This study aimed to investigate the correlation between left atrial low-voltage areas (LVAs) and an arrhythmogenic superior vena cava (SVC) and the impact on the efficacy of an empiric SVC isolation (SVCI) along with a pulmonary vein isolation (PVI) of non-paroxysmal atrial fibrillation (non-PAF) with or without LVAs.

We retrospectively enrolled 153 consecutive patients with non-PAF who underwent a PVI alone (n=51) or empiric PVI plus an SVCI (n=102). Left atrial voltage maps were constructed during sinus rhythm to identify the LVAs (<0.5mV). An arrhythmogenic SVC was defined as firing from the SVC and an SVC associated with the maintenance of AF-like rapid SVC activity.

An arrhythmogenic SVC and LVAs were identified in 28% and 65% of patients with a PVI alone and 36% and 73% of patients with a PVI plus SVCI, respectively (

=.275 and

=.353). In the multivariate analysis a female gender, higher pulmonary artery systolic pressure (PAPs), and arrhythmogenic SVC were associated with the presence of LVAs. In the PVI plus SVCI strategy, there was no significant difference in the atrial tachyarrhythmia/AF-free survival between the patients with and without LVAs after initial and multiple sessions (50% vs. selleck 61%;

=.386, 73% vs. 79%;

=.530), however, differences were observed in the PVI alone group (27% vs. 61%;

=.018, 49% vs. 78%;

=.046).

The presence of LVAs was associated with an arrhythmogenic SVC. An SVCI may have the potential to compensate for an impaired outcome after a PVI in non-PAF patients with LVAs.

The presence of LVAs was associated with an arrhythmogenic SVC. An SVCI may have the potential to compensate for an impaired outcome after a PVI in non-PAF patients with LVAs.

There are several prognostic scores for the assessment of risk of atrial fibrillation (AF) recurrence post ablation procedure. However, the use of these complex scores is difficult and the validation on different populations brought divergent results. Our goal was to compare the performance of these risk scores as the basis for the development of a new, simplified score based only on few universally predictive variables.

All cryoballoon-based AF ablations performed in a single-center over a 10-year period were prospectively analyzed with regard to AF recurrence. This served to analyze the performance of APPLE, CAAP-AF, SCALE-CryoAF, MB-LATER, CHADS

, and CHA

DS

-VASc risk scores.

A total of 597 patients, mostly (78.1%) with paroxysmal AF were studied. Analyzed risk scores performed poorer than in the original publications because some risk factors were not predictive of AF recurrence. A simplified score named

, composed of just two universally predictive variables, AF type (1 point for

ersistent AF) and LA dimension (1 point for

A size >45mm) was developed. The 0-1-2 PL score stratified patients into low risk (

points), intermediate risk (

point), and high risk categories (

points) which were related to a 2-year risk of AF recurrence of 21%, 37%, and 55%, respectively. This score had C-statistics (0.620) higher/comparable to other investigated much more complex scores.

The assessment of risk of AF recurrence at the pre-ablation stage can be simplified without compromising accuracy. This could help to popularize risk assessment and standardization of AF management.

The assessment of risk of AF recurrence at the pre-ablation stage can be simplified without compromising accuracy. This could help to popularize risk assessment and standardization of AF management.

The association between atrial fibrillation (Afib) and sinus and AV nodal dysfunction has previously been reported. However, no data are available regarding the association between Afib and bundle branch block (BBB).

Patient data were obtained from the Nationwide Inpatient Sample (NIS) database between years 2009 and 2015. Patients with a diagnosis of Afib and BBB were identified using validated International Classification of Diseases, 9th revision, and Clinical Modification (ICD-9-CM) codes. Statistical analysis using the chi-square test and multivariate linear regression analysis were performed to determine the association between Afib and BBB.

The total number of patients with BBB was 3,116,204 (1.5%). Patients with BBB had a mean age of 73.5±13.5years, 53.6% were males, 39.1% belonged to the age group ≥80years, and 72.9% were Caucasians. The prevalence of Afib was higher in the BBB group, as compared to the non-BBB group (29% vs 11.8%, p value<.001). This association remained significant in multivariate regression analysis with an odds ratio of 1.25 (CI 1.24-1.25,

<.001). Among the subtypes of BBB, Afib was comparatively more associated with RBBB (1.32, CI 1.31-1.33, p value<.0001) than LBBB (1.17, CI 1.16-1.18, p value<.0001). The mean cost was higher among Afib with BBB, compared with Afib patients without BBB ($15795 vs $14391, p value<.0001). There was no significant difference in the mean length of stay (5.6 vs 5.9days, p value<.0001) or inpatient mortality (4.9% vs 4.8%).

This study demonstrates that prevalence of Afib is higher in patients with BBB than without BBB. Cost are higher for Afib patients with BBB, compared to those without BBB, with no significant increase in mortality or length of stay.

This study demonstrates that prevalence of Afib is higher in patients with BBB than without BBB. Cost are higher for Afib patients with BBB, compared to those without BBB, with no significant increase in mortality or length of stay.

Atrial fibrillation (Afib) is a common cardiac manifestation of hyperthyroidism. The data regarding outcomes of Afib with and without hyperthyroidism are lacking.

We hypothesized that patients with Afib and hyperthyroidism have better clinical outcomes, compared with Afib patients without hyperthyroidism.

We queried the National Inpatient Sample database for years 2015-2017 using Validated ICD-10-CM codes for Afib and hyperthyroidism. Patients were separated into two groups, Afib with hyperthyroidism and without hyperthyroidism.

The study was conducted with 68095278 patients. A total of 9727295 Afib patients were identified, 90635 (0.9%) had hyperthyroidism. The prevalence of hyperthyroidism was higher in patients with Afib (0.9% vs 0.4%,

<.001), compared with patients without Afib. Using multivariate regression analysis adjusting for various confounding factors, the odds ratio of Afib with hyperthyroidism was 2.08 (CI 2.07-2.10;

<.0001). Afib patients with hyperthyroidism were younger (71 vted with Afib in both univariate and multivariate analysis. Afib patients with hyperthyroidism have better clinical outcomes, compared with Afib patients without hyperthyroidism.

Patients with atrial fibrillation (AF) usually have a heterogeneous co-morbid history, with dynamic changes in risk factors impacting on multiple adverse outcomes. We investigated a large prospective cohort of patients with multimorbidity, using a machine-learning approach, accounting for the dynamic nature of comorbidity risks and incident AF.

Using machine-learning, we studied a prospective US cohort using medical/pharmacy databases of 1091911 patients, with an incident AF cohort of 14078 and non-AF cohort of 1077833 enrolled in the 4-year study. Five incident clinical outcomes (heart failure, stroke, myocardial infarction, major bleeding, and cognitive impairment) were examined in relationship to AF status (AF vs non-AF), diverse multi-morbid (conditions and medications) history, and demographic parameters (age and gender), with supervised machine-learning techniques.

Complex inter-relationships of various comorbidities were uncovered for AF cases, leading to 6-fold higher risk of heart failure relat for risk stratification and adverse clinical outcomes. This approach may facilitate automated approaches in the presence of multimorbidity, potentially helping decision making.

Complex multimorbidity relationships uncovered using a machine learning approach for incident AF cases have major consequences for integrated care management, with implications for risk stratification and adverse clinical outcomes. This approach may facilitate automated approaches in the presence of multimorbidity, potentially helping decision making.

Atrial fibrillation (AF) is characterized by the repetitive regeneration of unstable rotational events, the pivot of which are known as phase singularities (PSs). The spatial concentration and distribution of PSs have not been systematically investigated using quantitative statistical approaches.

We utilized a geospatial statistical approach to determine the presence of local spatial concentration and global clustering of PSs in biatrial human AF recordings.

64-electrode conventional basket (~5min, n=18 patients, persistent AF) recordings were studied. Phase maps were produced using a Hilbert-transform based approach. PSs were characterized spatially using the following approaches (i) local „hotspots“ of high phase singularity (PS) concentration using Getis-Ord Gi* (

≥1.96,

≤.05) and (ii) global spatial clustering using Moran’s

(inverse distance matrix).

Episodes of AF were analyzed from basket catheter recordings (H 41 epochs, 120000s, n=18 patients). The Getis-Ord Gi* statistic showed local PS hotspots in 12/41 basket recordings. As a metric of spatial clustering, Moran’s

showed an overall mean of 0.033 (95% CI 0.0003-0.065), consistent with the notion of complete spatial randomness.

Using a systematic, quantitative geospatial statistical approach, evidence for the existence of spatial concentrations („hotspots“) of PSs were detectable in human AF, along with evidence of spatial clustering. Geospatial statistical approaches offer a new approach to map and ablate PS clusters using substrate-based approaches.

Using a systematic, quantitative geospatial statistical approach, evidence for the existence of spatial concentrations („hotspots“) of PSs were detectable in human AF, along with evidence of spatial clustering. Geospatial statistical approaches offer a new approach to map and ablate PS clusters using substrate-based approaches.

Atrial fibrillationis the most clinically significant arrhythmia in humans when viewed both from a global and also a national perspective.In the United States, approximately 2.7-6.1 million people are estimated to have atrial fibrillation. With the aging of the population, this prevalence is on an increasing trend and remains an obstacle to cardiovascular health despite significant advancements specific to cardiovascular disease management.

In this specific group of patients, healthcare utilization is a concern from the public health perspective. Unfortunately, misconceptions dominate clinical decision making; for instance, the avoidance of safe and effective anticoagulation strategies in patients atthehighest risk for embolic strokes continues to be widespread in clinical practice and is often based on askewed assessment of risk versus benefit.Also, when there are contraindications to standard interventions foratrial fibrillation, a clear and nuanced understanding of second- and third-line interventions with proven benefit is often lacking.

An individualized approach should be followed byphysicians when managing atrial fibrillation in the elderly patient, taking into consideration the risk of complications, particularly the embolic stroke and the availability of treatment options for stroke prevention whether through pharmacological anticoagulation or left atrial appendage occluding devices. The following review sets out to clarify these issues.

An individualized approach should be followed by physicians when managing atrial fibrillation in the elderly patient, taking into consideration the risk of complications, particularly the embolic stroke and the availability of treatment options for stroke prevention whether through pharmacological anticoagulation or left atrial appendage occluding devices. The following review sets out to clarify these issues.