174 results found
Koch C, Reilly-ODonnell B, Gutierrez R, et al., 2023, Nanopore sequencing of DNA-barcoded probes for highly multiplexed detection of microRNA, proteins and small biomarkers, Nature Nanotechnology, ISSN: 1748-3387
There is an unmet need to develop low-cost, rapid and highly multiplexed diagnostic technology platforms for quantitatively detecting blood biomarkers to advance clinical diagnostics beyond the single biomarker model. Here we perform nanopore sequencing of DNA-barcoded molecular probes engineered to recognize a panel of analytes. This allows for highly multiplexed and simultaneous quantitative detection of at least 40 targets, such as microRNAs, proteins and neurotransmitters, on the basis of the translocation dynamics of each probe as it passes through a nanopore. Our workflow is built around a commercially available MinION sequencing device, offering a one-hour turnaround time from sample preparation to results. We also demonstrate that the strategy can directly detect cardiovascular disease-associated microRNA from human serum without extraction or amplification. Due to the modularity of barcoded probes, the number and type of targets detected can be significantly expanded.
Chen JY, Ardissino M, Reddy RK, et al., 2023, Genetically predicted androgenic profiles and adverse cardiac markers: a sex-specific Mendelian randomization study., ESC Heart Fail
AIMS: Observational evidence suggests associations between sex hormone levels and heart failure (HF). We used sex-specific genetic variants associated with androgenic sex hormone profiles to investigate the causal relevance of androgenic sex hormone profiles on cardiac structure and function and HF using Mendelian randomization (MR). METHODS AND RESULTS: Sex-specific uncorrelated genome-wide significant (P < 5 × 10-8 ) variants predicting sex hormone-binding globulin (SHBG), total testosterone, and bioavailable testosterone were extracted from summary statistics of genome-wide association study (GWAS) on 425 097 participants in the UK Biobank. Sex-specific gene-outcome association estimates were computed for left ventricular ejection fraction (LVEF), left ventricular end-diastolic and end-systolic volumes (LVEDV and LVESV, respectively), left ventricular stroke volume (LVSV), cardiac index, and cardiac output in 11 528 female and 14 356 male UK Biobank Imaging Study participants and for incident or prevalent HF in an external cohort of 47 309 cases and 930 014 controls. Inverse-variance weighted MR was the primary analysis method. In females, higher genetically predicted bioavailable testosterone was associated with lower LVEDV [β per nmol/L = -0.11 (-0.19 to -0.03), P = 0.006], lower LVESV [β = -0.09 (-0.17 to -0.01), P = 0.022], lower LVSV [β = -0.11 (-0.18 to -0.03), P = 0.005], lower cardiac output [β = -0.08 (-0.16 to 0.00), P = 0.046], and lower cardiac index [β = -0.08 (-0.16 to -0.01), P = 0.034] and a higher risk of HF [odds ratio 1.10 (1.01-1.19), P = 0.026] on external validation analysis in larger scale, sex-adjusted GWAS data. Higher genetically predicted SHBG was associated with higher LVEDV [β per nmol/L = 0.17 (0.08-0.25), P = 2 ×
Ardissino M, Morley A, Slob E, et al., 2023, Birth weight influences cardiac structure, function and disease risk: evidence of a causal association, European Heart Journal, Pages: 1-12, ISSN: 0195-668X
Background and AimsLow birth weight is a common pregnancy complication, which has been associated with higher risk of cardiometabolic disease in later life. Prior Mendelian randomization (MR) studies exploring this question do not distinguish the mechanistic contributions of variants that directly influence birth weight through the foetal genome (direct foetal effects), vs. variants influencing birth weight indirectly by causing an adverse intrauterine environment (indirect maternal effects). In this study, MR was used to assess whether birth weight, independent of intrauterine influences, is associated with cardiovascular disease risk and measures of adverse cardiac structure and function.MethodsUncorrelated (r2 < .001), genome-wide significant (P < 5 × 10−8) single nucleotide polymorphisms were extracted from genome-wide association studies summary statistics for birth weight overall, and after isolating direct foetal effects only. Inverse-variance weighted MR was utilized for analyses on outcomes of atrial fibrillation, coronary artery disease, heart failure, ischaemic stroke, and 16 measures of cardiac structure and function. Multiple comparisons were accounted for by Benjamini–Hochberg correction.ResultsLower genetically-predicted birth weight, isolating direct foetal effects only, was associated with an increased risk of coronary artery disease (odds ratio 1.21, 95% confidence interval 1.06–1.37; P = .031), smaller chamber volumes, and lower stroke volume, but higher contractility.ConclusionsThe results of this study support a causal role of low birth weight in cardiovascular disease, even after accounting for the influence of the intrauterine environment. This suggests that individuals with a low birth weight may benefit from early targeted cardiovascular disease prevention strategies, independent of whether this was linked to an adverse intrauterine environment during gestation.
Stabenau HF, Sau A, Kramer DB, et al., 2023, Limits of the spatial ventricular gradient and QRST angles in patients with normal electrocardiograms and no known cardiovascular disease stratified by age, sex, and race., J Cardiovasc Electrophysiol
INTRODUCTION: Measurement of the spatial ventricular gradient (SVG), spatial QRST angles, and other vectorcardiographic measures of myocardial electrical heterogeneity have emerged as novel risk stratification methods for sudden cardiac death and other adverse cardiovascular events. Prior studies of normal limits of these measurements included primarily young, healthy, White volunteers, but normal limits in older patients are unknown. The influence of race and body mass index (BMI) on these measurements is also unclear. METHODS: Normal 12-lead electrocardiograms (ECGs) from a single center were identified. Patients with abnormal cardiovascular, pulmonary, or renal history (assessed by International Classification of Disease [ICD-9/ICD-10] codes) or abnormal cardiovascular imaging were excluded. The SVG and QRST angles were measured and stratified by age, sex, and race. Multivariable linear regression was used to assess the influence of age, BMI, and heart rate (HR) on these measurements. RESULTS: Among 3292 patients, observed ranges of SVG and QRST angles (peak and mean) differed significantly based on sex, age, and race. Sex differences attenuated with increasing age. Men tended to have larger SVG magnitude (60.4 [46.1-77.8] vs. 52.5 [41.3-65.8] mv*ms, p < .0001) and elevation, and more anterior/negative SVG azimuth (-14.8 [-25.1 to -4.3] vs. 1.3 [-9.8 to 10.5] deg, p < .0001) compared to women. Men also had wider QRST angles. Observed ranges varied significantly with BMI and HR. SVG and QRST angle measurements were robust to different filtering bandwidths and moderate fiducial point annotation errors, but were heavily affected by changes in baseline correction. CONCLUSIONS: Age, sex, race, BMI, and HR significantly affect the range of SVG and QRST angles in patients with normal ECGs and no known cardiovascular disease, and should be accounted for in future studies. An online calculator for prediction of these &quo
Maddalena A, Reddy R, Slob E, et al., 2023, Maternal hypertensive traits and adverse outcome in pregnancy: a Mendelian randomization study, Journal of Hypertension, Vol: 41, Pages: 1438-1445, ISSN: 0263-6352
IntroductionHypertensive disorders of pregnancy are associated with adverse feto-maternal outcomes. Existing evidence is mostly limited to observational studies, which are liable to confounding and bias. This study investigated the causal relevance of component hypertensive indices on multiple adverse pregnancy outcomes using Mendelian randomization (MR).MethodsUncorrelated (r2<0.001) genome-wide significant (p<5x10-8) single-nucleotide polymorphisms associated with SBP, diastolic blood pressure (DBP) and pulse pressure (PP) were selected as instrumental variables. Genetic association estimates for outcomes of pre-eclampsia or eclampsia, preterm birth, placental abruption and hemorrhage in early pregnancy were extracted from summary statistics of genome-wide association studies in the FinnGen cohort. Two-sample, inverse-variance weighted MR formed the primary analysis method. Odds ratios (OR) are presented per-10 mmHg higher genetically-predicted hypertensive index. ResultsHigher genetically-predicted SBP associated with higher odds of pre-eclampsia or eclampsia (OR 1.81, 95% confidence interval (CI) 1.68–1.96, p=5.45x10-49), preterm birth (OR 1.09 95%CI 1.03–1.16, p=0.005) and placental abruption (OR 1.33, 95%CI 1.05–1.68, p=0.016). Higher genetically-predicted DBP was associated with pre-eclampsia or eclampsia (OR 2.54, 95%CI 2.21–2.92, p=5.35x10-40). Higher genetically-predicted PP was associated with pre-eclampsia or eclampsia (OR 1.68, 95%CI 1.47–1.92, p=1.9×10-14) and preterm birth (OR 1.18, 95%CI 1.06–1.30, p= 0.002).ConclusionThis study provides genetic evidence to support causal associations of SBP, DBP and PP on multiple adverse outcomes of pregnancy. SBP and PP were associated with the broadest range of adverse outcomes, suggesting that optimized management of blood pressure, particularly SBP, is a key priority to improve feto-maternal health.
Sau A, Kapadia S, Al-Aidarous S, et al., 2023, Temporal trends and lesion sets for persistent atrial fibrillation ablation: a meta-analysis with trial sequential analysis and meta-regression, Circulation: Arrhythmia and Electrophysiology, Vol: 16, Pages: 536-545, ISSN: 1941-3084
BACKGROUND: Ablation for persistent atrial fibrillation (PsAF) has been performed for over 20 years, although success rates have remained modest. Several adjunctive lesion sets have been studied but none have become standard of practice. We sought to describe how the efficacy of ablation for PsAF has evolved in this time period with a focus on the effect of adjunctive ablation strategies. METHODS: Databases were searched for prospective studies of PsAF ablation. We performed meta-regression and trial sequential analysis. RESULTS: A total of 99 studies (15 424 patients) were included. Ablation for PsAF achieved the primary outcome (freedom of atrial fibrillation/atrial tachycardia rate at 12 months follow-up) in 48.2% (5% CI, 44.0-52.3). Meta-regression showed freedom from atrial arrhythmia at 12 months has improved over time, while procedure time and fluoroscopy time have significantly reduced. Through the use of cumulative meta-analyses and trial sequential analysis, we show that some ablation strategies may initially seem promising, but after several randomized controlled trials may be found to be ineffective. Trial sequential analysis showed that complex fractionated atrial electrogram ablation is ineffective and further study of this treatment would be futile, while posterior wall isolation currently does not have sufficient evidence for routine use in PsAF ablation. CONCLUSIONS: Overall success rates from PsAF ablation and procedure/fluoroscopy times have improved over time. However, no adjunctive lesion set, in addition to pulmonary vein isolation, has been conclusively demonstrated to be beneficial. Through the use of trial sequential analysis, we highlight the importance of adequately powered randomized controlled trials, to avoid reaching premature conclusions, before widespread adoption of novel therapies.
Ali N, Arnold AD, Miyazawa AA, et al., 2023, Septal scar as a barrier to left bundle branch area pacing., Pacing Clin Electrophysiol, Vol: 46, Pages: 1077-1084
BACKGROUND: The use of left bundle branch area pacing (LBBAP) for bradycardia pacing and cardiac resynchronization is increasing, but implants are not always successful. We prospectively studied consecutive patients to determine whether septal scar contributes to implant failure. METHODS: Patients scheduled for bradycardia pacing or cardiac resynchronization therapy were prospectively enrolled. Recruited patients underwent preprocedural scar assessment by cardiac MRI with late gadolinium enhancement imaging. LBBAP was attempted using a lumenless lead (Medtronic 3830) via a transeptal approach. RESULTS: Thirty-five patients were recruited: 29 male, mean age 68 years, 10 ischemic, and 16 non-ischemic cardiomyopathy. Pacing indication was bradycardia in 26% and cardiac resynchronization in 74%. The lead was successfully deployed to the left ventricular septum in 30/35 (86%) and unsuccessful in the remaining 5/35 (14%). Septal late gadolinium enhancement was significantly less extensive in patients where left septal lead deployment was successful, compared those where it was unsuccessful (median 8%, IQR 2%-18% vs. median 54%, IQR 53%-57%, p < .001). CONCLUSIONS: The presence of septal scar appears to make it more challenging to deploy a lead to the left ventricular septum via the transeptal route. Additional implant tools or alternative approaches may be required in patients with extensive septal scar.
Ardissino M, Patel KHK, Rayes B, et al., 2023, Multiple anthropometric measures and proarrhythmic 12-lead ECG indices: A mendelian randomization study., PLoS Med, Vol: 20
BACKGROUND: Observational studies suggest that electrocardiogram (ECG) indices might be influenced by obesity and other anthropometric measures, though it is difficult to infer causal relationships based on observational data due to risk of residual confounding. We utilized mendelian randomization (MR) to explore causal relevance of multiple anthropometric measures on P-wave duration (PWD), PR interval, QRS duration, and corrected QT interval (QTc). METHODS AND FINDINGS: Uncorrelated (r2 < 0.001) genome-wide significant (p < 5 × 10-8) single nucleotide polymorphisms (SNPs) were extracted from genome-wide association studies (GWAS) on body mass index (BMI, n = 806,834), waist:hip ratio adjusted for BMI (aWHR, n = 697,734), height (n = 709,594), weight (n = 360,116), fat mass (n = 354,224), and fat-free mass (n = 354,808). Genetic association estimates for the outcomes were extracted from GWAS on PR interval and QRS duration (n = 180,574), PWD (n = 44,456), and QTc (n = 84,630). Data source GWAS studies were performed between 2018 and 2022 in predominantly European ancestry individuals. Inverse-variance weighted MR was used for primary analysis; weighted median MR and MR-Egger were used as sensitivity analyses. Higher genetically predicted BMI was associated with longer PWD (β 5.58; 95%CI [3.66,7.50]; p = < 0.001), as was higher fat mass (β 6.62; 95%CI [4.63,8.62]; p < 0.001), fat-free mass (β 9.16; 95%CI [6.85,11.47]; p < 0.001) height (β 4.23; 95%CI [3.16, 5.31]; p < 0.001), and weight (β 8.08; 95%CI [6.19,9.96]; p < 0.001). Finally, genetically predicted BMI was associated with longer QTc (β 3.53; 95%CI [2.63,4.43]; p < 0.001), driven by both fat mass (β 3.65; 95%CI [2.73,4.57]; p < 0.001) and fat-free mass (β 2.08; 95%CI [0.85,3.31]; p = 0.001). Additionally, genetically predicted height (β 0.98; 95%CI [0.46,1.50]; p < 0.001), weight (β 3.45; 95%CI [2.54,4.36]; p < 0.001), and
Sau A, Pastika L, Ng FS, 2023, Atrial fibrillation phenotypes: the route to personalised care?, Heart
Reddy R, Ardissino M, Ng FS, 2023, Type 2 diabetes mellitus and atrial fibrillation: evaluating causal and pleiotropic pathways using Mendelian randomization., Journal of the American Heart Association, ISSN: 2047-9980
Sau A, Ng FS, 2023, Response to letter by Saumarez et al. entitled 'Regarding the editorial by Sau and Ng. "Hypertrophic cardiomyopathy risk stratification based on clinical or dynamic electrophysiological features: two sides of the same coin"'., Europace, Vol: 25
Sau A, Ng FS, 2023, The emerging role of artificial intelligence-enabled electrocardiograms in healthcare, BMJ Medicine, ISSN: 2754-0413
Sau A, Ng FS, 2023, Hypertrophic cardiomyopathy risk stratification based on clinical or dynamic electrophysiological features: two sides of the same coin., Europace, Vol: 25
Chow J-J, Leong KMW, Shun-Shin MJ, et al., 2023, Ventricular conduction stability noninvasively identifies an arrhythmic substrate in survivors of idiopathic ventricular fibrillation, Journal of the American Heart Association, Vol: 12, Pages: 1-24, ISSN: 2047-9980
Background Idiopathic ventricular fibrillation (VF) is a diagnosis of exclusion following normal cardiac investigations. We sought to determine if exercise-induced changes in electrical substrate could distinguish patient groups with various ventricular arrhythmic pathophysiological conditions and identify patients susceptible to VF. Methods and Results Computed tomography and exercise testing in patients wearing a 252-electrode vest were combined to determine ventricular conduction stability between rest and peak exercise, as previously described. Using ventricular conduction stability, conduction heterogeneity in idiopathic VF survivors (n=14) was compared with those surviving VF during acute ischemia with preserved ventricular function following full revascularization (n=10), patients with benign ventricular ectopy (n=11), and patients with normal hearts, no arrhythmic history, and negative Ajmaline challenge during Brugada family screening (Brugada syndrome relatives; n=11). Activation patterns in normal subjects (Brugada syndrome relatives) are preserved following exercise, with mean ventricular conduction stability of 99.2±0.9%. Increased heterogeneity of activation occurred in the idiopathic VF survivors (ventricular conduction stability: 96.9±2.3%) compared with the other groups combined (versus 98.8±1.6%; P=0.001). All groups demonstrated periodic variation in activation heterogeneity (frequency, 0.3-1 Hz), but magnitude was greater in idiopathic VF survivors than Brugada syndrome relatives or patients with ventricular ectopy (7.6±4.1%, 2.9±2.9%, and 2.8±1.2%, respectively). The cause of this periodicity is unknown and was not replicable by introducing exercise-induced noise at comparable frequencies. Conclusions In normal subjects, ventricular activation patterns change little with exercise. In contrast, patients with susceptibility to VF experience activation heterogeneity following exercise that requires f
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, Vol: 12
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, 2023, Artificial intelligence-enabled electrocardiogram to distinguish atrioventricular re-entrant tachycardia from atrioventricular nodal re-entrant tachycardia, Cardiovascular Digital Health Journal, Vol: 4, Pages: 60-67, 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.
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.
Coyle C, Koutsoftidis S, Kim M-Y, et al., 2023, Feasibility of mapping and ablating ectopy-triggering ganglionated plexus reproducibly in persistent atrial fibrillation, Journal of Interventional Cardiac Electrophysiology: an international journal of arrhythmias and pacing, ISSN: 1383-875X
BackgroundAblation 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.MethodsNine 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.ResultsThe 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.ConclusionsET-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 further studies would be warranted
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, Vol: 25, Pages: 1060-1067, 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.
Ardissino M, Slob EAW, Carter P, et al., 2023, Sex-specific reproductive factors augment cardiovascular disease risk in females: a Mendelian randomization study, Journal of the American Heart Association, Vol: 12, Pages: 1-73, 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
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
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, 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.
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