Accurate determination of intra-atrial conduction velocity (CV) is essential to identify arrhythmogenic areas. The most optimal, commonly used, estimation methodology to measure conduction heterogeneity, including finite differences (FiD), polynomial surface fitting (PSF), and a novel technique using discrete velocity vectors (DVV), has not been determined. We aim (i) to identify the most suitable methodology to unravel local areas of conduction heterogeneities using high-density CV estimation techniques, (ii) to quantify intra-atrial differences in CV, and (iii) to localize areas of CV slowing associated with paroxysmal atrial fibrillation (PAF). Intra-operative epicardial mapping (>5000 sites, interelectrode distances 2 mm) of the right and left atrium and Bachmann’s bundle (BB) was performed during sinus rhythm (SR) in 412 patients with or without PAF. The median atrial CV estimated using the DVV, PSF, and FiD techniques was 90.0 (62.4–116.8), 92.0 (70.6–123.2), and 89.4 (62.5–126.5) cm/s, respectively. The largest difference in CV estimates was found between PSF and DVV which was caused by smaller CV magnitudes detected only by the DVV technique. Using DVV, a lower CV at BB was found in PAF patients compared with those without atrial fibrillation (AF) [79.1 (72.2–91.2) vs. 88.3 (79.3–97.2) cm/s; P < 0.001]. Areas of local conduction heterogeneities were most accurately identified using the DVV technique, whereas PSF and FiD techniques smoothen wavefront propagation thereby masking local areas of conduction slowing. Comparing patients with and without AF, slower wavefront propagation during SR was found at BB in PAF patients, indicating structural remodelling.

Background: Low-voltage areas (LVAs) are commonly considered surrogate markers for an arrhythmogenic substrate underlying tachyarrhythmias. It remains challenging to define a proper threshold to classify LVA, and it is unknown whether unipolar, bipolar, and the recently introduced omnipolar voltage mapping techniques are complementary or contradictory in classifying LVAs. Therefore, this study examined similarities and dissimilarities in unipolar, bipolar, and omnipolar voltage mapping and explored the relation between various types of voltages and conduction velocity (CV). Methods: Intraoperative epicardial mapping (interelectrode distance 2 mm, ±1900 sites) was performed during sinus rhythm in 21 patients (48±13 years, 9 male) with atrial volume overload. Cliques of 4 electrodes (2×2 mm) were used to calculate the maximal unipolar, bipolar, and omnipolar voltages and mean CV. Areas with maximal bipolar or omnipolar clique voltage ≤0.5 mV were defined as LVA. Results: The maximal unipolar clique voltage was not only larger than maximal bipolar clique voltage but also larger than maximal omnipolar clique voltage (7.08 [4.22–10.59] mV versus 5.27 [2.39–9.56] mV and 5.77 [2.58–10.52] mV, respectively, P <0.001). In addition, the largest bipolar clique voltage was on average 1.66 (range: 1.0–59.0) times larger to the corresponding perpendicular bipolar voltage pair. LVAs identified by a bipolar or omnipolar threshold corresponded to a broad spectrum of unipolar voltages and, although CV was generally decreased, still high CVs and large unipolar voltages were found in these LVAs. Conclusions: In patients with atrial volume overload, there were considerable discrepancies in the different types of LVAs. Additionally, the identification of LVAs was hampered by considerable directional differences in bipolar voltages. Even using directional independent omnipolar voltage to identify LVAs, high CVs and large unipolar voltages are present within these areas. Therefore, a combination of low unipolar and low omnipolar voltage may be more indicative of true LVAs.

Automated detection of atrial fibrillation (AF) in continuous rhythm registrations is essential in order to prevent complications and optimize treatment of AF. Many algorithms have been developed to detect AF in surface electrocardiograms (ECGs) during the past few years. The aim of this systematic review is to gain more insight into these available classification methods by discussing previously used digital biomarkers and algorithms and make recommendations for future research. On the 14th of September 2020, the PubMed database was searched for articles focusing on algorithms for AF detection in ECGs using the MeSH terms Atrial Fibrillation, Electrocardiography and Algorithms. Articles which solely focused on differentiation of types of rhythm disorders or prediction of AF termination were excluded. The search resulted in 451 articles, of which 130 remained after full-text screening. Not only did the amount of research on methods for AF detection increase over the past years, but a trend towards more complex classification methods is observed. Furthermore, three different types of features can be distinguished: atrial features, ventricular features, and signal features. Although AF is an atrial disease, only 22% of the described methods use atrial features. More and more studies focus on improving accuracy of classification methods for AF in ECGs. As a result, algorithms become increasingly complex and less well interpretable. Only a few studies focus on detecting atrial activity in the ECG. Developing innovative methods focusing on detection of atrial activity might provide accurate classifiers without compromising on transparency.

Introduction: Advancing age is a known risk factor for developing atrial fibrillation (AF), yet it is unknown which electrophysiological changes contribute to this increased susceptibility. The goal of this study is to investigate conduction disturbances and unipolar voltages (UV) related to aging.Methods: We included 216 patients (182 male, age: 36–83 years) without a history of AF undergoing elective coronary artery bypass surgery. Five seconds of sinus rhythm were recorded intraoperatively at the right atrium (RA), Bachmann's bundle (BB), the left atrium and the pulmonary vein area (PVA). Conduction delay (CD), ‐block (CB), ‐velocity (CV), length of longest CB lines and UV were assessed in all regions.Results: With aging, increasing conduction disturbances were found, particularly at RA and BB (RA: longest CB line r_s = .158, p = .021; BB: CB prevalence r_s = .206, p = .003; CV r_s = −.239, p < .0005). Prevalence of low UV areas (UV <5th percentile) increased with aging at the BB and PVA (BB: r_s = .237, p < .0005 and PVA: r_s = .228, p = .001).Conclusions: Aging is accompanied by an increase in conduction disturbances during sinus rhythm and a higher prevalence of low UV areas, particularly at BB and in the RA. These electrophysiological alterations could in part explain the increasing susceptibility to AF development associated with aging.

Unipolar voltage (UV) mapping is increasingly used for guiding ablative therapy of atrial fibrillation (AF) as unipolar electrograms (U-EGMs) are independent of electrode orientation and atrial wavefront direction. This study was aimed at constructing individual, high-resolution sinus rhythm (SR) UV fingerprints to identify low-voltage areas and study the effect of AF episodes in patients with mitral valve disease (MVD). Intra-operative epicardial mapping (interelectrode distance 2 mm) of the right and left atrium, Bachmann’s bundle (BB), and pulmonary vein area was performed in 67 patients (27 male, 67 ± 11 years) with or without a history of paroxysmal AF (PAF). In all patients, there were considerable regional variations in voltages. UVs at BB were lower in patients with PAF compared with those without [no AF: 4.94 (3.56–5.98) mV, PAF: 3.30 (2.25–4.57) mV, P = 0.006]. A larger number of low-voltage potentials were recorded at BB in the PAF group [no AF: 2.13 (0.52–7.68) %, PAF: 12.86 (3.18–23.59) %, P = 0.001]. In addition, areas with low-voltage potentials were present in all patients, yet we did not find any predilection sites for low-voltage potentials to occur. Even in SR, advanced atrial remodelling in MVD patients shows marked inter-individual and regional variation. Low UVs are even present during SR in patients without a history of AF indicating that low UVs should carefully be used as target sites for ablative therapy.

Objectives Delirium is a serious complication following neurosurgical procedures. We hypothesise that the beneficial effect of music on a combination of delirium-eliciting factors might reduce delirium incidence following neurosurgery and subsequently improve clinical outcomes. Design Prospective randomised controlled trial. Setting Single centre, conducted at the neurosurgical department of the Erasmus Medical Center, Rotterdam, the Netherlands. Participants Adult patients undergoing craniotomy were eligible. Interventions Patients in the intervention group received preferred recorded music before, during and after the operation until day 3 after surgery. Patients in the control group were treated according to standard of clinical care. Primary and secondary outcome measures Primary outcome was presence or absence of postoperative delirium within the first 5 postoperative days measured with the Delirium Observation Screening Scale (DOSS) and, in case of a daily mean score of 3 or higher, a psychiatric evaluation with the latest Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria. Secondary outcomes included anxiety, heart rate variability (HRV), depth of anaesthesia, delirium severity and duration, postoperative complications, length of stay and location of discharge. Results We enrolled 189 patients (music=95, control=94) from July 2020 through September 2021. Delirium, as assessed by the DOSS, was less common in the music (n=11, 11.6%) than in the control group (n=21, 22.3%, OR:0.49, p=0.048). However, after DSM-5 confirmation, differences in delirium were not significant (4.2% vs 7.4%, OR:0.47, p=0.342). Moreover, music increased the HRV (root mean square of successive differences between normal heartbeats, p=0.012). All other secondary outcomes were not different between groups. Conclusion Our results support the efficacy of music in reducing the incidence of delirium after craniotomy, as found with DOSS but not after DSM-5 confirmation, substantiated by the effect of music on preoperative autonomic tone. Delirium screening tools should be validated and the long-term implications should be evaluated after craniotomy. Trial registration number Trialregister.nl: NL8503 and ClinicalTrials.gov: NCT04649450.