Use of continuous cardiac monitoring to assess the influence of atrial fibrillation burden and patterns on patient symptoms and healthcare utilization: The DEFINE AFib study.

Background: Atrial fibrillation (AF) has a significant impact on health and quality of life. The relationship of AF burden and temporal patterns of AF on patient symptoms, outcomes, and healthcare utilization is unknown. Insertable cardiac monitors (ICMs) are a strategic and as yet untapped, tool to investigate these relationships.

Molecular, cellular, and developmental organization of the mouse vomeronasal organ at single cell resolution.

We have generated single cell transcriptomic atlases of vomeronasal organs (VNO) from juvenile and adult mice. Combined with spatial molecular imaging, we uncover a distinct, previously unidentified class of cells that express the vomeronasal receptors (VRs) and a population of canonical olfactory sensory neurons in the VNO. High-resolution trajectory and cluster analyses reveal the lineage relationship, spatial distribution of cell types, and a putative cascade of molecular events that specify the V1r, V2r, and OR lineages from a common stem cell population.

Impact of atrial fibrillation and atrial fibrillation therapies on sports performance in athletes.

Background: It has been hypothesized that both atrial fibrillation (AF) and medications for AF are poorly tolerated in athletes.

Objective: The purpose of this study was to determine the impact of AF and AF treatments on sports performance.

Methods: An Internet-based survey, initiated via StopAfib.

Using Atrial Fibrillation Burden Trends and Machine Learning to Predict Near-Term Risk of Cardiovascular Hospitalization.

Background: Atrial fibrillation is associated with an increased risk of cardiovascular hospitalization (CVH), which may be triggered by changes in daily burden. Machine learning of dynamic trends in atrial fibrillation burden, as measured by insertable cardiac monitors (ICMs), may be useful in predicting near-term CVH.

Methods: Using Optum's deidentified Clinformatics Data Mart Database (2007-2019), linked with the Medtronic CareLink ICM database, we identified patients with >1 days of ICM-detected atrial fibrillation.

Performance of Atrial Fibrillation Burden Trends for Stroke Risk Stratification.

Background: Atrial fibrillation (AF) is associated with an increased risk of stroke, yet the limitations of conventional monitoring have restricted our understanding of AF burden risk thresholds. Predictive algorithms incorporating continuous AF burden measures may be useful for predicting stroke. This study evaluated the performance of temporal AF burden trends as predictors of stroke from a large cohort with insertable cardiac monitors.