Publications
158 results found
Shen CP, Freed BC, Walter DP, et al., 2023, Convolution Neural Network Algorithm for Shockable Arrhythmia Classification Within a Digitally Connected Automated External Defibrillator., J Am Heart Assoc
Background Diagnosis of shockable rhythms leading to defibrillation remains integral to improving out-of-hospital cardiac arrest outcomes. New machine learning techniques have emerged to diagnose arrhythmias on ECGs. In out-of-hospital cardiac arrest, an algorithm within an automated external defibrillator is the major determinant to deliver defibrillation. This study developed and validated the performance of a convolution neural network (CNN) to diagnose shockable arrhythmias within a novel, miniaturized automated external defibrillator. Methods and Results There were 26 464 single-lead ECGs that comprised the study data set. ECGs of 7-s duration were retrospectively adjudicated by 3 physician readers (N=18 total readers). After exclusions (N=1582), ECGs were divided into training (N=23 156), validation (N=721), and test data sets (N=1005). CNN performance to diagnose shockable and nonshockable rhythms was reported with area under the receiver operating characteristic curve analysis, F1, and sensitivity and specificity calculations. The duration for the CNN to output was reported with the algorithm running within the automated external defibrillator. Internal and external validation analyses included CNN performance among arrhythmias, often mistaken for shockable rhythms, and performance among ECGs modified with noise to mimic artifacts. The CNN algorithm achieved an area under the receiver operating characteristic curve of 0.995 (95% CI, 0.990-1.0), sensitivity of 98%, and specificity of 100% to diagnose shockable rhythms. The F1 scores were 0.990 and 0.995 for shockable and nonshockable rhythms, respectively. After input of a 7-s ECG, the CNN generated an output in 383±29 ms (total time of 7.383 s). The CNN outperformed adjudicators in classifying atrial arrhythmias as nonshockable (specificity of 99.3%-98.1%) and was robust against noise artifacts (area under the receiver operating characteristic curve range, 0.871-0.999). Con
Sau A, Ng FS, 2023, Hypertrophic cardiomyopathy risk stratification based on clinical or dynamic electrophysiological features: two sides of the same coin., Europace
Coyle C, Koutsoftidis S, Kim M-Y, et al., 2023, Feasibility of mapping and ablating ectopy-triggering ganglionated plexus reproducibly in persistent atrial fibrillation., J Interv Card Electrophysiol
BACKGROUND: Ablation of autonomic ectopy-triggering ganglionated plexuses (ET-GP) has been used to treat paroxysmal atrial fibrillation (AF). It is not known if ET-GP localisation is reproducible between different stimulators or whether ET-GP can be mapped and ablated in persistent AF. We tested the reproducibility of the left atrial ET-GP location using different high-frequency high-output stimulators in AF. In addition, we tested the feasibility of identifying ET-GP locations in persistent atrial fibrillation. METHODS: Nine patients undergoing clinically-indicated paroxysmal AF ablation received pacing-synchronised high-frequency stimulation (HFS), delivered in SR during the left atrial refractory period, to compare ET-GP localisation between a custom-built current-controlled stimulator (Tau20) and a voltage-controlled stimulator (Grass S88, SIU5). Two patients with persistent AF underwent cardioversion, left atrial ET-GP mapping with the Tau20 and ablation (Precision™, Tacticath™ [n = 1] or Carto™, SmartTouch™ [n = 1]). Pulmonary vein isolation (PVI) was not performed. Efficacy of ablation at ET-GP sites alone without PVI was assessed at 1 year. RESULTS: The mean output to identify ET-GP was 34 mA (n = 5). Reproducibility of response to synchronised HFS was 100% (Tau20 vs Grass S88; [n = 16] [kappa = 1, SE = 0.00, 95% CI 1 to 1)][Tau20 v Tau20; [n = 13] [kappa = 1, SE = 0, 95% CI 1 to 1]). Two patients with persistent AF had 10 and 7 ET-GP sites identified requiring 6 and 3 min of radiofrequency ablation respectively to abolish ET-GP response. Both patients were free from AF for > 365 days without anti-arrhythmics. CONCLUSIONS: ET-GP sites are identified at the same location by different stimulators. ET-GP ablation alone was able to prevent AF recurrence in persistent AF, and fur
Kappadan V, Sohi A, Parlitz U, et al., 2023, Optical mapping of contracting hearts., J Physiol
Optical mapping is a widely used tool to record and visualize the electrophysiological properties in a variety of myocardial preparations such as Langendorff-perfused isolated hearts, coronary-perfused wedge preparations, and cell culture monolayers. Motion artifact originating from the mechanical contraction of the myocardium creates a significant challenge to performing optical mapping of contracting hearts. Hence, to minimize the motion artifact, cardiac optical mapping studies are mostly performed on non-contracting hearts, where the mechanical contraction is removed using pharmacological excitation-contraction uncouplers. However, such experimental preparations eliminate the possibility of electromechanical interaction, and effects such as mechano-electric feedback cannot be studied. Recent developments in computer vision algorithms and ratiometric techniques have opened the possibility of performing optical mapping studies on isolated contracting hearts. In this review, we discuss the existing techniques and challenges of optical mapping of contracting hearts.
Ali N, Arnold AD, Miyazawa AA, et al., 2023, Comparison of methods for delivering cardiac resynchronization therapy: an acute electrical and haemodynamic within-patient comparison of left bundle branch area, His bundle, and biventricular pacing, EP Europace, Pages: 1-8, ISSN: 1099-5129
AimsLeft bundle branch area pacing (LBBAP) is a promising method for delivering cardiac resynchronization therapy (CRT), but its relative physiological effectiveness compared with His bundle pacing (HBP) is unknown. We conducted a within-patient comparison of HBP, LBBAP, and biventricular pacing (BVP).Methods and resultsPatients referred for CRT were recruited. We assessed electrical response using non-invasive mapping, and acute haemodynamic response using a high-precision haemodynamic protocol. Nineteen patients were recruited: 14 male, mean LVEF of 30%. Twelve had time for BVP measurements. All three modalities reduced total ventricular activation time (TVAT), (ΔTVATHBP -43 ± 14 ms and ΔTVATLBBAP −35 ± 20 ms vs. ΔTVATBVP −19 ± 30 ms, P = 0.03 and P = 0.1, respectively). HBP produced a significantly greater reduction in TVAT compared with LBBAP in all 19 patients (−46 ± 15 ms, −36 ± 17 ms, P = 0.03). His bundle pacing and LBBAP reduced left ventricular activation time (LVAT) more than BVP (ΔLVATHBP −43 ± 16 ms, P < 0.01 vs. BVP, ΔLVATLBBAP −45 ± 17 ms, P < 0.01 vs. BVP, ΔLVATBVP −13 ± 36 ms), with no difference between HBP and LBBAP (P = 0.65). Acute systolic blood pressure was increased by all three modalities. In the 12 with BVP, greater improvement was seen with HBP and LBBAP (6.4 ± 3.8 mmHg BVP, 8.1 ± 3.8 mmHg HBP, P = 0.02 vs. BVP and 8.4 ± 8.2 mmHg for LBBAP, P = 0.3 vs. BVP), with no difference between HBP and LBBAP (P = 0.8).ConclusionHBP delivered better ventricular resynchronization than LBBAP because right ventricular activation was slower during LBBAP. But LBBAP was not inferior to HBP with respect to LV electrical resynchronization and acute haemodynamic response.
Kim MY, Nesbitt J, Koutsoftidis S, et al., 2023, Immunohistochemical characteristics of local sites that trigger atrial arrhythmias in response to high frequency stimulation, EP Europace, Vol: 25, Pages: 726-738, ISSN: 1099-5129
Introduction: The response to high frequency stimulation (HFS) is used to locate putative sites of ganglionated plexuses (GPs), which are implicated in triggering atrial fibrillation (AF). Objective: To identify topological and immunohistochemical characteristics of presumed GP sites functionally identified by HFS. Methods: 63 atrial sites were tested with HFS in 4 Langendorff-perfused porcine hearts. A 3.5mm tip quadripolar ablation catheter was used to stimulate and deliver HFS to the left and right atrial epicardium, within the local atrial refractory period. Tissue samples from sites triggering atrial ectopy/AF (ET) sites and non-ET sites were stained with choline acetyl transferase (ChAT) and tyrosine hydroxylase (TH), for quantification of parasympathetic and sympathetic nerves, respectively. The average cross-sectional area (CSA) of nerves was also calculated.Results: Histomorphometry of 6 ET sites (9.5%) identified by HFS evoking at least a single atrial ectopic was compared with non-ET sites. All ET sites contained ChAT-immunoreactive (ChAT-IR) and/or TH-immunoreactive nerves (TH-IR). Nerve density was greater in ET sites compared to non-ET sites (nerves/cm2: 162.3 ±110.9 vs 69.65 ±72.48; p=0.047). Overall, TH-IR nerves had larger CSA than ChAT-IR nerves (µm2: 11,196 ± 35,141 vs 2,070 ± 5,841; p<0.0001), but in ET sites, TH-IR nerves were smaller than in non-ET sites (µm2: 6,021±14,586 vs 25,254 ± 61,499; p<0.001).Conclusions: ET sites identified by HFS contained higher density of smaller nerves than non-ET sites. Majority of these nerves were within the atrial myocardium. This has important clinical implications on devising an effective therapeutic strategy for targeting autonomic triggers of AF.
Rayes B, Ardissino M, Slob E, et al., 2023, Association of hypertensive disorders of pregnancy with future cardiovascular disease, Jama Network Open, Vol: 6, Pages: 1-13, ISSN: 2574-3805
Importance Hypertensive disorders in pregnancy (HDPs) are major causes of maternal and fetal morbidity and are observationally associated with future maternal risk of cardiovascular disease. However, observational results may be subject to residual confounding and bias.Objective To investigate the association of HDPs with multiple cardiovascular diseases.Design, Setting, and Participants A genome-wide genetic association study using mendelian randomization (MR) was performed from February 16 to March 4, 2022. Primary analysis was conducted using inverse-variance-weighted MR. Mediation analyses were performed using a multivariable MR framework. All studies included patients predominantly of European ancestry. Female-specific summary-level data from FinnGen (sixth release).Exposures Uncorrelated (r2<0.001) single-nucleotide variants (SNVs) were selected as instrumental variants from the FinnGen consortium summary statistics for exposures of any HDP, gestational hypertension, and preeclampsia or eclampsia.Main Outcomes and Measures Genetic association estimates for outcomes were extracted from genome-wide association studies of 122 733 cases for coronary artery disease, 34 217 cases for ischemic stroke, 47 309 cases for heart failure, and 60 620 cases for atrial fibrillation.Results Genetically predicted HDPs were associated with a higher risk of coronary artery disease (odds ratio [OR], 1.24; 95% CI, 1.08-1.43; P = .002); this association was evident for both gestational hypertension (OR, 1.08; 95% CI, 1.00-1.17; P = .04) and preeclampsia/eclampsia (OR, 1.06; 95% CI, 1.01-1.12; P = .03). Genetically predicted HDPs were also associated with a higher risk of ischemic stroke (OR, 1.27; 95% CI, 1.12-1.44; P = 2.87 × 10−4). Mediation analysis revealed a partial attenuation of the effect of HDPs on coronary artery disease after adjustment for systolic blood pressure (total effect OR
Sau A, 2023, Artificial intelligence-enabled electrocardiogram to distinguish atrioventricular re-entrant tachycardia from atrioventricular nodal re-entrant tachycardia, Cardiovascular Digital Health Journal, Pages: 1-8, ISSN: 2666-6936
BackgroundAccurately determining arrhythmia mechanism from a 12-lead electrocardiogram (ECG) of supraventricular tachycardia can be challenging. We hypothesized a convolutional neural network (CNN) can be trained to classify atrioventricular re-entrant tachycardia (AVRT) vs atrioventricular nodal re-entrant tachycardia (AVNRT) from the 12-lead ECG, when using findings from the invasive electrophysiology (EP) study as the gold standard.MethodsWe trained a CNN on data from 124 patients undergoing EP studies with a final diagnosis of AVRT or AVNRT. A total of 4962 5-second 12-lead ECG segments were used for training. Each case was labeled AVRT or AVNRT based on the findings of the EP study. The model performance was evaluated against a hold-out test set of 31 patients and compared to an existing manual algorithm.ResultsThe model had an accuracy of 77.4% in distinguishing between AVRT and AVNRT. The area under the receiver operating characteristic curve was 0.80. In comparison, the existing manual algorithm achieved an accuracy of 67.7% on the same test set. Saliency mapping demonstrated the network used the expected sections of the ECGs for diagnoses; these were the QRS complexes that may contain retrograde P waves.ConclusionWe describe the first neural network trained to differentiate AVRT from AVNRT. Accurate diagnosis of arrhythmia mechanism from a 12-lead ECG could aid preprocedural counseling, consent, and procedure planning. The current accuracy from our neural network is modest but may be improved with a larger training dataset.
Wu H, Patel KHK, Li X, et al., 2022, A fully-automated paper ECG digitisation algorithm using deep learning, Scientific Reports, Vol: 12, ISSN: 2045-2322
There is increasing focus on applying deep learning methods to electrocardiograms (ECGs), with recent studies showing that neural networks (NNs) can predict future heart failure or atrial fibrillation from the ECG alone. However, large numbers of ECGs are needed to train NNs, and many ECGs are currently only in paper format, which are not suitable for NN training. We developed a fully-automated online ECG digitisation tool to convert scanned paper ECGs into digital signals. Using automated horizontal and vertical anchor point detection, the algorithm automatically segments the ECG image into separate images for the 12 leads and a dynamical morphological algorithm is then applied to extract the signal of interest. We then validated the performance of the algorithm on 515 digital ECGs, of which 45 were printed, scanned and redigitised. The automated digitisation tool achieved 99.0% correlation between the digitised signals and the ground truth ECG (n = 515 standard 3-by-4 ECGs) after excluding ECGs with overlap of lead signals. Without exclusion, the performance of average correlation was from 90 to 97% across the leads on all 3-by-4 ECGs. There was a 97% correlation for 12-by-1 and 3-by-1 ECG formats after excluding ECGs with overlap of lead signals. Without exclusion, the average correlation of some leads in 12-by-1 ECGs was 60–70% and the average correlation of 3-by-1 ECGs achieved 80–90%. ECGs that were printed, scanned, and redigitised, our tool achieved 96% correlation with the original signals. We have developed and validated a fully-automated, user-friendly, online ECG digitisation tool. Unlike other available tools, this does not require any manual segmentation of ECG signals. Our tool can facilitate the rapid and automated digitisation of large repositories of paper ECGs to allow them to be used for deep learning projects.
Ardissino M, Slob EAW, Carter P, et al., 2022, Sex-specific reproductive factors augment cardiovascular disease risk in females: a Mendelian randomization study, Journal of the American Heart Association, ISSN: 2047-9980
Background: Cardiovascular disease is a major cause of morbidity and mortality in women. Observational studies suggest that reproductive factors are associated with cardiovascular disease risk, but these are liable to influence by residual confounding. This study aims to explore the causal role of reproductive factors on cardiovascular disease in women using Mendelian randomisation and explore potentially modifiable mediating pathways amenable to intervention.Methods and results: Uncorrelated (r2<0.001), genome-wide significant (p<5x10 -8) SNPs were extracted from sex-specific genome-wide association studies of age at first birth, number of live births, age at menarche and age at menopause. Inverse-variance weighted Mendelian randomisation was utilised for primary analyses on outcomes of atrial fibrillation, coronary artery disease, heart failure, ischaemic stroke, and stroke. Earlier genetically-predicted age at first birth increased risk of coronary artery disease (OR per 1-year lower 1.49, 95%CI 1.28-1.74, p=3.72x10 -7 ), heart failure (OR 1.27, 95%CI 1.06-1.53, p=0.009) and stroke (OR 1.25, 95%CI 1.00-1.56, p=0.048), with partial mediation through body mass index, type 2 diabetes, blood pressure and cholesterol traits. Higher genetically-predicted number of live births increased risk of atrial fibrillation (OR per category increase <2 vs 2 vs>2 live births 2.91, 95%CI 1.16-7.29, p=0.023), heart failure (OR 1.90, 95%CI 1.28-2.82, p=0.001), ischaemic stroke (OR 1.86, 95%CI 1.03-3.37, p=0.039) and stroke (OR 2.07, 95%CI 1.22-3.52, p=0.007). Earlier genetically-predicted age at menarche increased risk of coronary artery disease (OR per 1-year lower 1.10, 95%CI 1.06-1.14, p=1.68 x10 -6) and heart failure (OR 1.12, 95%CI 1.07-1.17, p=5.06x10 -7), and both associations were at least partly mediated by body mass index.Conclusion: These results support a causal role of a number of reproductive factors on cardiovascular disease in women, and identify multiple
Ardissino M, Reddy RK, Ng FS, 2022, Type 2 Diabetes and Atrial Fibrillation: Exploring Causal Pathways Using Mendelian Randomization, Scientific Sessions of the American-Heart-Association / Resuscitation Science Symposium, Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0009-7322
Ardissino M, Slob E, Rogne T, et al., 2022, Impact of reproductive factors on major cardiovascular disease risk in women: a Mendelian randomization study, Publisher: OXFORD UNIV PRESS, Pages: 2500-2500, ISSN: 0195-668X
Ardissino M, Rajasundaram S, Reddy R, et al., 2022, Safety of beta-blocker and calcium channel blocker antihypertensive drugs in pregnancy: a Mendelian randomization study, BMC Medicine, Vol: 20, ISSN: 1741-7015
Background: Beta-blocker (BB) and calcium channel blocker (CCB)antihypertensive drugs are commonly used in pregnancy. However, data on theirrelative impact on maternal and fetal outcomes are limited. We leveraged geneticvariants mimicking BB and CCB antihypertensive drugs to investigate their effects onrisk of pre-eclampsia, gestational diabetes and birthweight using the Mendelianrandomization paradigm.Methods: Genetic association estimates for systolic blood pressure (SBP) wereextracted from summary data of a genome-wide association study (GWAS) on757,601 participants. Uncorrelated single-nucleotide polymorphisms (SNPs)associated with SBP (p<5x10-8) in BB and CCB drug target gene regions wereselected as proxies for drug target perturbation. Genetic association estimates forthe outcomes were extracted from GWASs on 4,743 cases and 136,325 controls(women without a hypertensive disorder in pregnancy) for pre-eclampsia oreclampsia, 7,676 cases and 130,424 controls (women without any pregnancy-relatedmorbidity) for gestational diabetes, and 155,202 women (who have given birth atleast once) for birthweight of the first child. All studies were in European ancestrypopulations. Mendelian randomization estimates were generated using the twosample inverse-variance weighted model.Results: Although not reaching the conventional threshold for statistical significance,genetically-proxied BB was associated with reduced risk of pre-eclampsia (OR per10mmHg SBP reduction 0.27, 95%CI 0.06-1.19, p=0.08) and increased risk ofgestational diabetes (OR per 10mmHg SBP reduction 2.01, 95%CI 0.91-4.42,p=0.08), and significantly associated with lower birthweight of first child (beta per 10mmHg SBP reduction -0.27, 95%CI -0.39 to -0.15, p=1.90x10-5). Geneticallyproxied CCB was associated with reduced risk of pre-eclampsia and eclampsia (OR0.62, 95%CI 0.43-0.89, p=9.33x10-3), and was not associated with gestationaldiabetes (OR 1.05, 95% CI 0.76-1.45, p=0.76) or changes in birthweight of first
Sau A, Ibrahim S, Ahmed A, et al., 2022, Artificial intelligence-enabled electrocardiogram to distinguish cavotricuspid isthmus dependence from other atrial tachycardia mechanisms, European Heart Journal – Digital Health, Vol: 3, Pages: 405-414, ISSN: 2634-3916
Aims:Accurately determining atrial arrhythmia mechanisms from a 12-lead electrocardiogram (ECG) can be challenging. Given the high success rate of cavotricuspid isthmus (CTI) ablation, identification of CTI-dependent typical atrial flutter (AFL) is important for treatment decisions and procedure planning. We sought to train a convolutional neural network (CNN) to classify CTI-dependent AFL vs. non-CTI dependent atrial tachycardia (AT), using data from the invasive electrophysiology (EP) study as the gold standard.Methods and results:We trained a CNN on data from 231 patients undergoing EP studies for atrial tachyarrhythmia. A total of 13 500 five-second 12-lead ECG segments were used for training. Each case was labelled CTI-dependent AFL or non-CTI-dependent AT based on the findings of the EP study. The model performance was evaluated against a test set of 57 patients. A survey of electrophysiologists in Europe was undertaken on the same 57 ECGs. The model had an accuracy of 86% (95% CI 0.77–0.95) compared to median expert electrophysiologist accuracy of 79% (range 70–84%). In the two thirds of test set cases (38/57) where both the model and electrophysiologist consensus were in agreement, the prediction accuracy was 100%. Saliency mapping demonstrated atrial activation was the most important segment of the ECG for determining model output.Conclusion:We describe the first CNN trained to differentiate CTI-dependent AFL from other AT using the ECG. Our model matched and complemented expert electrophysiologist performance. Automated artificial intelligence-enhanced ECG analysis could help guide treatment decisions and plan ablation procedures for patients with organized atrial arrhythmias.
Patel K, li X, xu X, et al., 2022, Increasing adiposity is associated with QTc interval prolongation and increased ventricular arrhythmic risk in the context of metabolic dysfunction: results from the UK Biobank, Frontiers in Cardiovascular Medicine, Vol: 9, Pages: 1-11, ISSN: 2297-055X
Background: Small-scale studies have linked obesity (Ob) and metabolic ill-health with proarrhythmic repolarisation abnormalities. Whether these are observed at a population-scale, modulated by individuals’ genetics and confer higher risks of ventricular arrhythmias (VA) are not known. Methods and Results: Firstly, using the UK Biobank, the association between adiposity and QTc interval was assessed in participants with resting 12-lead ECG (n=23,683), and a polygenic risk score was developed to investigate any modulatory effect of genetics. Participants were also categorised into four phenotypes according to presence (+) or absence (-) of Ob, and if they were metabolically unhealthy (MU+) or not (MU-). QTc was positively associated with body mass index, body fat, waist:hip ratio, and hip and waist girths. Individuals’ genetics had no significant modulatory effect on QTc-prolonging effects of increasing adiposity. QTc was comparably longer in those with metabolic perturbationwithout obesity (Ob-MU+) and obesity alone (Ob+MU-) compared to individuals with neither (Ob-MU-), and their co-existence (Ob+MU+) had an additive effect on QTc interval. Secondly, for 502,536 participants in the UK Biobank, odds ratios (OR) for ventricular arrhythmias (VA) were computed for the four clinical phenotypes above using their past medical records. Referenced to Ob-MU-, ORs for VA in Ob-MU+ males and females were 5.96 (95%CI: 4.70-7.55) and 5.10 (95%CI: 3.34-7.80), respectively. OR for Ob+MU+ were 6.99 (95%CI: 5.72-8.54) and 3.56 (95%CI: 2.66-4.77) in males and females, respectively. Conclusion: Adiposity and metabolic perturbation increase QTc to a similar degree, and their co-existence exerts an additive effect. These effects are not modulated by individuals’ genetics. Metabolic ill-health is associated with higher OR for VA than obesity.
Falkenberg McGillivray M, Coleman JA, Dobson S, et al., 2022, Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps, PLoS One, Vol: 17, Pages: 1-24, ISSN: 1932-6203
Micro-anatomical reentry has been identified as a potential driver of atrial fibrillation (AF). In this paper, we introduce a novel computational method which aims to identify which atrial regions are most susceptible to micro-reentry. The approach, which considers the structural basis for micro-reentry only, is based on the premise that the accumulation of electrically insulating interstitial fibrosis can be modelled by simulating percolation-like phenomena on spatial networks. Our results suggest that at high coupling, where micro-reentry is rare, the micro-reentrant substrate is highly clusteredin areas where the atrial walls are thin and have convex wall morphology, likely facilitating localised treatment via ablation. However, as transverse connections between fibres are removed, mimicking the accumulation of interstitial fibrosis, the substrate becomes less spatially clustered, and the bias to forming in thin, convex regions of the atria is reduced, possibly restricting the efficacy of localised ablation. Comparing our algorithm on image-based models with and without atrial fibre structure, we find thatstrong longitudinal fibre coupling can suppress the micro-reentrant substrate, whereas regions with disordered fibre orientations have an enhanced risk of micro-reentry. With further development, these methods may be useful for modelling the temporal development of the fibrotic substrate on an individualised basis.
Sivanandarajah P, Wu H, Bajaj N, et al., 2022, Is machine learning the future for atrial fibrillation screening?, Cardiovascular Digital Health Journal, Vol: 3, Pages: 136-145, ISSN: 2666-6936
Atrial fibrillation (AF) is the most common arrhythmia and causes significant morbidity and mortality. Early identification of AF may lead to early treatment of AF and may thus prevent AF-related strokes and complications. However, there is no current formal, cost-effective strategy for population screening for AF. In this review, we give a brief overview of targeted screening for AF, AF risk score models used for screening and describe the different screening tools. We then go on to extensively discuss the potential applications of machine learning in AF screening.
Nagy SZ, Kasi P, Afonso VX, et al., 2022, Cycle length evaluation in persistent atrial fibrillation using kernel density estimation to identify transient and stable rapid atrial activity, Cardiovascular Engineering and Technology, Vol: 13, Pages: 219-233, ISSN: 1869-408X
PurposeLeft atrial (LA) rapid AF activity has been shown to co-localise with areas of successful atrial fibrillation termination by catheter ablation. We describe a technique that identifies rapid and regular activity.MethodsEight-second AF electrograms were recorded from LA regions during ablation for psAF. Local activation was annotated manually on bipolar signals and where these were of poor quality, we inspected unipolar signals. Dominant cycle length (DCL) was calculated from annotation pairs representing a single activation interval, using a probability density function (PDF) with kernel density estimation. Cumulative annotation duration compared to total segment length defined electrogram quality. DCL results were compared to dominant frequency (DF) and averaging.ResultsIn total 507 8 s AF segments were analysed from 7 patients. Spearman’s correlation coefficient was 0.758 between independent annotators (P < 0.001), 0.837–0.94 between 8 s and ≥ 4 s segments (P < 0.001), 0.541 between DCL and DF (P < 0.001), and 0.79 between DCL and averaging (P < 0.001). Poorer segment organization gave greater errors between DCL and DF.ConclusionDCL identifies rapid atrial activity that may represent psAF drivers. This study uses DCL as a tool to evaluate the dynamic, patient specific properties of psAF by identifying rapid and regular activity. If automated, this technique could rapidly identify areas for ablation in psAF.
Kim M-Y, Coyle C, Tomlinson DR, et al., 2022, Ectopy-triggering ganglionated plexus ablation to prevent atrial fibrillation: GANGLIA-AF study., Heart Rhythm, Vol: 19, Pages: 516-524, ISSN: 1547-5271
BACKGROUND: The ganglionated plexuses (GP) of the intrinsic cardiac autonomic system may play a role in atrial fibrillation (AF). OBJECTIVES: We hypothesized that ablating the ectopy-triggering GPs (ET-GP) prevents AF. METHODS: GANGLIA-AF (NCT02487654) was a prospective, randomized, controlled, 3-centre trial. ET-GP were mapped using high frequency stimulation (HFS), delivered within the atrial refractory period and ablated until non-functional. If triggered AF became incessant, atrioventricular dissociating GPs (AVD-GP) were ablated. We compared GP ablation (GPA) without pulmonary vein isolation (PVI) against PVI, in patients with paroxysmal AF. Follow-up was for 12 months including 3-monthly 48hr Holter monitors. The primary endpoint was documented ≥30s atrial arrhythmia after a 3-month blanking period. RESULTS: 102 randomized patients were analysed on a per-protocol basis after GPA (n=52) or PVI (n=50). GPA patients had 89±26 HFS sites tested, identifying median 18.5 (IQR 16; 21%) GPs. RF ablation time in GPA was 22.9±9.8mins and 38±14.4mins in PVI (p<0.0001). The freedom from ≥30s atrial arrhythmia at 12-month follow-up with GPA was 50% (26/52) vs 64% (32/50) with PVI (log rank p=0.09). ET-GP ablation without AVD-GP ablation achieved 58% (22/38) freedom from the primary endpoint. There was a significantly higher reduction in AAD usage post-ablation after GPA vs PVI (55.5% vs 36%; p=0.05). Patients were referred for redo ablations in 31% (16/52) after GPA and 24% (12/50) after PVI (p=0.53). CONCLUSIONS: GPA did not prevent atrial arrhythmias more than PVI. However, less RF ablation was delivered to achieve a higher reduction in AAD usage with GPA than PVI.
Sau A, Kaura A, Ahmed A, et al., 2022, Prognostic significance of ventricular arrhythmias in 13444 patients with acute coronary syndrome: a retrospective cohort study based on routine clinical data (NIHR Health Informatics Collaborative VA-ACS Study), Journal of the American Heart Association, Vol: 11, Pages: 1-19, ISSN: 2047-9980
Background: A minority of acute coronary syndrome (ACS) cases are associated with ventricular arrhythmias (VA) and/or cardiac arrest (CA). We investigated the effect of VA/CA at time of ACS on long-term outcomes.Methods and Results: We analysed routine clinical data from 5 NHS Trusts in the United Kingdom, collected between 2010 and 2017, by the National Institute for Health Research Health Informatics Collaborative (NIHR HIC).13,444 patients with ACS, of which 376 (2.8%) had concurrent VA, survived to hospital discharge and were followed up for a median of 3.42 years. Patients with VA or CA at index presentation had significantly increased risks of subsequent VA during follow-up (VA group: adjusted HR 4.15, 95% CI 2.42-7.09, CA group: adjusted HR 2.60 95% CI 1.23-5.48). Patients who suffered a CA in the context of ACS and survived to discharge also had a 36% increase in long-term mortality (adjusted hazard ratio 1.36 (95% 1.04-1.78)), though the concurrent diagnosis of VA alone during ACS did not affect all-cause mortality (adjusted HR 1.03, 95% CI 0.80-1.33). Conclusions: Patients who develop VA or CA during ACS, who survive to discharge, have increased risks of subsequent VA, while those who have CA during ACS also have an increase in long-term mortality. These individuals may represent a subgroup at greater risk of subsequent arrhythmic events due to intrinsically lower thresholds for developing VA.
Ardissino M, Slob E, Millar O, et al., 2022, Maternal hypertension increases risk of pre-eclampsia and low fetal birthweight: genetic evidence from a Mendelian randomization study, Hypertension, Vol: 79, Pages: 1-11, ISSN: 0194-911X
Background: Maternal cardiovascular risk factors have been associated with adverse maternal and fetal outcomes. Given the difficulty in establishing causal relationships using epidemiological data, we applied Mendelian randomization to explore the role of cardiovascular risk factors on risk of developing pre-eclampsia or eclampsia, and low fetal birthweight.Methods: Uncorrelated single nucleotide polymorphisms associated systolic blood pressure, body mass index, type 2 diabetes mellitus, low-density lipoprotein with cholesterol, smoking, urinary albumin-to-creatinine ratio and estimated glomerular filtration rate at genome-wide significance in studies of 298,957 to 1,201,909 European ancestry participants were selected as instrumental variables. A two-sample Mendelian randomization study was performed with primary outcome of pre-eclampsia or eclampsia (PET). Risk factors associated with PET were further investigated for their association with low birthweight. Results: Higher genetically-predicted systolic blood pressure was associated increased risk of PET [odds ratio (OR) per 1-SD systolic blood pressure increase 1.90 (95% confidence interval (CI)1.45-2.49;p=3.23x10-6 and reduced birthweight (OR=0.83; 95%CI=0.79-0.86;p=3.96x10-18), and this was not mediated by PET. Body mass index and type 2 diabetes were also associated with PET (respectively, OR per 1-SD body mass index increase=1.67 95%CI=1.44-1.94,;p=7.45x10-12; and OR per logOR increase type 2 diabetes=1.11 95%CI=1.04-1.19p;=1.19x10-3), but not with reduced birthweight. Conclusions: Our results provide evidence for causal effects of systolic blood pressure, body mass index and type 2 diabetes on PET, and identify that systolic blood pressure is associated with reduced birthweight independently of PET. The results provide insight into the pathophysiological basis of PET and identify hypertension as a potentially modifiable risk factor amenable to therapeutic intervention.
Ardissino M, Reddy RK, Slob EAW, et al., 2022, Sleep disordered breathing, obesity and atrial fibrillation: a mendelian randomisation study, Geneses, Vol: 13, Pages: 1-11, ISSN: 1155-3219
It remains unclear whether the association between obstructive sleep apnoea (OSA), a form of sleep-disordered breathing (SDB), and atrial fibrillation (AF) is causal or mediated by shared co-morbidities such as obesity. Existing observational studies are conflicting and limited by confounding and reverse causality. We performed Mendelian randomisation (MR) to investigate the causal relationships between SDB, body mass index (BMI) and AF. Single-nucleotide polymorphisms associated with SDB (n = 29) and BMI (n = 453) were selected as instrumental variables to investigate the effects of SDB and BMI on AF, using genetic association data on 55,114 AF cases and 482,295 controls. Primary analysis was conducted using inverse-variance weighted MR. Higher genetically predicted SDB and BMI were associated with increased risk of AF (OR per log OR increase in snoring liability 2.09 (95% CI 1.10–3.98), p = 0.03; OR per 1-SD increase in BMI 1.33 (95% CI 1.24–1.42), p < 0.001). The association between SDB and AF was not observed in sensitivity analyses, whilst associations between BMI and AF remained consistent. Similarly, in multivariable MR, SDB was not associated with AF after adjusting for BMI (OR 0.68 (95% CI 0.42–1.10), p = 0.12). Higher BMI remained associated with increased risk of AF after adjusting for OSA (OR 1.40 (95% CI 1.30–1.51), p < 0.001). Elevated BMI appears causal for AF, independent of SDB. Our data suggest that the association between SDB, in general, and AF is attributable to mediation or confounding from obesity, though we cannot exclude that more severe SDB phenotypes (i.e., OSA) are causal for AF.
Patel KHK, Reddy RK, Sau A, et al., 2022, Obesity as a risk factor for cardiac arrhythmias., BMJ Med, Vol: 1
Obesity is global health problem with an estimated three billion people worldwide being classified as overweight or obese. In addition to being associated with a range of adverse health outcomes, obesity is linked to higher risks of atrial and ventricular arrhythmias, as well as sudden cardiac death. Obesity is a multifactorial disease that often co-exists with hypertension, diabetes, and sleep apnoea, which are also independent risk factors for cardiac arrhythmias. Nevertheless, compelling evidence suggests that increasing adiposity is an independent proarrhythmic risk factor and that weight loss can be a mitigating and preventative intervention to reduce arrhythmia incidence. This review briefly outlines the economic and social burden of obesity and summarises evidence for the direct and indirect effects of increasing adiposity on risk of atrial and ventricular arrhythmias. The paper also summarises the evidence for electrocardiographic changes indicative of obesity-related atrial and ventricular remodelling and how weight reduction and management of comorbidity might reduce arrhythmic burden.
Patel K, Hwang T, Se Liebers C, et al., 2021, Epicardial adipose tissue as a mediator of cardiac arrhythmias, American Journal of Physiology: Heart and Circulatory Physiology, Vol: 322, ISSN: 0363-6135
Obesity is associated with higher risks of cardiac arrhythmias. Although this may be partly explained by concurrent cardiometabolic ill-health, growing evidence suggests that increasing adiposity independently confers risk for arrhythmias. Amongst fat depots, epicardial adipose tissue (EAT) exhibits a proinflammatory secretome, and given the lack of fascial separation, has been implicated as a transducer of inflammation to the underlying myocardium. The present review explores the mechanisms underpinning adverse electrophysiological remodelling as a consequence of EAT accumulation and the consequent inflammation. We first describe the physiological and pathophysiological function of EAT and its unique secretome, and subsequently discuss the evidence for ionic channel and connexin expression modulation as well as fibrotic remodelling induced by cytokines and free fatty acids that are secreted by EAT. Finally, we highlight how weight reduction and regression of EAT volume may cause reverse remodelling to ameliorate arrhythmic risk.
Patel K, Li X, Sun L, et al., 2021, Neural networks applied to 12-lead electrocardiograms predict body mass index, visceral adiposity and concurrent cardiometabolic ill-health, Cardiovascular Digital Health Journal, Vol: 2, Pages: S1-S10, ISSN: 2666-6936
BackgroundObesity is associated with electrophysiological remodeling, which manifests as detectable changes on the surface electrocardiogram (ECG).ObjectiveTo develop neural networks (NN) to predict body mass index (BMI) from ECGs and test the hypothesis that discrepancies between NN-predicted BMI and measured BMI are indicative of underlying adiposity and/or concurrent cardiometabolic ill-health.MethodsNN models were developed using 36,856 12-lead resting ECGs from the UK Biobank. Two architectures were developed for continuous and categorical BMI estimation (normal weight [BMI <25 kg/m2] vs overweight/obese [BMI ≥25 kg/m2]). Models for male and female participants were trained and tested separately. For each sex, data were randomly divided into 4 folds, and models were evaluated in a leave-1-fold-out manner.ResultsECGs were available for 17,807 male and 19,049 female participants (mean ages: 61 ± 7 and 63 ± 8 years; mean BMI 26 ± 5 kg/m2 and 27 ± 4 kg/m2, respectively). NN models detected overweight/obese individuals with average accuracies of 75% and 73% for male and female subjects, respectively. The magnitudes of difference between NN-predicted BMI and actual BMI were significantly correlated with visceral adipose tissue volumes. Concurrent hypertension, diabetes, dyslipidemia, and/or coronary heart disease explained false-positive classifications (ie, calculated BMI <25 kg/m2 misclassified as ≥25 kg/m2 by NN model, P < .001).ConclusionNN models applied to 12-lead ECGs predict BMI with a reasonable degree of accuracy. Discrepancies between NN-predicted and calculated BMI may be indicative of underlying visceral adiposity and concomitant cardiometabolic perturbation, which could be used to identify individuals at risk of cardiometabolic disease.
Ardissino M, Millar O, Reddy R, et al., 2021, Effect of Cardiovascular Risk Factors on Hypertensive Disorders of Pregnancy: A Mendelian Randomization Study, Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0009-7322
Chow J-J, Leong KMW, Yazdani M, et al., 2021, A Multicenter External Validation of a Score Model to Predict Risk of Events in Patients With Brugada Syndrome, AMERICAN JOURNAL OF CARDIOLOGY, Vol: 160, Pages: 53-59, ISSN: 0002-9149
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Hartley A, Shalhoub J, Ng F, et al., 2021, Size matters in atrial fibrillation: the underestimated importance of reduction of contiguous electrical mass underlying the effectiveness of catheter ablation, Europace, Vol: 23, Pages: 1698-1707, ISSN: 1099-5129
Evidence has accumulated over the last century of the importance of a critical electrical mass in sustaining atrial fibrillation (AF). AF ablation certainly reduces electrically contiguous atrial mass, but this is not widely accepted to be an important part of its mechanism of action. In this article, we review data showing that atrial size is correlated in many settings with AF propensity. Larger mammals are more likely to exhibit AF. This is seen both in the natural world and in animal models, where it is much easier to create a goat model than a mouse model of AF, for example. This also extends to humans—athletes, taller people, and obese individuals all have large atria and are more likely to exhibit AF. Within an individual, risk factors such as hypertension, valvular disease and ischaemia can enlarge the atrium and increase the risk of AF. With respect to AF ablation, we explore how variations in ablation strategy and the relative effectiveness of these strategies may suggest that a reduction in electrical atrial mass is an important mechanism of action. We counter this with examples in which there is no doubt that mass reduction is less important than competing theories such as ganglionated plexus ablation. We conclude that, when considering future strategies for the ablative therapy of AF, it is important not to discount the possibility that contiguous electrical mass reduction is the most important mechanism despite the disappointing consequence being that enhancing success rates in AF ablation may involve greater tissue destruction.
Li X, Shi X, Handa BS, et al., 2021, Classification of fibrillation organisation using electrocardiograms to guide mechanism-directed treatments, Frontiers in Physiology, Vol: 12, Pages: 1-14, ISSN: 1664-042X
Background: Atrial fibrillation (AF) and ventricular fibrillation (VF) are complex heart rhythm disorders and may be sustained by distinct electrophysiological mechanisms. Disorganised self-perpetuating multiple-wavelets and organised rotational drivers (RDs) localising to specific areas are both possible mechanisms by which fibrillation is sustained. Determining the underlying mechanisms of fibrillation may be helpful in tailoring treatment strategies. We investigated whether global fibrillation organisation, a surrogate for fibrillation mechanism, can be determined from electrocardiograms (ECGs) using band-power (BP) feature analysis and machine learning.Methods: In this study, we proposed a novel ECG classification framework to differentiate fibrillation organisation levels. BP features were derived from surface ECGs and fed to a linear discriminant analysis classifier to predict fibrillation organisation level. Two datasets, single-channel ECGs of rat VF (n = 9) and 12-lead ECGs of human AF (n = 17), were used for model evaluation in a leave-one-out (LOO) manner.Results: The proposed method correctly predicted the organisation level from rat VF ECG with the sensitivity of 75%, specificity of 80%, and accuracy of 78%, and from clinical AF ECG with the sensitivity of 80%, specificity of 92%, and accuracy of 88%.Conclusion: Our proposed method can distinguish between AF/VF of different global organisation levels non-invasively from the ECG alone. This may aid in patient selection and guiding mechanism-directed tailored treatment strategies.
Arnold AD, Shun-Shin MJ, Ali N, et al., 2021, Left ventricular activation time and pattern are preserved with both selective and non-selective his bundle pacing, Heart Rhythm O2, Vol: 2, Pages: 439-445, ISSN: 2666-5018
BackgroundHis bundle pacing (HBP) can be achieved in two ways: selective HBP (S-HBP), where the His bundle is captured alone, and non-selective HBP (NS-HBP), where local myocardium is also captured resulting a pre-excited ECG appearance.ObjectiveWe assessed the impact of this ventricular pre-excitation on left and right ventricular dys-synchrony.MethodsWe recruited patients who displayed both S-HBP and NS-HBP. We performed non-invasive epicardial electrical mapping for left and right ventricular activation time (LVAT and RVAT) and pattern.Results20 patients were recruited. In the primary analysis, the mean within-patient change in LVAT from S-HBP to NS-HBP was -5.5ms (95% confidence interval: -0.6 to -10.4, non-inferiority p<0.0001). NS-HBP did not prolong RVAT (4.3ms, -4.0 to 12.8, p=0.296) but did prolong QRS duration (QRSd, 22.1ms, 11.8 to 32.4, p = 0.0003). In patients with narrow intrinsic QRS (n=6), NS-HBP preserved LVAT (-2.9ms, -9.7 to 4.0, p=0.331) but prolonged QRS duration (31.4ms, 22.0 to 40.7, p=0.0003) and mean RVAT (16.8ms, -5.3 to 38.9, p=0.108) compared to S-HBP. Activation pattern of the left ventricular surface was unchanged between S-HBP and NS-HBP but NS-HBP produced early basal right ventricular activation that was not seen in S-HBP.ConclusionCompared to S-HBP, local myocardial capture during NS-HBP produces pre-excitation of the basal right ventricle resulting in QRS duration prolongation. However, NS-HBP preserves the left ventricular activation time and pattern of S-HBP. Left ventricular dys-synchrony is not an important factor when choosing between S-HBP and NS-HBP in most patients.
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