Dynamics of Atrial Fibrillation Mechanisms and Comorbidities

Identification of key differentially expressed immune related genes in patients with persistent atrial fibrillation: an integrated bioinformation analysis

OBJECTIVE

We aimed to investigate key differentially expressed immune related genes in persistent atrial fibrillation.

METHODS

Gene expression profiles were downloaded from Gene Expression Omnibus (GEO) using "GEO query" package. "limma" package and "sva" package were used to conduct normalization and eliminate batch effects, respectively. We screened out differentially expressed genes (DEGs) based on "limma" package with the standard of |log fold change (FC)| ≥ 1.5 and false discovery rate (FDR) < 0.05. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were performed by "clusterProfler" package. We further applied LASSO to select key DEGs, and intersected key DEGs with immune related genes from ImmPort database. The ROC curve of each DEIRG was constructed to evaluate its diagnostic efficiency for AF.

RESULTS

A total of 103 DEGs we were screened out, of them, 48 genes were down-regulated and 55 genes were up-regulated. Result of functional enrichment analysis show that, most of DEGs were related to immune response, inflammation, and oxidative stress. Ultimately, CYBB, RORB, S100A12, and CHGB were determined as key DEIRGs, each of which displayed a favor efficiency for diagnosing persistent AF.

CONCLUSION

CYBB, RORB, S100A12, and CHGB were identified as key DEIRGs in persistent AF, and future studies are needed to further explore the underlying roles of CYBB, RORB, S100A12, and CHGB in persistent AF.

Impact of Persistent Versus Paroxysmal Preoperative Atrial Fibrillation on In-Hospital, One-Year, and Late Clinical Outcomes Following Transcatheter Aortic Valve Implantation

Previous reports on the impact of preexisting atrial fibrillation (AF) on clinical outcomes after transcatheter aortic valve implantation (TAVI) have presented limited data on the relative impact of paroxysmal versus persistent AF subtypes. We compared in-hospital, 1-year, and late clinical outcomes in 1,098 patients who underwent TAVI with preoperative AF (556 paroxysmal, 542 persistent) versus 1,787 patients without AF. The propensity-matched cohorts with AF (n = 643) and without AF (n = 686) did not differ with respect to baseline clinical characteristics, operative technique, or in-hospital TAVI complications. At 1-year, patients with AF had higher all-cause mortality (9.0% vs 6.1%, p = 0.046) and readmission rates (13.1 vs 8.8%, p = 0.014), with lower Kansas City cardiomyopathy questionnaire scores (77.8 ± 21.8 vs 84.3 ± 17.1, p <0.001). Echocardiographic follow-up (mean time 455 ± 285 days) demonstrated no significant intergroup differences in hemodynamic findings other than a progressive increase in left atrial volume index in patient subgroups (without AF: 37.4 ± 14.7 ml/m2 vs paroxysmal AF: 46.4 ± 21.4 ml/m2 vs persistent AF: 60.5 ± 26.3 ml/m2, p <0.001). On late follow-up (mean time 49.0 [45.1 to 52.9] months), patients with persistent AF had worse all-cause mortality than patients without AF (hazard ratio 1.55, 95% confidence interval 1.17 to 2.06, p = 0.003), with no significant survival differences between the paroxysmal AF and without AF subgroups. In conclusion, patients with preexisting AF and patients without AF who underwent TAVI had similar in-hospital outcomes but worse 1-year mortality, hospital readmission, and quality of life outcomes. Compared with patients without AF, patients with persistent but not paroxysmal preexisting AF have higher late all-cause mortality at a mean follow-up of 49 months. Patients with persistent AF have higher levels of left atrial volume index than patients with paroxysmal AF and patients without AF on intermediate echocardiographic follow-up.

Compartmentalization proteomics revealed endolysosomal protein network changes in a goat model of atrial fibrillation

Endolysosomes (EL) are known for their role in regulating both intracellular trafficking and proteostasis. EL facilitate the elimination of damaged membranes, protein aggregates, membranous organelles and play an important role in calcium signaling. The specific role of EL in cardiac atrial fibrillation (AF) is not well understood. We isolated atrial EL organelles from AF goat biopsies and conducted a comprehensive integrated omics analysis to study the EL-specific proteins and pathways. We also performed electron tomography, protein and enzyme assays on these biopsies. Our results revealed the upregulation of the AMPK pathway and the expression of EL-specific proteins that were not found in whole tissue lysates, including GAA, DYNLRB1, CLTB, SIRT3, CCT2, and muscle-specific HSPB2. We also observed structural anomalies, such as autophagic-vacuole formation, irregularly shaped mitochondria, and glycogen deposition. Our results provide molecular information suggesting EL play a role in AF disease process over extended time frames.

Artificial-intelligence-based risk prediction and mechanism discovery for atrial fibrillation using heart beat-to-beat intervals

BACKGROUND

Early diagnosis of atrial fibrillation (AF) is important for preventing stroke and other complications. Predicting AF risk in advance can improve early diagnostic efficiency. Deep learning has been used for disease risk prediction; however, it lacks adherence to evidence-based medicine standards. Identifying the underlying mechanisms behind disease risk prediction is important and required.

METHODS

We developed an explainable deep learning model called HBBI-AI to predict AF risk using only heart beat-to-beat intervals (HBBIs) during sinus rhythm. We proposed a possible AF mechanism based on the model's explainability and verified this conjecture using confirmed AF risk factors while also examining new AF risk factors. Finally, we investigated the changes in clinicians' ability to predict AF risk using only HBBIs before and after learning the model's explainability.

FINDINGS

HBBI-AI consistently performed well across large in-house and external public datasets. HBBIs with large changes or extreme stability were critical predictors for increased AF risk, and the underlying cause was autonomic imbalance. We verified various AF risk factors and discovered that autonomic imbalance was associated with all these factors. Finally, cardiologists effectively understood and learned from these findings to improve their abilities in AF risk prediction.

CONCLUSIONS

HBBI-AI effectively predicted AF risk using only HBBI information through evaluating autonomic imbalance. Autonomic imbalance may play an important role in many risk factors of AF rather than in a limited number of risk factors.

FUNDING

This study was supported in part by the National Key R&D Program and the National Natural Science Foundation of China.

Longer and better lives for patients with atrial fibrillation: the 9th AFNET/EHRA consensus conference

AIMS

Recent trial data demonstrate beneficial effects of active rhythm management in patients with atrial fibrillation (AF) and support the concept that a low arrhythmia burden is associated with a low risk of AF-related complications. The aim of this document is to summarize the key outcomes of the 9th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA).

METHODS AND RESULTS

Eighty-three international experts met in Münster for 2 days in September 2023. Key findings are as follows: (i) Active rhythm management should be part of the default initial treatment for all suitable patients with AF. (ii) Patients with device-detected AF have a low burden of AF and a low risk of stroke. Anticoagulation prevents some strokes and also increases major but non-lethal bleeding. (iii) More research is needed to improve stroke risk prediction in patients with AF, especially in those with a low AF burden. Biomolecules, genetics, and imaging can support this. (iv) The presence of AF should trigger systematic workup and comprehensive treatment of concomitant cardiovascular conditions. (v) Machine learning algorithms have been used to improve detection or likely development of AF. Cooperation between clinicians and data scientists is needed to leverage the potential of data science applications for patients with AF.

CONCLUSIONS

Patients with AF and a low arrhythmia burden have a lower risk of stroke and other cardiovascular events than those with a high arrhythmia burden. Combining active rhythm control, anticoagulation, rate control, and therapy of concomitant cardiovascular conditions can improve the lives of patients with AF.

Optoelectronic control of cardiac rhythm: Toward shock-free ambulatory cardioversion of atrial fibrillation

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia, progressive in nature, and known to have a negative impact on mortality, morbidity, and quality of life. Patients requiring acute termination of AF to restore sinus rhythm are subjected to electrical cardioversion, which requires sedation and therefore hospitalization due to pain resulting from the electrical shocks. However, considering the progressive nature of AF and its detrimental effects, there is a clear need for acute out-of-hospital (i.e., ambulatory) cardioversion of AF. In the search for shock-free cardioversion methods to realize such ambulatory therapy, a method referred to as optogenetics has been put forward. Optogenetics enables optical control over the electrical activity of cardiomyocytes by targeted expression of light-activated ion channels or pumps and may therefore serve as a means for cardioversion. First proof-of-principle for such light-induced cardioversion came from in vitro studies, proving optogenetic AF termination to be very effective. Later, these results were confirmed in various rodent models of AF using different transgenes, illumination methods, and protocols, whereas computational studies in the human heart provided additional translational insight. Based on these results and fueled by recent advances in molecular biology, gene therapy, and optoelectronic engineering, a basis is now being formed to explore clinical translations of optoelectronic control of cardiac rhythm. In this review, we discuss the current literature regarding optogenetic cardioversion of AF to restore normal rhythm in a shock-free manner. Moreover, key translational steps will be discussed, both from a biological and technological point of view, to outline a path toward realizing acute shock-free ambulatory termination of AF.

Bioinformatics analysis reveals the potential common genes and immune characteristics between atrial fibrillation and periodontitis

BACKGROUND AND OBJECTIVE

Atrial fibrillation (AF) and periodontitis, both classified under chronic inflammatory diseases, share common etiologies, including genetic factors and immune pathways. However, the exact mechanisms are still poorly understood. This study aimed to explore the potential common genes and immune characteristics between AF and periodontitis.

METHODS

Gene expression datasets for AF and periodontitis were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis was used to identify common genes in the training set. Functional analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, were conducted to elucidate the underlying mechanisms. Hub genes were further screened based on expression levels, receiver operating characteristic (ROC) curves, and least absolute shrinkage and selection operator (LASSO) regression. Then, based on the expression levels and ROC values of the hub genes in the validation set, the target genes were identified. Finally, immune cell infiltration analysis was performed on the AF and periodontitis datasets in the training set using the "CIBERSORT" R package. The relationships between target genes, infiltrating immune cells, and inflammatory factors were also investigated. In addition, AF susceptibility, atrial fibrosis, inflammatory infiltration, and RGS1 protein expression in rat models of periodontitis were assessed through in vivo electrophysiology experiments, Masson's trichrome staining, hematoxylin-eosin staining, immunohistochemistry, and western blotting, respectively.

RESULTS

A total of 21 common genes were identified between AF and periodontitis among the differentially expressed genes. After evaluating gene expression levels, ROC curves, and LASSO analysis, four significant genes between AF and periodontitis were identified, namely regulator of G-protein signaling 1 (RGS1), annexin A6 (ANXA6), solute carrier family 27 member 6 (SLC27A6), and ficolin 1 (FCN1). Further validation confirmed that RGS1 was the optimal shared target gene for AF and periodontitis. Immune cell infiltration analysis revealed that neutrophils and T cells play an important role in the pathogenesis of both diseases. RGS1 showed a significant positive correlation with activated memory CD4 T cells and gamma-delta T cells and a negative correlation with CD8 T cells and regulatory T cells in both training sets. Moreover, RGS1 was positively correlated with classical pro-inflammatory cytokines IL1β and IL6. In periodontitis rat models, AF susceptibility, atrial fibrosis, and inflammatory infiltration were significantly increased, and RGS1 expression in the atrial tissue was upregulated.

CONCLUSION

A common gene between AF and periodontitis, RGS1 appears central in linking the two conditions. Immune and inflammatory responses may underlie the interaction between AF and periodontitis.

Evaluation of Clinical, Echocardiographic, and Therapeutic Characteristics, and Prognostic Outcomes of Coexisting Heart Failure among Patients with Atrial Fibrillation: The Jordan Atrial Fibrillation (JoFib) Study

BACKGROUND

Atrial fibrillation (AF) is the most commonly encountered cardiac arrhythmia in clinical practice. Heart failure (HF) can occur concurrently with AF.

AIM

We compared different demographic, clinical, and echocardiographic characteristics between patients with AF+HF and patients with AF only. Furthermore, we explored whether concurrent HF independently predicts several outcomes (all-cause mortality, cardiovascular mortality, ischemic stroke/systemic embolism (IS/SE), major bleeding, and clinically relevant non-major bleeding (CRNMB)).

MATERIALS AND METHODS

Comparisons between the AF+HF and the AF-only group were carried out. Multivariable Cox proportional hazard models were constructed for each outcome to assess whether HF was predictive of any of them while controlling for possible confounding factors.

RESULTS

A total of 2020 patients were included in this study: 481 had AF+HF; 1539 had AF only. AF+HF patients were older, more commonly males, and had a higher prevalence of diabetes mellitus, dyslipidemia, coronary artery disease, and chronic kidney disease (p≤0.05). Furthermore, AF+HF patients more commonly had pulmonary hypertension and low ejection fraction (p≤0.001). Finally, HF was independently predictive of all-cause mortality (adjusted HR 2.17, 95% CI (1.66-2.85) and cardiovascular mortality (adjusted HR 2.37, 95% CI (1.68-3.36).

CONCLUSION

Coexisting AF+HF was associated with a more labile and higher-risk population among Jordanian patients. Furthermore, coexisting HF independently predicted higher all-cause mortality and cardiovascular mortality. Efforts should be made to efficiently identify such cases early and treat them aggressively.

Heart Failure, Female Sex, and Atrial Fibrillation Are the Main Drivers of Human Atrial Cardiomyopathy: Results From the CATCH ME Consortium

BACKGROUND

Atrial cardiomyopathy (atCM) is an emerging prognostic factor in cardiovascular disease. Fibrotic remodeling, cardiomyocyte hypertrophy, and capillary density are hallmarks of atCM. The contribution of etiological factors and atrial fibrillation (AF) to the development of differential atCM phenotypes has not been quantified. This study aimed to evaluate the association between histological features of atCM and the clinical phenotype.

METHODS AND RESULTS

We examined left atrial (LA, n=95) and right atrial (RA, n=76) appendages from a European cohort of patients undergoing cardiac surgery. Quantification of histological atCM features was performed following wheat germ agglutinin/CD31/vimentin staining. The contributions of AF, heart failure, sex, and age to histological characteristics were determined with multiple linear regression models. Persistent AF was associated with increased endomysial fibrosis (LA: +1.13±0.47 μm, P=0.038; RA: +0.94±0.38 μm, P=0.041), whereas total extracellular matrix content was not. Men had larger cardiomyocytes (LA: +1.92±0.72 μm, P<0.001), while women had more endomysial fibrosis (LA: +0.99±0.56 μm, P=0.003). Patients with heart failure showed more endomysial fibrosis (LA: +1.85±0.48 μm, P<0.001) and extracellular matrix content (LA: +3.07±1.29%, P=0.016), and a higher capillary density (LA: +0.13±0.06, P=0.007) and size (LA: +0.46±0.22 μm, P=0.044). Fuzzy k-means clustering of histological features identified 2 subtypes of atCM: 1 characterized by enhanced endomysial fibrosis (LA: +3.17 μm, P<0.001; RA: +2.86 μm, P<0.001), extracellular matrix content (LA: +3.53%, P<0.001; RA: +6.40%, P<0.001) and fibroblast density (LA: +4.38%, P<0.001), and 1 characterized by cardiomyocyte hypertrophy (LA: +1.16 μm, P=0.008; RA: +2.58 μm, P<0.001). Patients with fibrotic atCM were more frequently female (LA: odds ratio [OR], 1.33, P=0.002; RA: OR, 1.54, P=0.004), with persistent AF (LA: OR, 1.22, P=0.036) or heart failure (LA: OR, 1.62, P<0.001). Hypertrophic features were more common in men (LA: OR=1.33, P=0.002; RA: OR, 1.54, P=0.004).

CONCLUSIONS

Fibrotic atCM is associated with female sex, persistent AF, and heart failure, while hypertrophic features are more common in men.

What determines the optimal pharmacological treatment of atrial fibrillation? Insights from in silico trials in 800 virtual atria

The best pharmacological treatment for each atrial fibrillation (AF) patient is unclear. We aim to exploit AF simulations in 800 virtual atria to identify key patient characteristics that guide the optimal selection of anti-arrhythmic drugs. The virtual cohort considered variability in electrophysiology and low voltage areas (LVA) and was developed and validated against experimental and clinical data from ionic currents to ECG. AF sustained in 494 (62%) atria, with large inward rectifier K+ current (IK1 ) and Na+ /K+ pump (INaK ) densities (IK1 0.11 ± 0.03 vs. 0.07 ± 0.03 S mF-1 ; INaK 0.68 ± 0.15 vs. 0.38 ± 26 S mF-1 ; sustained vs. un-sustained AF). In severely remodelled left atrium, with LVA extensions of more than 40% in the posterior wall, higher IK1 (median density 0.12 ± 0.02 S mF-1 ) was required for AF maintenance, and rotors localized in healthy right atrium. For lower LVA extensions, rotors could also anchor to LVA, in atria presenting short refractoriness (median L-type Ca2+ current, ICaL , density 0.08 ± 0.03 S mF-1 ). This atrial refractoriness, modulated by ICaL and fast Na+ current (INa ), determined pharmacological treatment success for both small and large LVA. Vernakalant was effective in atria presenting long refractoriness (median ICaL density 0.13 ± 0.05 S mF-1 ). For short refractoriness, atria with high INa (median density 8.92 ± 2.59 S mF-1 ) responded more favourably to amiodarone than flecainide, and the opposite was found in atria with low INa (median density 5.33 ± 1.41 S mF-1 ). In silico drug trials in 800 human atria identify inward currents as critical for optimal stratification of AF patient to pharmacological treatment and, together with the left atrial LVA extension, for accurately phenotyping AF dynamics. KEY POINTS: Atrial fibrillation (AF) maintenance is facilitated by small L-type Ca2+ current (ICaL ) and large inward rectifier K+ current (IK1 ) and Na+ /K+ pump. In severely remodelled left atrium, with low voltage areas (LVA) covering more than 40% of the posterior wall, sustained AF requires higher IK1 and rotors localize in healthy right atrium. For lower LVA extensions, rotors can also anchor to LVA, if the atria present short refractoriness (low ICaL ) Vernakalant is effective in atria presenting long refractoriness (high ICaL ). For short refractoriness, atria with fast Na+ current (INa ) up-regulation respond more favourably to amiodarone than flecainide, and the opposite is found in atria with low INa . The inward currents (ICaL and INa ) are critical for optimal stratification of AF patient to pharmacological treatment and, together with the left atrial LVA extension, for accurately phenotyping AF dynamics.

No causal genetic relationships between atrial fibrillation and vascular dementia: A bidirectional Mendelian randomization study

Background

Numerous observational studies have suggested that atrial fibrillation (AF) was associated with an increased risk of vascular dementia (VaD). However, the causal genetic relationships between AF and VaD remains unclear. To evaluate the effect of AF on VaD, we performed the Mendelian randomization (MR) analysis to investigate the causal genetic relationships between AF and VaD.

Methods

The bidirectional MR analysis was conducted to explore the causal relationships between exposure and disease. We applied a series of quality assessments to select significantly and independently single nucleotide polymorphisms (SNPs) from publicly available large-scale genome-wide association studies (GWAS) databases. Three methods [Inverse variance weighted method (IVW), MR-Egger method, and weighted median (WM)method] were used to derive MR estimates. In order to ensure reliable MR results, sensitivity analyses were performed to evaluate the horizontal pleiotropy and heterogeneity.

Results

Our MR analyses revealed no significant genetic relationships between AF and the risk of VaD (IVW: OR =  1.10, 95%CI = 0.95-1.28, P = 0.20). In the reverse direction analysis, there was no evidence to support a significant genetic relationship of VaD with AF risk (IVW: OR =  1.00, 95% CI = 0.99-1.01, P = 0.52). Consistent results were obtained using different MR methods. Sensitivity analyses suggested no significant horizontal pleiotropy and heterogeneity in the study.

Conclusion

This MR analysis did not provide evidence to support the causal genetic relationships between AF on VaD risk and the causal effect of VaD on AF risk.

Cell to whole organ global sensitivity analysis on a four-chamber heart electromechanics model using Gaussian processes emulators

Cardiac pump function arises from a series of highly orchestrated events across multiple scales. Computational electromechanics can encode these events in physics-constrained models. However, the large number of parameters in these models has made the systematic study of the link between cellular, tissue, and organ scale parameters to whole heart physiology challenging. A patient-specific anatomical heart model, or digital twin, was created. Cellular ionic dynamics and contraction were simulated with the Courtemanche-Land and the ToR-ORd-Land models for the atria and the ventricles, respectively. Whole heart contraction was coupled with the circulatory system, simulated with CircAdapt, while accounting for the effect of the pericardium on cardiac motion. The four-chamber electromechanics framework resulted in 117 parameters of interest. The model was broken into five hierarchical sub-models: tissue electrophysiology, ToR-ORd-Land model, Courtemanche-Land model, passive mechanics and CircAdapt. For each sub-model, we trained Gaussian processes emulators (GPEs) that were then used to perform a global sensitivity analysis (GSA) to retain parameters explaining 90% of the total sensitivity for subsequent analysis. We identified 45 out of 117 parameters that were important for whole heart function. We performed a GSA over these 45 parameters and identified the systemic and pulmonary peripheral resistance as being critical parameters for a wide range of volumetric and hemodynamic cardiac indexes across all four chambers. We have shown that GPEs provide a robust method for mapping between cellular properties and clinical measurements. This could be applied to identify parameters that can be calibrated in patient-specific models or digital twins, and to link cellular function to clinical indexes.

Advances in basic and translational research in atrial fibrillation

Atrial fibrillation (AF) is a very common cardiac arrhythmia with an estimated prevalence of 33.5 million patients globally. It is associated with an increased risk of death, stroke and peripheral embolism. Although genetic studies have identified a growing number of genes associated with AF, the definitive impact of these genetic findings is yet to be established. Several mechanisms, including electrical, structural and neural remodelling of atrial tissue, have been proposed to contribute to the development of AF. Despite over a century of exploration, the molecular and cellular mechanisms underlying AF have not been fully established. Current antiarrhythmic drugs are associated with a significant rate of adverse events and management of AF using ablation is not optimal, especially in cases of persistent AF. This review discusses recent advances in our understanding and management of AF, including new concepts of epidemiology, genetics and pathophysiological mechanisms. We review the current status of antiarrhythmic drug therapy for AF, new potential agents, as well as mechanism-based AF ablation. This article is part of the theme issue 'The heartbeat: its molecular basis and physiological mechanisms'.

Atrial fibrillation: primary prevention, secondary prevention, and prevention of thromboembolic complications: part 1

Atrial fibrillation (AF), is the most common sustained cardiac arrhythmia. It was once thought to be benign as long as the ventricular rate was controlled, however, AF is associated with significant cardiac morbidity and mortality. Increasing life expectancy driven by improved health care and decreased fertility rates has, in most of the world, resulted in the population aged ≥65 years growing more rapidly than the overall population. As the population ages, projections suggest that the burden of AF may increase more than 60% by 2050. Although considerable progress has been made in the treatment and management of AF, primary prevention, secondary prevention, and prevention of thromboembolic complications remain a work in progress. This narrative review was facilitated by a MEDLINE search to identify peer-reviewed clinical trials, randomized controlled trials, meta-analyses, and other clinically relevant studies. The search was limited to English-language reports published between 1950 and 2021. Atrial fibrillation was searched via the terms primary prevention, hyperthyroidism, Wolff-Parkinson-White syndrome, catheter ablation, surgical ablation, hybrid ablation, stroke prevention, anticoagulation, left atrial occlusion and atrial excision. Google and Google scholar as well as bibliographies of identified articles were reviewed for additional references. In these two manuscripts, we discuss the current strategies available to prevent AF, then compare noninvasive and invasive treatment strategies to diminish AF recurrence. In addition, we examine the pharmacological, percutaneous device and surgical approaches to prevent stroke as well as other types of thromboembolic events.

Time of onset of atrial fibrillation and atrial fibrillation progression data from the RACE V study

AIMS

Atrial fibrillation (AF) progression is associated with adverse outcome, but the role of the circadian or diurnal pattern of AF onset remains unclear. We aim to assess the association between the time of onset of AF episodes with the clinical phenotype and AF progression in patients with self-terminating AF.

METHODS AND RESULTS

The Reappraisal of AF: Interaction Between Hypercoagulability, Electrical Remodelling, and Vascular Destabilization in the Progression of AF study included patients with self-terminating AF who underwent extensive phenotyping at baseline and continuous rhythm monitoring with an implantable loop recorder (ILR). In this subanalysis, ILR data were used to assess the development of AF progression and the diurnal pattern of AF onset: predominant (>80%) nocturnal AF, predominant daytime AF, or mixed AF without a predominant diurnal AF pattern. The median follow-up was 2.2 (1.6-2.8) years. The median age was 66 (59-71) years, and 117 (42%) were women. Predominant nocturnal (n = 40) and daytime (n = 43) AF onset patients had less comorbidities compared to that of mixed (n = 195) AF patients (median 2 vs. 2 vs. 3, respectively, P = 0.012). Diabetes was more common in the mixed group (12% vs. 5% vs. 0%, respectively, P = 0.031), whilst obesity was more frequent in the nocturnal group (38% vs. 12% vs. 27%, respectively, P = 0.028). Progression rates in the nocturnal vs. daytime vs. mixed groups were 5% vs. 5% vs. 24%, respectively (P = 0.013 nocturnal vs. mixed and P = 0.008 daytime vs. mixed group, respectively).

CONCLUSION

In self-terminating AF, patients with either predominant nocturnal or daytime onset of AF episodes had less associated comorbidities and less AF progression compared to that of patients with mixed onset of AF.

CLINICAL TRIAL REGISTRATION

NCT02726698.

Biomarkers of Atrial Fibrillation Recurrence in Patients with Paroxysmal or Persistent Atrial Fibrillation Following External Direct Current Electrical Cardioversion

Atrial fibrillation (AF) is associated with atrial remodeling, cardiac dysfunction, and poor clinical outcomes. External direct current electrical cardioversion is a well-developed urgent treatment strategy for patients presenting with recent-onset AF. However, there is a lack of accurate predictive serum biomarkers to identify the risks of AF relapse after electrical cardioversion. We reviewed the currently available data and interpreted the findings of several studies revealing biomarkers for crucial elements in the pathogenesis of AF and affecting cardiac remodeling, fibrosis, inflammation, endothelial dysfunction, oxidative stress, adipose tissue dysfunction, myopathy, and mitochondrial dysfunction. Although there is ample strong evidence that elevated levels of numerous biomarkers (such as natriuretic peptides, C-reactive protein, galectin-3, soluble suppressor tumorigenicity-2, fibroblast growth factor-23, turn-over collagen biomarkers, growth differential factor-15) are associated with AF occurrence, the data obtained in clinical studies seem to be controversial in terms of their predictive ability for post-cardioversion outcomes. Novel circulating biomarkers are needed to elucidate the modality of this approach compared with conventional predictive tools. Conclusions: Biomarker-based strategies for predicting events after AF treatment require extensive investigation in the future, especially in the presence of different gender and variable comorbidity profiles. Perhaps, a multiple biomarker approach exerts more utilization for patients with different forms of AF than single biomarker use.

Knockdown of Ift88 in fibroblasts causes extracellular matrix remodeling and decreases conduction velocity in cardiomyocyte monolayers

Background: Atrial fibrosis plays an important role in the development and persistence of atrial fibrillation by promoting reentry. Primary cilia have been identified as a regulator of fibroblasts (FB) activation and extracellular matrix (ECM) deposition. We hypothesized that selective reduction of primary cilia causes increased fibrosis and facilitates reentry.

Aim: The aim of this study was to disrupt the formation of primary cilia in FB and examine its consequences on ECM and conduction in a co-culture system of cardiomyocytes (CM) and FB.

Materials: Using short interfering RNA (siRNA), we removed primary cilia in neonatal rat ventricular FB by reducing the expression of Ift88 gene required for ciliary assembly. We co-cultured neonatal rat ventricular cardiomyocytes (CM) with FB previously transfected with Ift88 siRNA (siIft88) or negative control siRNA (siNC) for 48 h. We examined the consequences of ciliated fibroblasts reduction on conduction and tissue remodeling by performing electrical mapping, microelectrode, and gene expression measurements.

Results: Transfection of FB with siIft88 resulted in a significant 60% and 30% reduction of relative Ift88 expression in FB and CM-FB co-cultures, respectively, compared to siNC. Knockdown of Ift88 significantly increased the expression of ECM genes Fn1, Col1a1 and Ctgf by 38%, 30% and 18%, respectively, in comparison to transfection with siNC. Conduction velocity (CV) was significantly decreased in the siIft88 group in comparison to siNC [11.12 ± 4.27 cm/s (n = 10) vs. 17.00 ± 6.20 (n = 10) respectively, p &lt; 0.05]. The fraction of sites with interelectrode activation block was larger in the siIft88 group than in the siNC group (6.59 × 10−2 ± 8.01 × 10−2 vs. 1.18 × 10−2 ± 3.72 × 10−2 respectively, p &lt; 0.05). We documented spontaneous reentrant arrhythmias in two cultures in the siIft88 group and in none of the siNC group. Action potentials were not significantly different between siNC and siIft88 groups.

Conclusion: Disruption of cilia formation by siIft88 causes ECM remodeling and conduction abnormalities. Prevention of cilia loss could be a target for prevention of arrhythmias.

Nano drugs delivery system: A novel promise for the treatment of atrial fibrillation

Atrial fibrillation (AF) is one of the most common sustained tachyarrhythmias worldwide, and its prevalence is positively correlated with aging. AF not only significantly reduces the quality of life of patients but also causes a series of complications, such as thromboembolism, stroke, and heart failure, increases the average number of hospitalizations of patients, and places a huge economic burden on patients and society. Traditional drug therapy and ablation have unsatisfactory success rates, high recurrence rates, and the risk of serious complications. Surgical treatment is highly traumatic. The nano drug delivery system has unique physical and chemical properties, and in the application of AF treatment, whether it is used to assist in enhancing the ablation effect or for targeted therapy, it provides a safer, more effective and more economical treatment strategy.

In-silico drug trials for precision medicine in atrial fibrillation: From ionic mechanisms to electrocardiogram-based predictions in structurally-healthy human atria

Atrial fibrillation (AF) inducibility, sustainability and response to pharmacological treatment of individual patients are expected to be determined by their ionic current properties, especially in structurally-healthy atria. Mechanisms underlying AF and optimal cardioversion are however still unclear. In this study, in-silico drug trials were conducted using a population of human structurally-healthy atria models to 1) identify key ionic current properties determining AF inducibility, maintenance and pharmacological cardioversion, and 2) compare the prognostic value for predicting individual AF cardioversion of ionic current properties and electrocardiogram (ECG) metrics. In the population of structurally-healthy atria, 477 AF episodes were induced in ionic current profiles with both steep action potential duration (APD) restitution (eliciting APD alternans), and high excitability (enabling propagation at fast rates that transformed alternans into discordant). High excitability also favored 211 sustained AF episodes, so its decrease, through prolonged refractoriness, explained pharmacological cardioversion. In-silico trials over 200 AF episodes, 100 ionic profiles and 10 antiarrhythmic compounds were consistent with previous clinical trials, and identified optimal treatments for individual electrophysiological properties of the atria. Algorithms trained on 211 simulated AF episodes exhibited >70% accuracy in predictions of cardioversion for individual treatments using either ionic current profiles or ECG metrics. In structurally-healthy atria, AF inducibility and sustainability are enabled by discordant alternans, under high excitability and steep restitution conditions. Successful pharmacological cardioversion is predicted with 70% accuracy from either ionic or ECG properties, and it is optimal for treatments maximizing refractoriness (thus reducing excitability) for the given ionic current profile of the atria.

Association between comorbidities and left and right atrial dysfunction in patients with paroxysmal atrial fibrillation: Analysis of AF-RISK

BACKGROUND

To identify the association between comorbidities and left atrial (LA) and right atrial (RA) function in patients with paroxysmal atrial fibrillation (AF).

METHODS

This is a cross-sectional study. Speckle-tracking echocardiography was performed in 344 patients with paroxysmal AF at baseline, and available in 298 patients after 1-year follow-up. The number of comorbidities (hypertension, diabetes mellitus, coronary artery disease, body mass index > 25 kg/m², age > 65 years, moderate to severe mitral valve regurgitation and kidney dysfunction (estimated glomerular filtration rate < 60 ml/min/1.73 m²)) was determined and the association with atrial strain was tested.

RESULTS

Mean age of the patients was 58 (SD 12) years and 137 patients were women (40%). Patients with a higher number of comorbidities had larger LA volumes (p for trend <0.001), and had a decrease in all strain phases from the LA and RA, except for the RA contraction phase (p for trend 0.47). A higher number of comorbidities was associated with LA reservoir and conduit strain decrease independently of LA volume (p < 0.001, p < 0.001 respectively). Patients with 1-2 comorbidities, but not patients with 3 or more comorbidities, showed a further progression of impaired LA and RA function in almost all atrial strain phases at 14 [13-17] months follow-up.

CONCLUSIONS

In patients with paroxysmal AF, individual and combined comorbidities are related to lower LA and RA strain. In patients with few comorbidities, impairment in atrial function progresses during one year of follow-up. Whether comorbidity management prevents or reverses decrease in atrial function warrants further study.

The Atrium in Atrial Fibrillation - A Clinical Review on How to Manage Atrial Fibrotic Substrates

Atrial fibrillation (AF) is the most common sustained arrhythmia in the population and is associated with a significant clinical and economic burden. Rigorous assessment of the presence and degree of an atrial arrhythmic substrate is essential for determining treatment options, predicting long-term success after catheter ablation, and as a substrate critical in the pathophysiology of atrial thrombogenesis. Catheter ablation of AF has developed into an essential rhythm-control strategy. Nowadays is one of the most common cardiac ablation procedures performed worldwide, with its success inversely related to the extent of atrial structural disease. Although atrial substrate evaluation remains complex, several diagnostic resources allow for a more comprehensive assessment and quantification of the extent of left atrial structural remodeling and the presence of atrial fibrosis. In this review, we summarize the current knowledge on the pathophysiology, etiology, and electrophysiological aspects of atrial substrates promoting the development of AF. We also describe the risk factors for its development and how to diagnose its presence using imaging, electrocardiograms, and electroanatomic voltage mapping. Finally, we discuss recent data regarding fibrosis biomarkers that could help diagnose atrial fibrotic substrates.

Association of RDW, NLR, and PLR with Atrial Fibrillation in Critical Care Patients: A Retrospective Study Based on Propensity Score Matching

Objective

Previous studies have shown inconsistent results in relation to the red cell distribution width (RDW), neutrophil to lymphocyte ratio (NLR), and platelet to lymphocyte ratio (PLR) of atrial fibrillation (AF). This retrospective study is aimed at detecting the association of RDW, NLR, and PLR with AF.

Methods

A total of 4717 critical care patients were screened from the Medical Information Mart for Intensive Care- (MIMIC-) III database. The patients were separated into the non-AF and AF groups. The imbalances between the groups were reduced using propensity score matching (PSM). ROC curves were generated to detect the diagnostic value of RDW, NLR, and PLR. Logistic regression analysis was used to detect the risk factors for AF.

Results

A total of 991 non-AF patients paired with 991 AF patients were included after PSM in this study. The RDW level in the AF group was significantly higher than that in the non-AF group (15.09 ± 1.93vs. 14.89 ± 1.91, P = 0.017). Neither NLR nor PLR showed any significant difference between the two groups (P > 0.05 for each). According to ROC curve, RDW showed a very low diagnostic value of AF (AUC = 0.5341), and the best cutoff of RDW was 14.1 (ACU = 0.5257, sensitivity = 0.658, specificity = 0.395). Logistic regression analysis showed that an elevated RDW level increased 1.308-fold (95%CI = 1.077-1.588, P = 0.007) risk of AF. Neither elevated NLR nor elevated PLR was a significant risk factor for AF (OR = 0.993, 95%CI = 0.802-1.228, P = 0.945 for NLR; OR = 0.945, 95%CI = 0.763-1.170, P = 0.603 for PLR).

Conclusions

Elevated RDW level but not NLR or PLR levels is associated with AF. RDW > 14.1 is a risk factor for AF, but its diagnostic capacity for AF is not of great value.

Prognostic Impact and Predictors of New-Onset Atrial Fibrillation in Heart Failure

Background: The prognostic impact and predictors of NOAF in HF patients are not fully elucidated. This study aims to determine whether new-onset atrial fibrillation (NOAF) affects patient outcome and investigate predictors of atrial fibrillation (AF) in acute heart failure (HF) patients using real-world data. Methods: The factors associated with NOAF in 2894 patients with sinus rhythm (SR) enrolled in the Korean Acute Heart Failure (KorAHF) registry were investigated. Survival was analyzed using AF as a time-dependent covariate. Relevant predictors of NOAF were analyzed using multivariate proportional hazards models. Results: Over 27.4 months, 187 patients developed AF. The median overall survival time was over 48 and 9.9 months for the SR and NOAF groups, respectively. Cox regression analysis with NOAF as a time-dependent covariate showed a higher risk of death among patients with NOAF. Multivariate Cox modeling showed that age, worsening HF, valvular heart disease (VHD), loop diuretics, lower heart rate, larger left atrium (LA) diameter, and elevated creatinine levels were independently associated with NOAF. Risk score indicated the number of independent predictors. The incidence of NOAF was 2.9%, 9.4%, and 21.8% in the low-risk, moderate-risk, and high-risk groups, respectively (p < 0.001). Conditional inference tree analysis identified worsening HF, heart rate, age, LA diameter, and VHD as discriminators. Conclusions: NOAF was associated with decreased survival in acute HF patients with SR. Age, worsening HF, VHD, loop diuretics, lower heart rate, larger LA diameter, and elevated creatinine could independently predict NOAF. This may be useful to risk-stratify HF patients at risk for AF.

Emerging Antiarrhythmic Drugs for Atrial Fibrillation

Atrial fibrillation (AF), the most common cardiac arrhythmia worldwide, is driven by complex mechanisms that differ between subgroups of patients. This complexity is apparent from the different forms in which AF presents itself (post-operative, paroxysmal and persistent), each with heterogeneous patterns and variable progression. Our current understanding of the mechanisms responsible for initiation, maintenance and progression of the different forms of AF has increased significantly in recent years. Nevertheless, antiarrhythmic drugs for the management of AF have not been developed based on the underlying arrhythmia mechanisms and none of the currently used drugs were specifically developed to target AF. With the increased knowledge on the mechanisms underlying different forms of AF, new opportunities for developing more effective and safer AF therapies are emerging. In this review, we provide an overview of potential novel antiarrhythmic approaches based on the underlying mechanisms of AF, focusing both on the development of novel antiarrhythmic agents and on the possibility of repurposing already marketed drugs. In addition, we discuss the opportunity of targeting some of the key players involved in the underlying AF mechanisms, such as ryanodine receptor type-2 (RyR2) channels and atrial-selective K⁺-currents (I_K2P and I_SK) for antiarrhythmic therapy. In addition, we highlight the opportunities for targeting components of inflammatory signaling (e.g., the NLRP3-inflammasome) and upstream mechanisms targeting fibroblast function to prevent structural remodeling and progression of AF. Finally, we critically appraise emerging antiarrhythmic drug principles and future directions for antiarrhythmic drug development, as well as their potential for improving AF management.

Enhanced Cardiac CaMKII Oxidation and CaMKII-Dependent SR Ca Leak in Patients with Sleep-Disordered Breathing

Background: Sleep-disordered breathing (SDB) is associated with increased oxidant generation. Oxidized Ca/calmodulin kinase II (CaMKII) can contribute to atrial arrhythmias by the stimulation of sarcoplasmic reticulum Ca release events, i.e., Ca sparks. Methods: We prospectively enrolled 39 patients undergoing cardiac surgery to screen for SDB and collected right atrial appendage biopsies. Results: SDB was diagnosed in 14 patients (36%). SDB patients had significantly increased levels of oxidized and activated CaMKII (assessed by Western blotting/specific pulldown). Moreover, SDB patients showed a significant increase in Ca spark frequency (CaSpF measured by confocal microscopy) compared with control subjects. CaSpF was 3.58 ± 0.75 (SDB) vs. 2.49 ± 0.84 (no SDB) 1/100 µm⁻¹s⁻¹ (p < 0.05). In linear multivariable regression models, SDB severity was independently associated with increased CaSpF (B [95%CI]: 0.05 [0.03; 0.07], p < 0.001) after adjusting for important comorbidities. Interestingly, 30 min exposure to the CaMKII inhibitor autocamtide-2 related autoinhibitory peptide normalized the increased CaSpF and eliminated the association between SDB and CaSpF (B [95%CI]: 0.01 [−0.1; 0.03], p = 0.387). Conclusions: Patients with SDB have increased CaMKII oxidation/activation and increased CaMKII-dependent CaSpF in the atrial myocardium, independent of major clinical confounders, which may be a novel target for treatment of atrial arrhythmias in SDB.

Self-Reported Mobile Health-Based Risk Factor and CHA2DS2-VASc-Score Assessment in Patients With Atrial Fibrillation: TeleCheck-AF Results

Introduction

The TeleCheck-AF approach is an on-demand mobile health (mHealth) infrastructure incorporating mobile app-based heart rate and rhythm monitoring through teleconsultation. We evaluated feasibility and accuracy of self-reported mHealth-based AF risk factors and CHA2DS2-VASc-score in atrial fibrillation (AF) patients managed within this approach.

Materials and Methods

Consecutive patients from eight international TeleCheck-AF centers were asked to complete an app-based 10-item questionnaire related to risk factors, associated conditions and CHA2DS2-VASc-score components. Patient's medical history was retrieved from electronic health records (EHR).

Results

Among 994 patients, 954 (96%) patients (38% female, median age 65 years) completed the questionnaire and were included in this analysis. The accuracy of self-reported assessment was highest for pacemaker and anticoagulation treatment and lowest for heart failure and arrhythmias. Patients who knew that AF increases the stroke risk, more often had a 100% or ≥80% correlation between EHR- and app-based results compared to those who did not know (27 vs. 14% or 84 vs. 77%, P = 0.001). Thromboembolic events were more often reported in app (vs. EHR) in all countries, whereas higher self-reported hypertension and anticoagulant treatment were observed in Germany and heart failure in the Netherlands. If the app-based questionnaire alone was used for clinical decision-making on anticoagulation initiation, 26% of patients would have been undertreated and 6.1%—overtreated.

Conclusion

Self-reported mHealth-based assessment of AF risk factors is feasible. It shows high accuracy of pacemaker and anticoagulation treatment, nevertheless, displays limited accuracy for some of the CHA2DS2-VASc-score components. Direct health care professional assessment of risk factors remains indispensable to ensure high quality clinical-decision making.

Patient Perspectives on Performance of a Smartphone App for Atrial FibrillationSelf-Management

INTRODUCTION

AF self-care requires patients to perform daily self-monitoring for symptoms, practice decision making to address symptom changes, and adhere to prescribed medication, diet, physical activity, and follow-up care. Technology can facilitate these critical self-care behaviors and ultimately improve patient outcomes. We assessed atrial fibrillation (AF) patients' experiences with a smartphone application (app) for AF self-management.

METHODS

A focus group with 9 AF patients and app users was conducted and analyzed using qualitative research methods. The focus group was recorded, transcribed, and coded using a priori and inductive coding strategies. Participant responses for each code were synthesized to identify primary themes.

RESULTS

We identified four superordinate themes from patients' experiences: (1) disconnect between tool and its intended use; (2) app as acknowledged tool for adherence; (3) knowledge as empowerment; (3) motives: self-interest vs supporting research. Results from this qualitative study underscore the need to clarify the app's intended use and to better accommodate patients with different AF experiences. The disconnect between a tool and its intended use can generate frustration for users.

DISCUSSION

The study reinforces that participants not only see how the app is a tool for adherence; they also see knowledge they gain via the app as empowering, suggesting a correlation between app use and self-efficacy.

Considerations for the Assessment of Substrates, Genetics and Risk Factors in Patients with Atrial Fibrillation

Successful translation of research focussing on atrial arrhythmogenic mechanisms has potential to provide a mechanism-tailored classification and to support personalised treatment approaches in patients with AF. The clinical uptake and clinical implementation of new diagnostic techniques and treatment strategies require translational research approaches on various levels. Diagnostic translation involves the development of clinical diagnostic tools. Additionally, multidisciplinary teams are required for collaborative translation to describe genetic mechanisms, molecular pathways, electrophysiological characteristics and concomitant risk factors. In this article, current approaches for AF substrate characterisation, analysis of genes potentially involved in AF and strategies for AF risk factor assessment are summarised. The authors discuss challenges and obstacles to clinical translation and implementation into clinical practice.

Atrial remodeling and atrial fibrillation recurrence after catheter ablation : Past, present, and future developments

The term "atrial remodeling" is used to describe the electrical, mechanical, and structural changes associated with the presence of an arrhythmogenic substrate for atrial fibrillation. Rhythm control therapy may slow down or even reverse progressive atrial remodeling. Atrial remodeling has long been recognized as an important predictor of clinical outcomes and therapeutic success, but recent advances have highlighted its clinical relevance and revealed the implications of specific anatomical changes such as atrial asymmetry or shape. This has opened the path to computational precision medicine that captures these data in detail and combines them with other factors, to provide patient-specific solutions. The goal of precision medicine lies in improving clinical outcomes, reducing costs, and avoiding unnecessary procedures. In this article, we review the history of atrial remodeling and we summarize the insights from our research on anatomical atrial remodeling and its association with rhythm outcomes after catheter ablation. Finally, we present recent advances in the field, reflecting the beginning of a new technological era that will enable us to improve patient care by personalized patient-specific medicine.

CVAR-Seg: An Automated Signal Segmentation Pipeline for Conduction Velocity and Amplitude Restitution

BACKGROUND

Rate-varying S1S2 stimulation protocols can be used for restitution studies to characterize atrial substrate, ionic remodeling, and atrial fibrillation risk. Clinical restitution studies with numerous patients create large amounts of these data. Thus, an automated pipeline to evaluate clinically acquired S1S2 stimulation protocol data necessitates consistent, robust, reproducible, and precise evaluation of local activation times, electrogram amplitude, and conduction velocity. Here, we present the CVAR-Seg pipeline, developed focusing on three challenges: (i) No previous knowledge of the stimulation parameters is available, thus, arbitrary protocols are supported. (ii) The pipeline remains robust under different noise conditions. (iii) The pipeline supports segmentation of atrial activities in close temporal proximity to the stimulation artifact, which is challenging due to larger amplitude and slope of the stimulus compared to the atrial activity.

METHODS AND RESULTS

The S1 basic cycle length was estimated by time interval detection. Stimulation time windows were segmented by detecting synchronous peaks in different channels surpassing an amplitude threshold and identifying time intervals between detected stimuli. Elimination of the stimulation artifact by a matched filter allowed detection of local activation times in temporal proximity. A non-linear signal energy operator was used to segment periods of atrial activity. Geodesic and Euclidean inter electrode distances allowed approximation of conduction velocity. The automatic segmentation performance of the CVAR-Seg pipeline was evaluated on 37 synthetic datasets with decreasing signal-to-noise ratios. Noise was modeled by reconstructing the frequency spectrum of clinical noise. The pipeline retained a median local activation time error below a single sample (1 ms) for signal-to-noise ratios as low as 0 dB representing a high clinical noise level. As a proof of concept, the pipeline was tested on a CARTO case of a paroxysmal atrial fibrillation patient and yielded plausible restitution curves for conduction speed and amplitude.

CONCLUSION

The proposed openly available CVAR-Seg pipeline promises fast, fully automated, robust, and accurate evaluations of atrial signals even with low signal-to-noise ratios. This is achieved by solving the proximity problem of stimulation and atrial activity to enable standardized evaluation without introducing human bias for large data sets.

Non-Invasive and Quantitative Estimation of Left Atrial Fibrosis Based on P Waves of the 12-Lead ECG-A Large-Scale Computational Study Covering Anatomical Variability

The arrhythmogenesis of atrial fibrillation is associated with the presence of fibrotic atrial tissue. Not only fibrosis but also physiological anatomical variability of the atria and the thorax reflect in altered morphology of the P wave in the 12-lead electrocardiogram (ECG). Distinguishing between the effects on the P wave induced by local atrial substrate changes and those caused by healthy anatomical variations is important to gauge the potential of the 12-lead ECG as a non-invasive and cost-effective tool for the early detection of fibrotic atrial cardiomyopathy to stratify atrial fibrillation propensity. In this work, we realized 54,000 combinations of different atria and thorax geometries from statistical shape models capturing anatomical variability in the general population. For each atrial model, 10 different volume fractions (0-45%) were defined as fibrotic. Electrophysiological simulations in sinus rhythm were conducted for each model combination and the respective 12-lead ECGs were computed. P wave features (duration, amplitude, dispersion, terminal force in V1) were extracted and compared between the healthy and the diseased model cohorts. All investigated feature values systematically in- or decreased with the left atrial volume fraction covered by fibrotic tissue, however value ranges overlapped between the healthy and the diseased cohort. Using all extracted P wave features as input values, the amount of the fibrotic left atrial volume fraction was estimated by a neural network with an absolute root mean square error of 8.78%. Our simulation results suggest that although all investigated P wave features highly vary for different anatomical properties, the combination of these features can contribute to non-invasively estimate the volume fraction of atrial fibrosis using ECG-based machine learning approaches.