Role of echocardiography in atrial fibrillation

Efficacy and safety of different antiarrhythmic protocols used for rate control in dogs with secondary atrial fibrillation

INTRODUCTION/OBJECTIVES

Studies comparing the effects of antiarrhythmic protocols used for rate control in dogs with secondary atrial fibrillation (AF) are currently limited; therefore, this study aimed to report detailed data on the efficacy and therapy-related side-effects (TRSEs) of different antiarrhythmic protocols in dogs with secondary AF.

ANIMALS, MATERIALS, AND METHODS

Dogs with secondary AF treated with combination therapy with diltiazem and digoxin (CTDilt+Digox), diltiazem monotherapy (MTDilt), digoxin monotherapy (MTDigox), or amiodarone monotherapy (MTAmiod) were retrospectively evaluated. Signalment, clinical, diagnostic, therapeutic, and outcome data were retrieved. Electrocardiographically, antiarrhythmic efficacy was defined by a reduction in the mean heart rate on Holter monitoring ≤125 beats/minutes. Statistical analysis was performed to compare selected data, including the rate of efficacy and TRSEs as well as the median survival time, between dogs treated with different antiarrhythmic protocols.

RESULTS

Fifty-four dogs were included, with 28 receiving the CTDilt+Digox and 26 receiving monotherapies (MTDigox = 16; MTDilt = 5; MTAmiod = 5). The efficacy rate documented in dogs treated with CTDilt+Digox was significantly higher than that observed in dogs from the composite monotherapy group (i.e., MTDilt+MTDigox+MTAmiod) (P=0.048). The rate of TRSEs documented in dogs treated with CTDilt+Digox was similar to that observed in dogs from the composed monotherapy group (P=0.129). The median survival time documented in dogs treated with CTDilt+Digox was significantly longer than that observed in dogs of the MTDigox group (P=0.01).

DISCUSSION

In dogs with secondary AF we included, CTDilt+Digox was well tolerated and provided clinically relevant benefits compared to the use of a single antiarrhythmic drug.

LIMITATIONS

Retrospective design; heterogeneous sample size of categories analyzed; clinicopathological data available for many, but not all, dogs.

CONCLUSIONS

Our findings support the indication to generally consider CTDilt+Digox as a first-line antiarrhythmic treatment in dogs with secondary AF.

Demographic trends in mortality with older population due to atrial fibrillation and flutter from 1999-2020

Atrial fibrillation (AF)/atrial flutter (AFL) is the most common sustained cardiac arrhythmia. The known risk factors for developing AF/AFL include age, structural heart disease, hypertension, diabetes mellitus, or hyperthyroidism. This study aims to attribute the trends in AF/AFL-related mortalities over the past two decades 1999-2020 concerning race and sex and disparity among them. To the best of our knowledge, this is the first study that estimates the trends and mortality due to AF/AFL from 1999-2020 in older adults in the United States. In this 21-year analysis of mortality data, we found a constant increase in mortality rates due to AF/AFL in older adults. From 1999 to 2020, the overall mortality in older adults aged 65 and above, regardless of sex and race, is found to be almost doubled i.e. about a 50.2% increase in the number of deaths due to AF/AFL. Furthermore, other confounding risk factors such has obesity, prior myocardial infarction, inflammation, hypertension, birth weight, diabetes mellitus, hyperthyroidism, hormone replacement therapy in menopausal women increases the risk in the occurrence or recurrent occurrence of AF.

Multi-organ clinical ultrasound as a complement to the diagnostic process in an internal medicine consultation

INTRODUCTION

Evaluating outpatient cases in internal medicine consultations presents a significant diagnostic challenge. Ultrasound can be a highly useful tool in assessment and decision-making.

PATIENTS AND METHODS

A prospective observational study was conducted on a cohort of patients attending an internal medicine rapid assessment clinic. Eighty patients were prospectively recruited. A medical consultation was conducted as per usual clinical practice, followed by a POCUS evaluation; collecting pulmonary, cardiac, and abdominal data. All findings were analyzed and recorded, particularly those that were significant or altered the initial diagnosis, subsequent tests, or treatment.

RESULTS

Significant ultrasound findings were found in 37.5% of the patients. Of all ultrasound scans, the most clinically relevant were in the heart region (31.9%), followed by the abdomen (26%). These findings led to a change in overall management in 27.5% of patients. Using logistic regression, a model was developed to estimate the presence of clinically relevant findings with an area under the curve (AUC) of 0.78 (95% CI 0.66-0.89; p < 0.001) with 80% Sensitivity and 66% Specificity.

CONCLUSION

The systematic and standardized incorporation of clinical ultrasound in internal medicine consultations contributes to decision-making, can provide significant findings that allow for modifications in clinical suspicion and therapeutic management.

Chemotherapy Related Cardiotoxicity Evaluation-A Contemporary Review with a Focus on Cardiac Imaging

The long-term survivorship of patients diagnosed with cancer has improved due to accelerated detection and rapidly evolving cancer treatment strategies. As such, the evaluation and management of cancer therapy related complications has become increasingly important, including cardiovascular complications. These have been captured under the umbrella term "cardiotoxicity" and include left ventricular dysfunction and heart failure, acute coronary syndromes, valvular abnormalities, pericardial disease, arrhythmia, myocarditis, and vascular complications. These complications add to the burden of cardiovascular disease (CVD) or are risk factors patients with cancer treatment are presenting with. Of note, both pre- and newly developing CVD is of prognostic significance, not only from a cardiovascular perspective but also overall, potentially impacting the level of cancer therapy that is possible. Currently, there are varying recommendations and practices regarding CVD risk assessment and mitigating strategies throughout the cancer continuum. This article provides an overview on this topic, in particular, the role of cardiac imaging in the care of the patient with cancer. Furthermore, it summarizes the current evidence on the spectrum, prevention, and management of chemotherapy-related adverse cardiac effects.

Efficacy and safety of antiarrhythmic therapy in dogs with naturally acquired tachyarrhythmias treated with amiodarone or sotalol: a retrospective analysis of 64 cases

INTRODUCTION/OBJECTIVE

Studies on the use of amiodarone or sotalol are limited in dogs. Therefore, this study aimed to provide data on the efficacy and safety of these drugs in dogs with ventricular tachyarrhythmia (VT) and/or supraventricular tachyarrhythmia (SvT).

ANIMALS, MATERIALS, AND METHODS

Dogs with VT and/or SvT treated with amiodarone or sotalol as a first-line therapy were retrospectively evaluated. Signalment, clinical, diagnostic, therapeutic, and outcome data were retrieved. For VT, efficacy was demonstrated through a decrease of the Lown-Wolf grade to less than five or a reduction of at least 85% in the number of ventricular premature complexes observed on Holter monitoring. For SvT, efficacy was represented by cardioversion or a reduction in the mean heart rate on Holter monitoring ≤140 beats/min. Treatment-related side effects (TRSEs) were classified as clinically relevant and irrelevant. Statistical analysis was performed to compare data before and after antiarrhythmic prescription.

RESULTS

Sixty-four dogs were included. Amiodarone and sotalol were efficacious in treating both VT (85.7% and 90.0% of cases, respectively) and SvT (75% and 71.4% of cases, respectively). No significant differences were found when comparing their efficacy rates in dogs with VT and SvT (P=0.531 and 0.483, respectively). Clinically relevant TRSEs were rare with both amiodarone and sotalol (8.3% and 5% of cases, respectively), while clinically irrelevant TRSEs occurred more frequently with amiodarone (29.2%) than with sotalol (10%).

DISCUSSION

In dogs with tachyarrhythmias, amiodarone and sotalol are generally efficacious and safe, as clinically relevant TRSEs seem rare.

CONCLUSIONS

This study provides novel data on the effects of amiodarone and sotalol in dogs with tachyarrhythmias.

Automated Atrial Fibrillation Diagnosis by Echocardiography without ECG: Accuracy and Applications of a New Deep Learning Approach

BACKGROUND

Automated rhythm detection on echocardiography through artificial intelligence (AI) has yet to be fully realized. We propose an AI model trained to identify atrial fibrillation (AF) using apical 4-chamber (AP4) cines without requiring electrocardiogram (ECG) data.

METHODS

Transthoracic echocardiography studies of consecutive patients ≥ 18 years old at our tertiary care centre were retrospectively reviewed for AF and sinus rhythm. The study was first interpreted by level III-trained echocardiography cardiologists as the gold standard for rhythm diagnosis based on ECG rhythm strip and imaging assessment, which was also verified with a 12-lead ECG around the time of the study. AP4 cines with three cardiac cycles were then extracted from these studies with the rhythm strip and Doppler information removed and introduced to the deep learning model ResNet(2+1)D with an 80:10:10 training-validation-test split ratio.

RESULTS

634 patient studies (1205 cines) were included. After training, the AI model achieved high accuracy on validation for detection of both AF and sinus rhythm (mean F1-score = 0.92; AUROC = 0.95). Performance was consistent on the test dataset (mean F1-score = 0.94, AUROC = 0.98) when using the cardiologist's assessment of the ECG rhythm strip as the gold standard, who had access to the full study and external ECG data, while the AI model did not.

CONCLUSIONS

AF detection by AI on echocardiography without ECG appears accurate when compared to an echocardiography cardiologist's assessment of the ECG rhythm strip as the gold standard. This has potential clinical implications in point-of-care ultrasound and stroke risk stratification.

The Use of Artificial Intelligence for Detecting and Predicting Atrial Arrhythmias Post Catheter Ablation

Catheter ablation (CA) is considered as one of the most effective methods technique for eradicating persistent and abnormal cardiac arrhythmias. Nevertheless, in some cases, these arrhythmias are not treated properly, resulting in their recurrences. If left untreated, they may result in complications such as strokes, heart failure, or death. Until recently, the primary techniques for diagnosing recurrent arrhythmias following CA were the findings predisposing to the changes caused by the arrhythmias on cardiac imaging and electrocardiograms during follow-up visits, or if patients reported having palpitations or chest discomfort after the ablation. However, these follow-ups may be time-consuming and costly, and they may not always determine the root cause of the recurrences. With the introduction of artificial intelligence (AI), these follow-up visits can be effectively shortened, and improved methods for predicting the likelihood of recurring arrhythmias after their ablation procedures can be developed. AI can be divided into two categories: machine learning (ML) and deep learning (DL), the latter of which is a subset of ML. ML and DL models have been used in several studies to demonstrate their ability to predict and identify cardiac arrhythmias using clinical variables, electrophysiological characteristics, and trends extracted from imaging data. AI has proven to be a valuable aid for cardiologists due to its ability to compute massive amounts of data and detect subtle changes in electric signals and cardiac images, which may potentially increase the risk of recurrent arrhythmias after CA. Despite the fact that these studies involving AI have generated promising outcomes comparable to or superior to human intervention, they have primarily focused on atrial fibrillation while atrial flutter (AFL) and atrial tachycardia (AT) were the subjects of relatively few AI studies. Therefore, the aim of this review is to investigate the interaction of AI algorithms, electrophysiological characteristics, imaging data, risk score calculators, and clinical variables in predicting cardiac arrhythmias following an ablation procedure. This review will also discuss the implementation of these algorithms to enable the detection and prediction of AFL and AT recurrences following CA.

Computational Fluid Dynamic Model of Left Atrium to Analyze Hemodynamic Manifestation during Atrial Fibrillation

In this paper, we present a computational fluid dynamic (CFD) model of left atrium (LA) to analyze the manifestation and progression of atrial fibrillation (AF) in terms of hemodynamic metrics. We propose a coupled lumped-CFD (0d-3d) pipeline to model and predict the pulsatile flow and pressure fields of three-dimensional cardiac chamber under the influence of sinus rhythm, high frequency AF (HF-AF) and LA remodeled AF, considering the interactions between the heart and the arterial system through a separately modeled 0d lumped hemodynamic cardiac model. A novel rhythm generator is modeled to generate modulated cardiac chamber compliance and decoupled auricular and ventricular contraction rate to synthesize variation in sinus rhythm and subsequent AF generation. CFD simulation were solved using subject specific CT scan. Systemic and pulmonary flow and pressure along with metrics related to wall shear stress in LA were derived. Left ventricular (LV) hemodynamic parameters associated with global cardio vascular evaluation like ejection fraction, stroke volume, cardiac output, etc. were also generated for all the rhythmic disturbance under consideration. The proposed 0d-3d coupled hemodynamic model of the LA can provide useful insights on the dynamics of AF manifestation and predict vulnerable regions in the cardiac chambers as well as arterial vasculature for probable thrombogenic plaque formation that leads to stroke and infraction, leading to heart failure.

AFCNNet: Automated detection of AF using chirplet transform and deep convolutional bidirectional long short term memory network with ECG signals

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia and is characterized by the heart's beating in an uncoordinated manner. In clinical studies, patients often do not have visible symptoms during AF, and hence it is harder to detect this cardiac ailment. Therefore, automated detection of AF using the electrocardiogram (ECG) signals can reduce the risk of stroke, coronary artery disease, and other cardiovascular complications. In this paper, a novel time-frequency domain deep learning-based approach is proposed to detect AF and classify terminating and non-terminating AF episodes using ECG signals. This approach involves evaluating the time-frequency representation (TFR) of ECG signals using the chirplet transform. The two-dimensional (2D) deep convolutional bidirectional long short-term memory (BLSTM) neural network model is used to detect and classify AF episodes using the time-frequency images of ECG signals. The proposed TFR based 2D deep learning approach is evaluated using the ECG signals from three public databases. Our developed approach has obtained an accuracy, sensitivity, and specificity of 99.18% (Confidence interval (CI) as [98.86, 99.49]), 99.17% (CI as [98.85 99.49]), and 99.18% (CI as [98.86 99.49]), respectively, with 10-fold cross-validation (CV) technique to detect AF automatically. The proposed approach also classified terminating and non-terminating AF episodes with an average accuracy of 75.86%. The average accuracy value obtained using the proposed approach is higher than the short-time Fourier transform (STFT), discrete-time continuous wavelet transform (DT-CWT), and Stockwell transform (ST) based time-frequency analysis methods with deep convolutional BLSTM models to detect AF. The proposed approach has better AF detection performance than the existing deep learning-based techniques using ECG signals from the MIT-BIH database.

Deep learning-based automated left ventricular ejection fraction assessment using 2-D echocardiography

Deep learning (DL) has been applied for automatic left ventricle (LV) ejection fraction (EF) measurement, but the diagnostic performance was rarely evaluated for various phenotypes of heart disease. This study aims to evaluate a new DL algorithm for automated LVEF measurement using two-dimensional echocardiography (2DE) images collected from three centers. The impact of three ultrasound machines and three phenotypes of heart diseases on the automatic LVEF measurement was evaluated. Using 36890 frames of 2DE from 340 patients, we developed a DL algorithm based on U-Net (DPS-Net) and the biplane Simpson's method was applied for LVEF calculation. Results showed a high performance in LV segmentation and LVEF measurement across phenotypes and echo systems by using DPS-Net. Good performance was obtained for LV segmentation when DPS-Net was tested on the CAMUS data set (Dice coefficient of 0.932 and 0.928 for ED and ES). Better performance of LV segmentation in study-wise evaluation was observed by comparing the DPS-Net v2 to the EchoNet-dynamic algorithm (P = 0.008). DPS-Net was associated with high correlations and good agreements for the LVEF measurement. High diagnostic performance was obtained that the area under receiver operator characteristic curve was 0.974, 0.948, 0.968, and 0.972 for normal hearts and disease phenotypes including atrial fibrillation, hypertrophic cardiomyopathy, dilated cardiomyopathy, respectively. High performance was obtained by using DPS-Net in LV detection and LVEF measurement for heart failure with several phenotypes. High performance was observed in a large-scale dataset, suggesting that the DPS-Net was highly adaptive across different echocardiographic systems.NEW & NOTEWORTHY A new strategy of feature extraction and fusion could enhance the accuracy of automatic LVEF assessment based on multiview 2-D echocardiographic sequences. High diagnostic performance for the determination of heart failure was obtained by using DPS-Net in cases with different phenotypes of heart diseases. High performance for left ventricle segmentation was obtained by using DPS-Net, suggesting the potential for a wider range of application in the interpretation of 2DE images.

Diastolic function assessed with speckle tracking over a decade and its prognostic value: The Copenhagen City Heart Study

BACKGROUND

The ratio of transmitral early filling velocity to early diastolic strain rate (E/e'sr) may be a more accurate measure of LV filling pressure then ratio of early filling pressure to early tissue velocity. The aim of the study was to investigate the impact of age, sex, obesity, smoking, hypertension, hypercholesterolemia, diabetes, physical activity level, socioeconomic, and psychosocial status on E/e'sr over a decade. Additionally, the predictive value of ΔE/e'sr on future major adverse cardiovascular events (MACE) has never been explored.

METHOD

The study included 623 participants from the general population, who participated in the 4th and 5th Copenhagen City Heart Study (CCHS4 and CCHS5). Examinations were median 10 years apart. MACE was the composite endpoint of heart failure, myocardial infarction, and all-cause death.

RESULTS

Follow-up time was median 5.7 years, and 43 (7%) experienced MACE. Mean age was 51 ± 14 years, and 43% were male. Mean ΔE/e'sr was 2.1 ± 23.0 cm. After multivariable adjustment for demographic, clinical, and biochemistry variables, high age (stand. β-coef. = .24, P < .001) and mean arterial blood pressure (MAP) (stand. β-coef. = .17, P < .001) were significantly associated with an accelerated increase in E/e'sr In multivariable Cox regression, E/e'sr at CCHS5 and ΔE/e'sr were independent predictors of MACE (HR = 1.20, 95% CI [1.01; 1.42] per 10 cm increase for both). ΔE/e'sr did only provide incremental prognostic value to change in left atrial volume index of the conventional diastolic measurements.

CONCLUSION

In the general population, age and MAP were predictors of an accelerated increase in E/e'sr over a decade. E/e'sr at CCHS5 and ΔE/e'sr were independent predictors of future MACE.

Myocardial performance index by tissue Doppler echocardiography predicts adverse events in patients with atrial fibrillation

AIMS

The prognostic value of myocardial performance index (MPI) has not yet been assessed in patients with atrial fibrillation (AF). The aim of this study was to evaluate the prognostic value of MPI by tissue Doppler imaging (TDI) M-mode in AF patients.

METHODS AND RESULTS

Echocardiograms from 210 patients with AF during examination were analysed offline. Patients with known heart failure (HF) were excluded. Time intervals were measured using an M-mode line through the mitral valve leaflets to provide a colour diagram of the mitral leaflet movement so all time intervals could be measured from one cardiac cycle. MPI was calculated as the sum of isovolumic relaxation time and isovolumic contraction time divided by the ejection time [(IVRT+IVCT)/ET]. During a median follow-up of 2.4 years, 84 patients (40%) reached the combined endpoint of major adverse cardiovascular events (MACE), being all-cause mortality, HF, myocardial infarction, or stroke. Increasing MPI was significantly associated with an increased risk of MACE, and the risk increased with 20% per 0.1 increase in MPI [hazard ratio (HR) 1.20, 95% confidence interval (CI) 1.10-1.32; P < 0.001]. Increasing MPI was also significantly associated with a lower left ventricular ejection fraction (LVEF) (P < 0.001). Nevertheless, MPI remained an independent predictor even after adjustment for age, sex, diabetes mellitus, left atrial volume, and LVEF (HR 1.12, 95% CI 1.01-1.25; P = 0.038).

CONCLUSION

Increasing MPI was significantly associated with increased risk of MACE and remained an independent predictor after multivariable adjustment. This demonstrates that the MPI obtained by TDI M-mode might be useful in assessing cardiac function in AF patients with ongoing arrhythmia during examination.

Novel Echocardiographic Biomarkers in the Management of Atrial Fibrillation

Purpose of Review

Atrial fibrillation (AF) is the most common arrhythmia in adults. The number of patients with AF is anticipated to increase annually, mainly due to the aging population alongside improved arrhythmia detection. AF is associated with a significantly elevated risk of hospitalization, stroke, thromboembolism, heart failure, and all-cause mortality. Echocardiography is one of the key components of routine assessment and management of AF. Therefore, the aim of this review is to briefly summarize current knowledge on “novel” echocardiographic parameters that may be of value in the management of AF patients.

Recent Findings

Novel echocardiographic biomarkers and their clinical application related to the management of AF have been taken into consideration. Both standard parameters such as atrial size and volume but also novels like atrial strain and tissue Doppler techniques have been analyzed.

Summary

A number of novel echocardiographic parameters have been proven to enable early detection of left atrial dysfunction along with increased diagnosis accuracy. This concerns particularly experienced echocardiographers. Hence, these techniques might improve the prediction of stroke and thromboembolic events among AF patients and need to be further developed and disseminated. Nonetheless, even the standard imaging parameters could be of significant value and should not be discontinued in everyday clinical practice.

Roles of Transesophageal Echocardiography and Cardiac Computed Tomography for Evaluation of Left Atrial Thrombus and Associated Pathology: A Review and Critical Analysis

Evaluation of the left atrium and left atrial appendage for the presence of thrombus prior to cardioversion and pulmonary vein isolation, and of the entire heart for embolic sources in the setting of cryptogenic stroke, has long been standard medical care. Guidelines have uniformly recommended transesophageal echocardiography (TEE) to accomplish these goals. In recent years, computed tomographic angiography has demonstrated diagnostic accuracy similar to that of TEE for the detection of thrombus. Analysis of the pertinent data and relative merits of the 2 technologies leads to the conclusions that: 1) both modalities have some unique, nonoverlapping capabilities that may dictate their use in specific situations; 2) computed tomographic angiography is a reasonable alternative to TEE when the primary aim is to exclude left atrial and left atrial appendage thrombus and in patients in whom the risks associated with TEE outweigh the benefits; and 3) both options should be discussed with the patient in the setting of shared decision making.

Prognostic Value of Left Atrial Functional Measures in Heart Failure With Reduced Ejection Fraction

BACKGROUND

The prognostic value of LA functional measures in heart failure patients with reduced ejection fraction (HFrEF) is unclear. Therefore, this study investigated the prognostic value of left atrial (LA) functional measures such as the left atrial emptying fraction (LAEF) and the minimal LA volume compared with left atrial volume index (LAVI) in HFrEF patients.

METHODS AND RESULTS

A total of 818 HFrEF patients with left ventricular ejection fractions <45% underwent echocardiography. LA volumes were determined by the area-length method from the apical 2-chamber and apical 4-chamber views. LAEF, minimal LA volume indexed to body surface area (MinLAVI), and LAVI were calculated. The end point was all-cause mortality. During a median follow-up of 3.3 years (interquartile range 1.8-4.6 years), 121 patients died (14.8%). Follow-up was 100%. In a final multivariable model adjusting for clinical and echocardiographic parameters, LAEF, but not MinLAVI or LAVI, was an independent predictor of all-cause mortality in HFrEF patients: LAEF: hazard ratio (HR) 1.11 (P = .033) per 5% decrease; MinLAVI: HR 1.03 (P = .57) per 5 mL/m² increase; LAVI: HR 1.06 (P = .16) per 5 mL/m² increase.

CONCLUSIONS

LAEF is an independent predictor of all-cause mortality in HFrEF patients after multivariable adjustment. LAEF provides incremental prognostic value over LAVI in risk stratification of HFrEF patients.

The Role of Echocardiography in Determining the Method of Ablation for the Treatment of Paroxysmal Atrial Fibrillation: A Literature Review

Atrial fibrillation is the most common cardiac arrhythmia, affecting approximately 1 out of every 250 people. It is associated with thrombus formation in the left atrium, decreased cardiac output, and deterioration of the myocardium. There are multiple treatments available for paroxysmal atrial fibrillation. This literature review will assess the benefits, risks, and complications associated with radiofrequency ablation and cryoablation, which utilize heat and freezing mechanisms, respectively. The review will also assess the role of echocardiography in determining which treatment, if any, is appropriate for atrial fibrillation.

The Cumulative Incidence of Stroke, Myocardial infarction, Heart Failure and Sudden Cardiac Death in Patients with Atrial Fibrillation

Introduction:

Atrial fibrillation represents the most common cardiac arrhythmia in clinical practice. By year 2030, 14–17 million AF patients are anticipated in the European Union. Atrial fibrillation remains one of the major causes of stroke, heart failure, sudden death all over the world.

Research Objectives:

The objective of our study is to determine the cardiac and cerebrovascular events (myocardial infarction, heart failure, stroke, sudden cardiac death) and their cumulative incidence during 11 years follow up period.

Patients and methods:

This study includes 2352 ambulant and hospitalized patients with atrial fibrillation (AF) who were enrolled during the follow up period. All patients underwent clinical evaluation in order to determine cardiac and cerebrovascular events (myocardial infarction, heart failure, stroke, sudden cardiac death) and their cumulative incidence.

Results:

The results of cumulative incidence for sudden cardiac death was 1.71%, for stroke 2.56%, for myocardial infarction 1.20% and for heart failure was 5.73%. In our study the age-adjusted incidence and prevalence of AF are slightly lower in women. The study shows that the risk of death is higher in females than in males with AF.

Conclusion:

Despite good progress in the management of patients with atrial fibrillation (AF), this arrhythmia remains one of the major causes of stroke, heart failure, sudden death. Effective treatment of patients with atrial fibrillation includes not only rate control, rhythm control, and prevention of stroke, but also management of cardiovascular risk factors and concomitant diseases.

The Impact of Risk Factors and Comorbidities on The Incidence of Atrial Fibrillation

INTRODUCTION

Atrial fibrillation (AF) is the most common form of cardiac arrhythmia in clinical practice and its prevalence increases with age. Patients who develop AF also have cardiovascular risk factors, structural heart disease, and comorbidities, all of which can increase mortality. AF causes a significant economic burden with the increasing trend in AF prevalence and hospitalizations.

RESEARCH OBJECTIVES

The objective of our study is to evaluate the impact of the most common known risk factors on the incidence of atrial fibrillation as an important precursor of cardiac and cerebrovascular morbidity and mortality among our patients in Bosnia and Herzegovina during median follow up period (September 2006 - September 2016). The other objective is to estimate the CHA2DS2-VASc score among our patients based on clinical parameters.

PATIENTS AND METHODS

This study includes 2352 ambulant and hospitalized patients with atrial fibrillation. All patients underwent clinical evaluation which includes thorough assessment for potential risk factors and concomitant conditions in order to determine which of them represent the most common among examinees with atrial fibrillation.

RESULTS

The results show that male gender has slightly more incidence of AF. Obesity and overweight with BMI ≥ 27, cigarettes smoking and sedentary life style are almost present in patients with AF. Arterial hypertension, coronary artery disease, diabetes mellitus, chronic obstructive pulmonary disease, chronic renal dysfunction, structural and valvular heart disease and peripheral vascular disease are the most common comorbidities among our patients. The mean CHA2DS2-VASc score was 3.2±1.4 and the mean HAS-BLED score was 2.1±1.2.

CONCLUSION

Atrial fibrillation is the most common sustained cardiac rhythm disorder. The study shows that obesity, alcohol consumption, smoking cigarettes and dyslipidemia can be considered as triggers and predisposing factors for appearance of AF. Arterial hypertension, coronary artery disease, chronic obstructive pulmonary disease, diabetes mellitus, Peripheral vascular disease and chronic kidney disease are playing important role in developing of AF.

Global longitudinal strain corrected by RR interval is a superior predictor of all-cause mortality in patients with systolic heart failure and atrial fibrillation

AIMS

Quantification of systolic function in patients with atrial fibrillation (AF) is challenging. A novel approach, based on RR interval correction, to counteract the varying heart cycle lengths in AF has recently been proposed. Whether this method is superior in patients with systolic heart failure (HFrEF) with AF remains unknown. This study investigates the prognostic value of RR interval-corrected peak global longitudinal strain {GLSc = GLS/[RR^(1/2)]} in relation to all-cause mortality in HFrEF patients displaying AF during echocardiographic examination.

METHODS AND RESULTS

Echocardiograms from 151 patients with HFrEF and AF during examination were analysed offline. Peak global longitudinal strain (GLS) was averaged from 18 myocardial segments obtained from three apical views. GLS was indexed with the square root of the RR interval {GLSc = GLS/[RR^(1/2)]}. Endpoint was all-cause mortality. During a median follow-up of 2.7 years, 40 patients (26.5%) died. Neither uncorrected GLS (P = 0.056) nor left ventricular ejection fraction (P = 0.053) was significantly associated with all-cause mortality. After RR^(1/2) indexation, GLSc became a significant predictor of all-cause mortality (hazard ratio 1.16, 95% confidence interval 1.02-1.22, P = 0.014, per %/s^(1/2) decrease). GLSc remained an independent predictor of mortality after multivariable adjustment (age, sex, mean heart rate, mean arterial blood pressure, left atrial volume index, and E/e') (hazard ratio 1.17, 95% confidence interval 1.05-1.31, P = 0.005 per %/s^(1/2) decrease).

CONCLUSIONS

Decreasing {GLSc = GLS/[RR^(1/2)]}, but not uncorrected GLS nor left ventricular ejection fraction, was significantly associated with increased risk of all-cause mortality in HFrEF patients with AF and remained an independent predictor after multivariable adjustment.

Left atrial appendage function assessment and thrombus identification

Background

The diagnosis of thrombus in the left atrium in patients with persistent atrial fibrillation (AF) and may be inconsistent because of variability in thrombus morphology. In some cases it is challenging and requires unusual approach. New Doppler-derived methods might be helpful to identify such thrombi. We evaluated quantitative differences in mechanical function of the left atrial appendage (LAA) basal segments using tissue Doppler imaging (TDI)and speckle tracking echocardiography (STE) in patients with non-valvular AF with and without LAA thrombus and compared them with SR patients.

Methods

A total of 80 patients with normal left ventricular ejection fraction underwent transesophageal echocardiography (40 patients with SR and 40 patients with AF on oral anticoagulants including patients with LAA thrombus). We analyzed the basal segments of LAA including left lateral ridge (LLR) and baso-medial appendage segment (BMAS). Quantitative analysis was used to calculate peak velocity, average velocity, strain, strain rate and deformation.

Results

In patients with AF the lower LLR strain rate was the sole new STE significant parameter differentiating patients with and without LAA thrombi: − 0.9(− 1.2; − 0.1)s^− 1 vs. − 1.6(− 1.9; − 1.3)s^− 1, (p = 0.004). Additionally, patients in SR demonstrated significantly better peak velocity, average velocity, strain, strain rate and deformation than those with AF (p < 0.001).

Conclusions

LLR appeared to be an appropriate site for measuring Doppler derived parameters. It is possible that the strain rate in LLR area may be a novel parameter correlating with the presence of thrombus in patients with AF.

Systolic and Diastolic Function by Tissue Doppler Imaging Predicts Mortality in Patients with Atrial Fibrillation

AIM

Tissue Doppler Imaging (TDI) detects early signs of left ventricular dysfunction. The prognostic potential of TDI in patients with atrial fibrillation (AF) has, however, not yet been clarified. This study evaluates the prognostic value of TDI in patients with atrial fibrillation.

METHODS AND RESULTS

In total, echocardiograms from 313 patients with AF during examination were analyzed offline. Longitudinal systolic velocity (s'), early diastolic velocity (e') and longitudinal displacement (LD) were measured by color TDI. During a median follow-up of 891 days, 64 patients (20%) died. TDI was significantly associated with all-cause mortality, and the risk of dying increased significantly per 1 cm/s decrease in s' (HR of 1.31, 95% CI 1.05-1.63; p=0.018) and e' (HR of 1.17, 95% CI 1.01-1.35; p=0.038) respectively, even after adjustment for age, gender, heart rate, aortic stenosis, DM and LVEF quartiles. LD also proved to be a significant predictor of outcome after multivariate adjustment (HR 1.23; 95% CI 1.05-1.44; p=0.012). The population was stratified according to high or low s' and e'. Patients with low s' and e' had more than three times the risk of mortality compared to the patients with high s' and e' (HR 3.64; 95% CI 1.83-7.26; p<0.001) and remained in significantly higher risk after adjustment for various risk factors.

CONCLUSIONS

Both systolic and diastolic performance, as assessed by TDI, are strong predictors of mortality in patients with atrial fibrillation, and especially the combination of systolic and diastolic dysfunction is a significant prognostic marker.

Design and evaluation of a transesophageal HIFU probe for ultrasound-guided cardiac ablation: simulation of a HIFU mini-maze procedure and preliminary ex vivo trials

Atrial fibrillation (AF) is the most frequent cardiac arrhythmia. Left atrial catheter ablation is currently performed to treat this disease. Several energy sources are used, such as radio-frequency or cryotherapy. The main target of this procedure is to isolate the pulmonary veins. However, significant complications caused by the invasive procedure are described, such as stroke, tamponade, and atrioesophageal fistula, and a second intervention is often needed to avoid atrial fibrillation recurrence. For these reasons, a minimally-invasive device allowing performance of more complex treatments is still needed. High-intensity focused ultrasound (HIFU) can cause deep tissue lesions without damaging intervening tissues. Left atrial ultrasound-guided transesophageal HIFU ablation could have the potential to become a new ablation technique. The goal of this study was to design and test a minimally-invasive ultrasound-guided transesophageal HIFU probe under realistic treatment conditions. First, numerical simulations were conducted to determine the probe geometry, and to validate the feasibility of performing an AF treatment using a HIFU mini-maze (HIFUMM) procedure. Then, a prototype was manufactured and characterized. The 18-mm-diameter probe head housing contained a 3-MHz spherical truncated HIFU transducer divided into 8 rings, with a 5-MHz commercial transesophageal echocardiography (TEE) transducer integrated in the center. Finally, ex vivo experiments were performed to test the impact of the esophagus layer between the probe and the tissue to treat, and also the influence of the lungs and the vascularization on lesion formation. First results show that this prototype successfully created ex vivo transmural myocardial lesions under ultrasound guidance, while preserving intervening tissues (such as the esophagus). Ultrasound-guided transesophageal HIFU can be a good candidate for treatment of AF in the future.

Intracardiac Echocardiography during Catheter-Based Ablation of Atrial Fibrillation

Accurate delineation of the variable left atrial anatomy is of utmost importance during anatomically based ablation procedures for atrial fibrillation targeting the pulmonary veins and possibly other structures of the atria. Intracardiac echocardiography allows real-time visualisation of the left atrium and adjacent structures and thus facilitates precise guidance of catheter-based ablation of atrial fibrillation. In patients with abnormal anatomy of the atria and/or the interatrial septum, intracardiac ultrasound might be especially valuable to guide transseptal access. Software algorithms like CARTOSound (Biosense Webster, Diamond Bar, USA) offer the opportunity to reconstruct multiple two-dimensional ultrasound fans generated by intracardiac echocardiography to a three-dimensional object which can be merged to a computed tomography or magnetic resonance imaging reconstruction of the left atrium. Intracardiac ultrasound reduces dwell time of catheters in the left atrium, fluoroscopy, and procedural time and is invaluable concerning early identification of potential adverse events. The application of intracardiac echocardiography has the great capability to improve success rates of catheter-based ablation procedures.