The role of high-intensity exercise and other emerging risk factors in lone atrial fibrillation (Ln-AF) epidemiology is still under debate. The aim of this study was to analyse the contribution of ...each of the emerging risk factors and the impact of physical activity dose in patients with Ln-AF.
Patients with Ln-AF and age- and sex-matched healthy controls were included in a 2:1 prospective case-control study. We obtained clinical and anthropometric data transthoracic echocardiography, lifetime physical activity questionnaire, 24-h ambulatory blood pressure monitoring, Berlin questionnaire score, and, in patients at high risk for obstructive sleep apnoea (OSA) syndrome, a polysomnography. A total of 115 cases and 57 controls were enrolled. Conditional logistic regression analysis associated height odds ratio (OR) 1.06 1.01-1.11, waist circumference (OR 1.06 1.02-1.11), OSA (OR 5.04 1.44-17.45), and 2000 or more hours of cumulative high-intensity endurance training to a higher AF risk. Our data indicated a U-shaped association between the extent of high-intensity training and AF risk. The risk of AF increased with an accumulated lifetime endurance sport activity ≥ 2,000 h compared with sedentary individuals (OR 3.88 1.55-9.73). Nevertheless, a history of <2000 h of high-intensity training protected against AF when compared with sedentary individuals (OR 0.38 0.12-0.98).
A history of ≥ 2,000 h of vigorous endurance training, tall stature, abdominal obesity, and OSA are frequently encountered as risk factors in patients with Ln-AF. Fewer than 2000 total hours of high-intensity endurance training associates with reduced Ln-AF risk.
Introduction
To investigate the relation between left atrial (LA) volume, sphericity, and fibrotic content derived from contrast‐enhanced cardiac magnetic resonance imaging (CE‐CMR) and their impact ...on the outcome of catheter ablation for atrial fibrillation (AF).
Methods and results
In 83 patients undergoing catheter ablation for AF, CE‐CMR was used to assess LA volume, sphericity, and fibrosis. There was a significant correlation between LA volume and sphericity (R = 0.535, P < 0.001) and between LA volume and fibrosis (R = 0.241, P = 0.029). Multivariate analyses demonstrated that LA volume was the strongest independent predictor of AF recurrence after catheter ablation (1.019, P = 0.018).
Conclusion
LA volume, sphericity, and fibrosis were closely related; however, LA volume was the strongest predictor of AF recurrence after catheter ablation.
Highlights • Molecular autopsy should be implemented in forensic protocols. • Nearly 40% of sudden death young cases carry a cardiac potentially pathogenic variant. • It is crucial to undertake a ...careful genetic analysis in a clinical context. • Genetic analyses help to identify relatives at risk of sudden death.
Display omitted
•Deep networks with pretraining can be used to assess ECGs as abnormal or not.•The decision support system uses ECG raw signals for classification.•The decision support system ...outperforms classification systems clinically approved.•The decision support system outperforms other standard classification methods.•Our approach is promising for referring patients to a cardiology service in clinical practice.
In this paper, we present a new automatic screening method to assess whether a patient from ambulatory care or emergency should be referred to a cardiology service. This method is based on deep neural networks with pretraining and takes as an input a raw ECG signal without annotation.
This work is based on a prospective clinical study that took place at Hospital Clínic in Barcelona between 2011–2012 and recruited 1390 patients. For each patient, we recorded a 12-lead ECG and the diagnosis was conducted by the cardiology service at the same hospital. Normal, borderline normal and normal variant ECGs were labelled as normal and the rest as abnormal.
Our deep neural networks with pretraining were tested through cross-validation with a cohort of 416 test patients. The performance of our model was compared against other standard classification methods such as neural networks without pretraining, Support Vector Machines, Extreme Learning Machines, k-Nearest Neighbours and a professional classification algorithm certified for medical use that annotates the raw ECG signals prior to classification.
The resulting best classifier was a pretrained neural network with three hidden layers and 700 units in every layer. This network yielded an accuracy of 0.8552, a sensitivity of 0.9176 and a specificity of 0.7827. The best alternative classification method was a Support Vector Machine with a Gaussian kernel, which yielded an accuracy of 0.8476, a sensitivity of 0.9446 and a specificity of 0.7346. The professional classification algorithm yielded an accuracy of 0.8407, a sensitivity of 0.8558 and a specificity of 0.8214.
Neural networks with pretraining automatically obtain a representation of the input data without resorting to any annotation and, thus, simplify the process of assessing normality of ECG signals. The results that we have obtained are slightly better than those obtained with the professional classification system and, for some network configurations, they can be considered as exchangeable.
Neural networks with pretraining open up a promising line of research for the automatic assessment of ECG signals that may be used in the future in clinical practice.
Hypertrophic cardiomyopathy (HCM) is the most prevalent inherited heart disease. Next-generation sequencing (NGS) is the preferred genetic test, but the diagnostic value of screening for minor and ...candidate genes, and the role of copy number variants (CNVs) deserves further evaluation.
Three hundred and eighty-seven consecutive unrelated patients with HCM were screened for genetic variants in the 5 most frequent genes (MYBPC3, MYH7, TNNT2, TNNI3 and TPM1) using Sanger sequencing (N = 84) or NGS (N = 303). In the NGS cohort we analyzed 20 additional minor or candidate genes, and applied a proprietary bioinformatics algorithm for detecting CNVs. Additionally, the rate and classification of TTN variants in HCM were compared with 427 patients without structural heart disease.
The percentage of patients with pathogenic/likely pathogenic (P/LP) variants in the main genes was 33.3%, without significant differences between the Sanger sequencing and NGS cohorts. The screening for 20 additional genes revealed LP variants in ACTC1, MYL2, MYL3, TNNC1, GLA and PRKAG2 in 12 patients. This approach resulted in more inconclusive tests (36.0% vs. 9.6%, p<0.001), mostly due to variants of unknown significance (VUS) in TTN. The detection rate of rare variants in TTN was not significantly different to that found in the group of patients without structural heart disease. In the NGS cohort, 4 patients (1.3%) had pathogenic CNVs: 2 deletions in MYBPC3 and 2 deletions involving the complete coding region of PLN.
A small percentage of HCM cases without point mutations in the 5 main genes are explained by P/LP variants in minor or candidate genes and CNVs. Screening for variants in TTN in HCM patients drastically increases the number of inconclusive tests, and shows a rate of VUS that is similar to patients without structural heart disease, suggesting that this gene should not be analyzed for clinical purposes in HCM.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Left atrial (LA) fibrosis can be identified by late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) in patients with atrial fibrillation (AF). However, there is limited information about ...anatomical fibrosis distribution in the left atrium. The aim is to determine whether there is a preferential spatial distribution of fibrosis in the left atrium in patients with AF.
A 3-Tesla LGE-CMR was performed in 113 consecutive patients referred for AF ablation. Images were post-processed and analysed using ADAS-AF software (Galgo Medical), which allows fibrosis identification in 3D colour-coded shells. A regional semiautomatic LA parcellation software was used to divide the atrial wall into 12 segments: 1-4, posterior wall; 5-6, floor; 7, septal wall; 8-11, anterior wall; 12, lateral wall. The presence and amount of fibrosis in each segment was obtained for analysis. After exclusions for artefacts and insufficient image quality, 76 LGE-MRI images (68%) were suitable for fibrosis analysis. Segments 3 and 5, closest to the left inferior pulmonary vein, had significantly higher fibrosis (40.42% ± 23.96 and 25.82% ± 21.24, respectively; P < 0.001), compared with other segments. Segments 8 and 10 in the anterior wall contained the lowest fibrosis (2.54% ± 5.78 and 3.82% ± 11.59, respectively; P < 0.001). Age >60 years was significantly associated with increased LA fibrosis 95% confidence interval (CI) 0.19-8.39, P = 0.04 and persistent AF approached significance (95% CI -0.19% to 7.83%, P = 0.08).
In patients with AF, the fibrotic area is preferentially located at the posterior wall and floor around the antrum of the left inferior pulmonary vein. Age >60 years was associated with increased fibrosis.
Long QT Syndrome is an inherited channelopathy leading to sudden cardiac death due to ventricular arrhythmias. Despite that several genes have been associated with the disease, nearly 20% of cases ...remain without an identified genetic cause. Other genetic alterations such as copy number variations have been recently related to Long QT Syndrome. Our aim was to take advantage of current genetic technologies in a family affected by Long QT Syndrome in order to identify the cause of the disease.
Complete clinical evaluation was performed in all family members. In the index case, a Next Generation Sequencing custom-built panel, including 55 sudden cardiac death-related genes, was used both for detection of sequence and copy number variants. Next Generation Sequencing variants were confirmed by Sanger method. Copy number variations variants were confirmed by Multiplex Ligation dependent Probe Amplification method and at the mRNA level. Confirmed variants and copy number variations identified in the index case were also analyzed in relatives.
In the index case, Next Generation Sequencing revealed a novel variant in TTN and a large deletion in KCNQ1, involving exons 7 and 8. Both variants were confirmed by alternative techniques. The mother and the brother of the index case were also affected by Long QT Syndrome, and family cosegregation was observed for the KCNQ1 deletion, but not for the TTN variant.
Next Generation Sequencing technology allows a comprehensive genetic analysis of arrhythmogenic diseases. We report a copy number variation identified using Next Generation Sequencing analysis in Long QT Syndrome. Clinical and familiar correlation is crucial to elucidate the role of genetic variants identified to distinguish the pathogenic ones from genetic noise.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Brugada syndrome (BrS) is a form of cardiac arrhythmia which may lead to sudden cardiac death. The recommended genetic testing (direct sequencing of SCN5A) uncovers disease-causing SNVs and/or indels ...in ~20% of cases. Limited information exists about the frequency of copy number variants (CNVs) in SCN5A in BrS patients, and the role of CNVs in BrS-minor genes is a completely unexplored field.
220 BrS patients with negative genetic results were studied to detect CNVs in SCN5A. 63 cases were also screened for CNVs in BrS-minor genes. Studies were performed by Multiplex ligation-dependent probe amplification or Next-Generation Sequencing (NGS).
The detection rate for CNVs in SCN5A was 0.45% (1/220). The detected imbalance consisted of a duplication from exon 15 to exon 28, and could potentially explain the BrS phenotype. No CNVs were found in BrS-minor genes.
CNVs in current BrS-related genes are uncommon among BrS patients. However, as these rearrangements may underlie a portion of cases and they undergo unnoticed by traditional sequencing, an appealing alternative to conventional studies in these patients could be targeted NGS, including in a single experiment the study of SNVs, indels and CNVs in all the known BrS-related genes.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
PDF
