, cluster. Additionally, whether the distribution of burden is associated with variations in the propensity to thrombosis or other clinical adverse events. Combining the improved methods for data analysis, clinical and translational science could be the basis for the early identification of the subset of patients at risk of progressing to a longer duration/higher burden of AF and the associated adverse outcomes.

Project description:Anxiety and depression are associated with worse outcomes in several cardiovascular conditions, but it is unclear whether they affect outcomes in atrial fibrillation (AF). In a large diverse population of adults with AF, we evaluated the association of diagnosed anxiety and/or depression with stroke and bleeding outcomes.The Cardiovascular Research Network WAVE (Community-Based Control and Persistence of Warfarin Therapy and Associated Rates and Predictors of Adverse Clinical Events in Atrial Fibrillation and Venous Thromboembolism) Study included adults with AF newly starting warfarin between 2004 and 2007 within 5 health delivery systems in the United States. Diagnosed anxiety and depression and other patient characteristics were identified from electronic health records. We identified stroke and bleeding outcomes from hospitalization databases using validated International Classification of Diseases, Ninth Revision (ICD-9), codes. We used multivariable Cox regression to assess the relation between anxiety and/or depression with outcomes after adjustment for stroke and bleeding risk factors. In 25 570 adults with AF initiating warfarin, 490 had an ischemic stroke or intracranial hemorrhage (1.52 events per 100 person-years). In multivariable analyses, diagnosed anxiety was associated with a higher adjusted rate of combined ischemic stroke and intracranial hemorrhage (hazard ratio, 1.52; 95% confidence interval, 1.01-2.28). Results were not materially changed after additional adjustment for patient-level percentage of time in therapeutic anticoagulation range on warfarin (hazard ratio, 1.56; 95% confidence interval, 1.03-2.36). In contrast, neither isolated depression nor combined depression and anxiety were significantly associated with outcomes.Diagnosed anxiety was independently associated with increased risk of combined ischemic stroke and intracranial hemorrhage in adults with AF initiating warfarin that was not explained by differences in risk factors or achieved anticoagulation quality.

Dataset Information

P Wave Indices-Advancing Our Understanding of Atrial Fibrillation-Related Cardiovascular Outcomes.

Publications

P Wave Indices-Advancing Our Understanding of Atrial Fibrillation-Related Cardiovascular Outcomes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure