| 1. |
- van de Vegte, Yordi, et al.
(författare)
-
Genetic insights into resting heart rate and its role in cardiovascular disease
- 2023
-
Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
-
Tidskriftsartikel (refereegranskat)abstract
- The genetics and clinical consequences of resting heart rate (RHR) remain incompletely understood. Here, the authors discover new genetic variants associated with RHR and find that higher genetically predicted RHR decreases risk of atrial fibrillation and ischemic stroke. Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.
|
|
| 2. |
- Ntalla, Ioanna, et al.
(författare)
-
Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction
- 2020
-
Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
-
Tidskriftsartikel (refereegranskat)abstract
- The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N=293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease. On the electrocardiogram, the PR interval reflects conduction from the atria to ventricles and also serves as risk indicator of cardiovascular morbidity and mortality. Here, the authors perform genome-wide meta-analyses for PR interval in multiple ancestries and identify 141 previously unreported genetic loci.
|
|
| 3. |
- Young, William J., et al.
(författare)
-
Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways
- 2022
-
Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 13
-
Tidskriftsartikel (refereegranskat)abstract
- The QT interval is a heritable electrocardiographic measure associated with arrhythmia risk when prolonged. Here, the authors used a series of genetic analyses to identify genetic loci, pathways, therapeutic targets, and relationships with cardiovascular disease. The QT interval is an electrocardiographic measure representing the sum of ventricular depolarization and repolarization, estimated by QRS duration and JT interval, respectively. QT interval abnormalities are associated with potentially fatal ventricular arrhythmia. Using genome-wide multi-ancestry analyses (>250,000 individuals) we identify 177, 156 and 121 independent loci for QT, JT and QRS, respectively, including a male-specific X-chromosome locus. Using gene-based rare-variant methods, we identify associations with Mendelian disease genes. Enrichments are observed in established pathways for QT and JT, and previously unreported genes indicated in insulin-receptor signalling and cardiac energy metabolism. In contrast for QRS, connective tissue components and processes for cell growth and extracellular matrix interactions are significantly enriched. We demonstrate polygenic risk score associations with atrial fibrillation, conduction disease and sudden cardiac death. Prioritization of druggable genes highlight potential therapeutic targets for arrhythmia. Together, these results substantially advance our understanding of the genetic architecture of ventricular depolarization and repolarization.
|
|
| 4. |
- Brandes, Axel, et al.
(författare)
-
Consumer-Led Screening for Atrial Fibrillation : Frontier Review of the AF-SCREEN International Collaboration
- 2022
-
Ingår i: Circulation. - 0009-7322 .- 1524-4539. ; 146:19, s. 1461-1474
-
Forskningsöversikt (refereegranskat)abstract
- The technological evolution and widespread availability of wearables and handheld ECG devices capable of screening for atrial fibrillation (AF), and their promotion directly to consumers, has focused attention of health care professionals and patient organizations on consumer-led AF screening. In this Frontiers review, members of the AF-SCREEN International Collaboration provide a critical appraisal of this rapidly evolving field to increase awareness of the complexities and uncertainties surrounding consumer-led AF screening. Although there are numerous commercially available devices directly marketed to consumers for AF monitoring and identification of unrecognized AF, health care professional-led randomized controlled studies using multiple ECG recordings or continuous ECG monitoring to detect AF have failed to demonstrate a significant reduction in stroke. Although it remains uncertain if consumer-led AF screening reduces stroke, it could increase early diagnosis of AF and facilitate an integrated approach, including appropriate anticoagulation, rate or rhythm management, and risk factor modification to reduce complications. Companies marketing AF screening devices should report the accuracy and performance of their products in high- and low-risk populations and avoid claims about clinical outcomes unless improvement is demonstrated in randomized clinical trials. Generally, the diagnostic yield of AF screening increases with the number, duration, and temporal dispersion of screening sessions, but the prognostic importance may be less than for AF detected by single-time point screening, which is largely permanent, persistent, or high-burden paroxysmal AF. Consumer-initiated ECG recordings suggesting possible AF always require confirmation by a health care professional experienced in ECG reading, whereas suspicion of AF on the basis of photoplethysmography must be confirmed with an ECG. Consumer-led AF screening is unlikely to be cost-effective for stroke prevention in the predominantly young, early adopters of this technology. Studies in older people at higher stroke risk are required to demonstrate both effectiveness and cost-effectiveness. The direct interaction between companies and consumers creates new regulatory gaps in relation to data privacy and the registration of consumer apps and devices. Although several barriers for optimal use of consumer-led screening exist, results of large, ongoing trials, powered to detect clinical outcomes, are required before health care professionals should support widespread adoption of consumer-led AF screening.
|
|
| 5. |
- De Groot, Natasja M.S., et al.
(författare)
-
Critical appraisal of technologies to assess electrical activity during atrial fibrillation : a position paper from the European Heart Rhythm Association and European Society of Cardiology Working Group on eCardiology in collaboration with the Heart Rhythm Society, Asia Pacific Heart Rhythm Society, Latin American Heart Rhythm Society and Computing in Cardiology
- 2022
-
Ingår i: Europace. - : Oxford University Press (OUP). - 1099-5129. ; 24:2, s. 313-330
-
Forskningsöversikt (refereegranskat)abstract
- We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (i) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e.g. catheter-electrode combinations) for signal processing (e.g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future.
|
|
| 6. |
- Glynn, Liam, et al.
(författare)
-
The Limerick Declaration on Rural Health Care 2022
- 2023
-
Ingår i: Rural and Remote Health. - 1445-6354. ; 23:1, s. 7905-7905
-
Tidskriftsartikel (refereegranskat)abstract
- The 19th World Rural Health Conference, hosted in rural Ireland and the University of Limerick, with over 650 participants coming from 40 countries and an additional 1600 engaging online, has carefully considered how best rural communities can be empowered to improve their own health and the health of those around them. The conference also considered the role of national health systems and all stakeholders, in keeping with the commitments made through the Sustainable Development Goals and the enjoyment of the highest attainable standard of health as one of the fundamental rights of every human being. This conference declaration, the Limerick Declaration on Rural Healthcare, is designed to inform rural communities, academics and policymakers about how to achieve the goal of delivering high quality health care in rural and remote areas most effectively, with a particular focus on the Irish healthcare system. Congruent with current evidence and best international practice, the participants of the conference endorsed a series of recommendations for the creation of high quality, sustainable and cost-effective healthcare delivery for rural communities in Ireland and globally. The recommendations focused on four major themes: rural healthcare needs and delivery, rural workforce, advocacy and policy, and research for rural health care. Equal access to health care is a crucial marker of democracy. Hence, we call on all governments, policymakers, academic institutions and communities globally to commit to providing their rural dwellers with equitable access to health care that is properly resourced and fundamentally patient-centred in its design.
|
|
| 7. |
- Hayes, Conor F., et al.
(författare)
-
A Brief Guide to Multi-Objective Reinforcement Learning and Planning
- 2023
-
Ingår i: Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS). - 9781450394321 ; , s. 1988-1990
-
Konferensbidrag (refereegranskat)abstract
- Real-world sequential decision-making tasks are usually complex, and require trade-offs between multiple–often conflicting–objectives. However, the majority of research in reinforcement learning (RL) and decision-theoretic planning assumes a single objective, or that multiple objectives can be handled via a predefined weighted sum over the objectives. Such approaches may oversimplify the underlying problem, and produce suboptimal results. This extended abstract outlines the limitations of using a semi-blind iterative process to solve multi-objective decision making problems. Our extended paper [4], serves as a guide for the application of explicitly multi-objective methods to difficult problems.
|
|
| 8. |
- Hayes, Conor F., et al.
(författare)
-
A practical guide to multi-objective reinforcement learning and planning
- 2022
-
Ingår i: Autonomous Agents and Multi-Agent Systems. - New York, NY, United States : Springer. - 1387-2532 .- 1573-7454. ; 36:1
-
Tidskriftsartikel (refereegranskat)abstract
- Real-world sequential decision-making tasks are generally complex, requiring trade-offs between multiple, often conflicting, objectives. Despite this, the majority of research in reinforcement learning and decision-theoretic planning either assumes only a single objective, or that multiple objectives can be adequately handled via a simple linear combination. Such approaches may oversimplify the underlying problem and hence produce suboptimal results. This paper serves as a guide to the application of multi-objective methods to difficult problems, and is aimed at researchers who are already familiar with single-objective reinforcement learning and planning methods who wish to adopt a multi-objective perspective on their research, as well as practitioners who encounter multi-objective decision problems in practice. It identifies the factors that may influence the nature of the desired solution, and illustrates by example how these influence the design of multi-objective decision-making systems for complex problems.
|
|
| 9. |
- Paixão, Gabriela M. M., et al.
(författare)
-
Electrocardiographic Predictors of Mortality: Data from a Primary Care Tele-Electrocardiography Cohort of Brazilian Patients
- 2021
-
Ingår i: Hearts. - : MDPI AG. - 2673-3846. ; 2:4, s. 449-458
-
Tidskriftsartikel (refereegranskat)abstract
- Computerized electrocardiography (ECG) has been widely used and allows linkage to electronic medical records. The present study describes the development and clinical applications of an electronic cohort derived from a digital ECG database obtained by the Telehealth Network of Minas Gerais, Brazil, for the period 2010–2017, linked to the mortality data from the national information system, the Clinical Outcomes in Digital Electrocardiography (CODE) dataset. From 2,470,424 ECGs, 1,773,689 patients were identified. A total of 1,666,778 (94%) underwent a valid ECG recording for the period 2010 to 2017, with 1,558,421 patients over 16 years old; 40.2% were men, with a mean age of 51.7 [SD 17.6] years. During a mean follow-up of 3.7 years, the mortality rate was 3.3%. ECG abnormalities assessed were: atrial fibrillation (AF), right bundle branch block (RBBB), left bundle branch block (LBBB), atrioventricular block (AVB), and ventricular pre-excitation. Most ECG abnormalities (AF: Hazard ratio [HR] 2.10; 95% CI 2.03–2.17; RBBB: HR 1.32; 95%CI 1.27–1.36; LBBB: HR 1.69; 95% CI 1.62–1.76; first degree AVB: Relative survival [RS]: 0.76; 95% CI0.71–0.81; 2:1 AVB: RS 0.21 95% CI0.09–0.52; and RS 0.36; third degree AVB: 95% CI 0.26–0.49) were predictors of overall mortality, except for ventricular pre-excitation (HR 1.41; 95% CI 0.56–3.57) and Mobitz I AVB (RS 0.65; 95% CI 0.34–1.24). In conclusion, a large ECG database established by a telehealth network can be a useful tool for facilitating new advances in the fields of digital electrocardiography, clinical cardiology and cardiovascular epidemiology.
|
|
| 10. |
- Ribeiro, Antônio H., et al.
(författare)
-
Automatic diagnosis of the 12-lead ECG using a deep neural network
- 2020
-
Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
-
Tidskriftsartikel (refereegranskat)abstract
- The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%. These results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice. The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. In that context, the authors present a Deep Neural Network (DNN) that recognizes different abnormalities in ECG recordings which matches or outperform cardiology and emergency resident medical doctors.
|
|
