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 versus subclinical episodes and in patients with non-paroxysmal AF versus 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.

Optimizing indices of AF susceptibility and burden to evaluate AF severity, risk and outcomes.

Beyond the 2020 guidelines on atrial fibrillation of the European society of cardiology.

Our aim was to assess the prevalence of unknown atrial fibrillation (AF) among adults during single-time point rhythm screening performed during meetings or social recreational activities organized by patient groups or volunteers. A total of 2814 subjects (median age 68 years) underwent AF screening by a handheld single-lead ECG device (MyDiagnostick). Overall, 56 subjects (2.0%) were diagnosed with AF, as a result of 12-lead ECG following a positive/suspected recording. Screening identified AF in 2.9% of the subjects ≥ 65 years. None of the 265 subjects aged below 50 years was found positive at AF screening. Risk stratification for unknown AF based on a CHA2DS2VASc > 0 in males and >1 in females (or CHA2DS2VA > 0) had a high sensitivity (98.2%) and a high negative predictive value (99.8%) for AF detection. A slightly lower sensitivity (96.4%) was achieved by using age ≥ 65 years as a risk stratifier. Conversely, raising the threshold at ≥75 years showed a low sensitivity. Within the subset of subjects aged ≥ 65 a CHA2DS2VASc > 1 in males and >2 in females, or a CHA2DS2VA > 1 had a high sensitivity (94.4%) and negative predictive value (99.3%), while age ≥ 75 was associated with a marked drop in sensitivity for AF detection.

https://www.mdpi.com/2077-0383/10/4/729/pdf

Clinical Factors Associated with Atrial Fibrillation Detection on Single-Time Point Screening Using a Hand-Held Single-Lead ECG Device.

Over time, atrial fibrillation (AF) naturally progresses from initially paroxysmal to persistent/permanent AF caused by structural and electrical remodelling with a complex underlying pathogenesis. It has been demonstrated that this progression of AF itself is linked to negative cardiovascular outcomes (stroke, systemic embolism, and hospitalization due to heart failure). Consequently, there is a profound rationale for early treatment of AF as a cornerstone of AF management. Recent randomized trials produced evidence that early rhythm control is effective in maintaining sinus rhythm, lower the risk of cardiovascular outcomes, and that catheter ablation of AF is effective to delay AF progression. This review will illuminate current evidence regarding the hypothesis of early AF treatment to prevent AF progression and improve clinical outcomes.

Atrial fibrillation progression and the importance of early treatment for improving clinical outcomes.

http://www.ejinme.com/article/S0953620522001625/pdf

Atrial cardiomyopathy markers and new-onset atrial fibrillation risk in patients with acute myocardial infarction.

Atrial fibrillation (AF) may progress from a non-permanent to a permanent form, and improvement in prediction may help in decision-making. In- and outpatients with non-permanent AF were enrolled in a prospective study and followed every 6 months. At baseline, 314 out of 523 patients (60%) had non-permanent AF (25.5% paroxysmal AF, 52.5% persistent, 2% first diagnosed AF). They were mostly males (188, 59.9%), median age 71 years [interquartile range (IQ) 62–77], median CHA2DS2VASc 3 (IQ 1–4), median HATCH score 1 (IQ 1–2). During a follow-up of 701 (IQ 437–902) days, 66 patients (21%) developed permanent AF. CHA2DS2VASc and HATCH scores were incrementally associated with AF progression (p for trend CHA2DS2VASc   2 (HR 0.358, 95%CI 0.162–0.791, p = 0.011) and valvular disease (HR 2.196, 95%CI 1.072–4.499, p = 0.032) were significantly associated with AF progression. Adding “moderate–severe LA dilation” to clinical scores, eg. HATCH score (HATCH-LA) with 2 points (Cox multivariable regression analysis) improved prediction of AF progression vs. HATCH score (p = 0.0225). In patients without permanent AF, progression of AF was independently associated with age, LA dilation, AF symptoms severity, antiarrhythmic drugs and valvular disease. Adding LA dilation (moderate–severe volume increase) to clinical scores improved prediction of progression to permanent AF.

Laura Melara

Papers

Atrial fibrillation pattern and factors affecting the progression to permanent atrial fibrillation