Publications by authors named "Swenne C"

Neurocardiology is a broad interdisciplinary specialty investigating how the cardiovascular and nervous systems interact. In this brief introductory review, we describe several key aspects of this interaction with specific attention to cardiovascular effects. The review introduces basic anatomy and discusses physiological mechanisms and effects that play crucial roles in the interaction of the cardiovascular and nervous systems, namely: the cardiac neuraxis, the taxonomy of the nervous system, integration of sensory input in the brainstem, influences of the autonomic nervous system (ANS) on heart and vasculature, the neural pathways and functioning of the arterial baroreflex, receptors and ANS effects in the walls of blood vessels, receptors and ANS effects in excitable cells in the heart, ANS effects on heart rate and sympathovagal balance, endo-epicardial inhomogeneity, ANS effects with a balanced vagal and sympathetic stimulation, sympathovagal interaction, arterial baroreflex, baroreflex sensitivity and heart rate variability, arrhythmias and the arterial baroreflex, the cardiopulmonary baroreflex, the exercise pressor reflex, exercise-recovery hysteresis, mental stress, cardiac-cardiac reflexes, the cardiac sympathetic afferent reflex (CSAR), and neuromodulation.

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Article Synopsis
  • This review discusses the noninvasive evaluation of cardiac autonomic nervous system activity (ANSA) through easily accessible parameters like heart rate (HR) and heart-rate variability (HRV), highlighting their importance in risk assessment for sudden cardiac death.
  • The translation of these parameters from controlled lab settings to real-world ambulatory environments faces challenges due to various uncontrolled factors such as blood pressure changes and physical activity.
  • To improve the accuracy of ANSA evaluations in everyday settings, the authors suggest using a multi-sensor and multiparametric approach, along with data fusion and machine-learning techniques.
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Background: Heart rate variability (HRV), an important marker of autonomic nervous system activity, is usually determined from electrocardiogram (ECG) recordings corrected for extrasystoles and artifacts. Especially in large population-based studies, computer-based algorithms are used to determine RR intervals. The Modular ECG Analysis System MEANS is a widely used tool, especially in large studies.

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Non-traumatic chest pain is a frequent reason for an urgent ambulance visit of a patient by the emergency medical services (EMS). Chest pain (or chest pain-equivalent symptoms) can be innocent, but it can also signal an acute form of severe pathology that may require prompt intervention. One of these pathologies is cardiac ischemia, resulting from a disbalance between blood supply and demand.

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The ECG is crucial in the prehospital (and early inhospital) phase of patients with symptoms suggestive of myocardial ischemia. Therefore, new algorithms for ECG-based myocardial ischemia detection are continuously being researched. Development and validation of these algorithms require a database of acute ECGs (from the prehospital or emergency department setting) including a representative mix of cases (ischemia present) and controls (no ischemia present).

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. Acute myocardial ischemia in the setting of acute coronary syndrome (ACS) may lead to myocardial infarction. Therefore, timely decisions, already in the pre-hospital phase, are crucial to preserving cardiac function as much as possible.

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Wilson assumed that the ventricular gradient (VG) is independent of the ventricular activation order. This paradigm has often been refuted and was never convincingly corroborated. We sought to validate Wilson's concept by intra-individual comparison of the VG of sinus beats and ectopic beats, thus assessing the effects of both altered ventricular conduction (caused by the ectopic focus) and restitution (caused by ectopic prematurity).

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Background: Evaluation of a complex intervention are often described as being diminished by difficulties regarding acceptability, compliance, delivery of the intervention, recruitment and retention. Research of peer learning for nursing students have found several positive benefits while studies of peer learning for newly graduated nurses are lacking. This study aimed (1) to investigate the study process in terms of (a) first-line managers' perspectives on the intervention study, the difficulties they face and how they handle these and (b) new graduates' fidelity to the intervention and (2) to examine the effect of the peer learning intervention in workplace introduction for newly graduated nurses.

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Myocardial ischemia, consisting in a reduction of blood flow to the heart, may cause sudden cardiac death by myocardial infarction or trigger serious abnormal rhythms. Thus, its timely identification is crucial. The Repeated Structuring and Learning Procedure (RS&LP), an innovative constructive algorithm able to dynamically create neural networks (NN) alternating structuring and learning phases, was previously found potentially useful for myocardial ischemia detection.

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The purpose of this observational study was to describe the collaboration between first-year nursing students using peer learning during their first clinical practice education. In earlier, predominantly interview studies, peer learning has been described as a model with several positive outcomes. However, no studies on how students act in collaboration in a real-life context have been found.

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Background: Healthcare-associated infections (HCAIs) have a large negative impact on morbidity, mortality, and quality of life. Approximately 9% of all patients hospitalized in Sweden suffer from HCAI. Hand hygiene plays a key role and is considered the single most important measure to reduce HCAI.

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Introduction: The YEARS algorithm was successfully developed to reduce the number of computed tomography pulmonary angiography (CTPA) investigations in the diagnostic management of patients with suspected pulmonary embolism (PE), although half of patients still needed to be referred for CTPA. We hypothesized that ECG derived ventricular gradient optimized for right ventricular pressure overload (VG-RVPO), an easy to use tool for detecting PE-induced pulmonary hypertension (PH), may further improve the efficiency of the YEARS algorithm.

Methods: In this post-hoc analysis of the Years study, ECGs of 479 patients with suspected PE managed according to the YEARS algorithm were available for analysis.

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Atrial fibrillation (AF) is a common cardiac disorder that can cause severe complications. AF diagnosis is typically based on the electrocardiogram (ECG) evaluation in hospitals or in clinical facilities. The aim of the present work is to propose a new artificial neural network for reliable AF identification in ECGs acquired through portable devices.

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Background Early prehospital recognition of critical conditions such as ST-segment-elevation myocardial infarction (STEMI) has prognostic relevance. Current international electrocardiographic STEMI thresholds are predominantly based on individuals of Western European descent. However, because of ethnic electrocardiographic variability both in health and disease, there is a need to reevaluate diagnostic ST-segment elevation thresholds for different populations.

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Aim: To discuss specialist operating theatre nurses' competence in relation to the general six core competencies and patient safety.

Design: A discursive analysis of legal statutes and scientific articles.

Methods: Swedish legal statutes and an overview of scientific articles on operating theatre nursing were deductively analysed and classified into healthcare providers' general six core competencies.

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Background: In the prehospital triage of patients presenting with symptoms suggestive of acute myocardial ischemia, reliable myocardial ischemia detection in the electrocardiogram (ECG) is pivotal. Due to large interindividual variability and overlap between ischemic and nonischemic ECG-patterns, incorporation of a previous elective (reference) ECG may improve accuracy. The aim of the current study was to explore the potential value of serial ECG analysis using subtraction electrocardiography.

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QT variability is a promising electrocardiographic marker. It has been studied as a screening tool for coronary artery disease and left ventricular hypertrophy, and increased QT variability is a known risk factor for sudden cardiac death. Considering that comprehensive normal values for QT variability were lacking, we set out to establish these in standard 10-s electrocardiograms (ECGs) covering both sexes and all ages.

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Background: Several studies have reported changes in electrocardiographic variables after atrial septal defect (ASD) closure. However no temporal electro-and vectorcardiographic changes have been described from acute to long-term follow-up at different ages. We aimed to study electrical remodeling after percutaneous ASD closure in pediatric and adult patients.

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Background: Serial electrocardiography aims to contribute to electrocardiogram (ECG) diagnosis by comparing the ECG under consideration with a previously made ECG in the same individual. Here, we present a novel algorithm to construct dedicated deep-learning neural networks (NNs) that are specialized in detecting newly emerging or aggravating existing cardiac pathology in serial ECGs.

Methods: We developed a novel deep-learning method for serial ECG analysis and tested its performance in detection of heart failure in post-infarction patients, and in the detection of ischemia in patients who underwent elective percutaneous coronary intervention.

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Background: Patients with systemic sclerosis (SSc) are at risk for developing pulmonary hypertension (PH) which is a major cause of death in this population. Echocardiographic (TTE) derived pulmonary arterial pressure (PAP) can be unreliable for the early detection of PH. Previous studies demonstrate that the ECG derived ventricular gradient optimized for right ventricular pressure overload (VG-RVPO) can detect PH in a heterogeneous population suspected of PH.

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Heart-rate variability (HRV) measured on standard 10-s electrocardiograms (ECGs) has been associated with increased risk of cardiac and all-cause mortality, but age- and sex-dependent normal values have not been established. Since heart rate strongly affects HRV, its effect should be taken into account. We determined a comprehensive set of normal values of heart-rate corrected HRV derived from 10-s ECGs for both children and adults, covering both sexes.

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Electrocardiographic Decision Support - Myocardial Ischaemia (EDS-MI) is a graphical decision support for detection and localization of acute transmural ischaemia. A recent study indicated that EDS-MI performs well for detection of acute transmural ischaemia. However, its performance has not been tested in patients with non-ischaemic ST-deviation.

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Background: Normal values of the mathematically-synthesized vectorcardiogram (VCG) are lacking for children. Therefore, the objective of this study was to assess normal values of the pediatric synthesized VCG (spatial QRS-T angle [SA] and ventricular gradient [VG]).

Methods: Electrocardiograms (ECGs) of 1263 subjects (0-24 years) with a normal heart were retrospectively selected.

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