Delivery Room ST Segment Analysis to Predict Short Term Outcomes in Near-Term and Term Newborns

Background: ST-segment changes to the fetal electrocardiogram (ECG) may indicate fetal acidosis. No large-scale characterization of ECG morphology immediately after birth has been performed, but ECG is used for heart rate (HR) assessment. We aimed to investigate ECG morphology immediately after birth in asphyxiated infants, using one-lead dry-electrode ECG developed for HR measurement. Methods: Observational study in Tanzania, between 2013–2018. Near-term and term infants that received bag-mask ventilation (BMV), and healthy controls, were monitored with one-lead dry-electrode ECG with a non-diagnostic bandwidth. ECGs were classified as normal, with ST-elevations or other ST-segment abnormalities including a biphasic ST-segment. We analyzed ECG morphology in relation to perinatal variables or short-term outcomes. Results: A total of 494 resuscitated and 25 healthy infants were included. ST-elevations were commonly seen both in healthy infants (7/25; 28%) and resuscitated (320/494; 65%) infants. The apparent ST-elevations were not associated with perinatal variables or short-term outcomes. Among the 32 (6.4%) resuscitated infants with “other ST-segment abnormalities”, duration of BMV was longer, 1-min Apgar score lower and normal outcomes less frequent than in the resuscitated infants with normal ECG or ST-elevations. Conclusions: ST-segment elevation was commonly seen and not associated with negative outcomes when using one-lead dry-electrode ECG. Other ST-segment abnormalities were associated with prolonged BMV and worse outcome. ECG with appropriate bandwidth and automated analysis may potentially in the future aid in the identification of severely asphyxiated infants.

Reliability of Electrocardiogram Signals during Feature Extraction Stage for Smart Textile Shirts

Wearable smart textiles have garnered significant interest due to their high flexibility, reusability, convenience and ability to work on home-based, real-life and real-time monitoring. Wearable smart textiles are shirts with inbuilt textile sensors that enable electrocardiogram (ECG) data to be collected more comfortably and smoothly outside the laboratory and clinical environment for a continuous and longer duration for ECG data collection. However, the existing ECG wearable smart textile main challenge is maintaining the quality and reliability of data across multiple wearable smart textile shirts. Therefore, this research analyses the capability of ECG morphology during Feature Extraction stages for different wearable smart textile shirts. This paper reports the experiment conducted on eleven healthy volunteers, either wearing the Hexoskin smart shirt or the HeartIn Fit shirt or both. ECG data were recorded while they are doing normal daily routine activities for at least 45 minutes. The study demonstrates a significant possibility of reliability in Feature Extraction stages at different time instances among subject and wearable smart textiles shirts. With R peaks average between 0.543 to 1.194 mV and R-R interval average between 0.625 to 0.799 seconds, the study concludes that both wearable smart textiles do not significantly differ in Feature Extraction stages. Thus, both wearable smart textiles gave a significant result, although both are affected by their wearer’s motion artefacts during the shifting of body postures and the wearer’s body physical states. Furthermore, the ECG morphology in this study has yielded a promising result in real life and as on-the-go ECG smart textile biometric readiness for future explorations.

Symmetric Projection Attractor Reconstruction: Sex Differences in the ECG

Background: The electrocardiogram (ECG) is a key tool in patient management. Automated ECG analysis supports clinical decision-making, but traditional fiducial point identification discards much of the time-series data that captures the morphology of the whole waveform. Our Symmetric Projection Attractor Reconstruction (SPAR) method uses all the available data to provide a new visualization and quantification of the morphology and variability of any approximately periodic signal. We therefore applied SPAR to ECG signals to ascertain whether this more detailed investigation of ECG morphology adds clinical value.Methods: Our aim was to demonstrate the accuracy of the SPAR method in discriminating between two biologically distinct groups. As sex has been shown to influence the waveform appearance, we investigated sex differences in normal sinus rhythm ECGs. We applied the SPAR method to 9,007 10 second 12-lead ECG recordings from Physionet, which comprised; Dataset 1: 104 subjects (40% female), Dataset 2: 8,903 subjects (54% female).Results: SPAR showed clear visual differences between female and male ECGs (Dataset 1). A stacked machine learning model achieved a cross-validation sex classification accuracy of 86.3% (Dataset 2) and an unseen test accuracy of 91.3% (Dataset 1). The mid-precordial leads performed best in classification individually, but the highest overall accuracy was achieved with all 12 leads. Classification accuracy was highest for young adults and declined with older age.Conclusions: SPAR allows quantification of the morphology of the ECG without the need to identify conventional fiducial points, whilst utilizing of all the data reduces inadvertent bias. By intuitively re-visualizing signal morphology as two-dimensional images, SPAR accurately discriminated ECG sex differences in a small dataset. We extended the approach to a machine learning classification of sex for a larger dataset, and showed that the SPAR method provided a means of visualizing the similarities of subjects given the same classification. This proof-of-concept study therefore provided an implementation of SPAR using existing data and showed that subtle differences in the ECG can be amplified by the attractor. SPAR's supplementary analysis of ECG morphology may enhance conventional automated analysis in clinically important datasets, and improve patient stratification and risk management.

Selective Proximal Left Anterior Fascicle Pacemapping for Guiding narrow QRS Premature Ventricular Complex ablation from the Right Coronary Cusp

Premature ventricular complexes (PVC) ablation has increased over the past decades. The morphology of PVCs arising from left anterior fascicle (LAF) is typically a right bundle branch block-like morphology with an inferior axis showing a qR or qRs complex in the inferior leads and an rS or RS complex in leads I and aVL. We describe the case of a 38 years old woman with symptomatic, high burden PVCs, despite of beta blockers treatment. The PVC’s ECG morphology suggested an origin in the LAF. This case illustrates how ablation from the right coronary cusp for PVC arising from the LAF could be accurately guided by pace-mapping. At this location, pacing at different outputs can result in both a selective and a non-selective capture of the left anterior fascicle.

Design and Optimization of ECG Modeling for Generating Different Cardiac Dysrhythmias

The electrocardiogram (ECG) has significant clinical importance for analyzing most cardiovascular diseases. ECGs beat morphologies, beat durations, and amplitudes vary from subject to subject and diseases to diseases. Therefore, ECG morphology-based modeling has long-standing research interests. This work aims to develop a simplified ECG model based on a minimum number of parameters that could correctly represent ECG morphology in different cardiac dysrhythmias. A simple mathematical model based on the sum of two Gaussian functions is proposed. However, fitting more than one Gaussian function in a deterministic way has accuracy and localization problems. To solve these fitting problems, two hybrid optimization methods have been developed to select the optimal ECG model parameters. The first method is the combination of an approximation and global search technique (ApproxiGlo), and the second method is the combination of an approximation and multi-start search technique (ApproxiMul). The proposed model and optimization methods have been applied to real ECGs in different cardiac dysrhythmias, and the effectiveness of the model performance was measured in time, frequency, and the time-frequency domain. The model fit different types of ECG beats representing different cardiac dysrhythmias with high correlation coefficients (>0.98). Compared to the nonlinear fitting method, ApproxiGlo and ApproxiMul are 3.32 and 7.88 times better in terms of root mean square error (RMSE), respectively. Regarding optimization, the ApproxiMul performs better than the ApproxiGlo method in many metrics. Different uses of this model are possible, such as a syntactic ECG generator using a graphical user interface has been developed and tested. In addition, the model can be used as a lossy compression with a variable compression rate. A compression ratio of 20:1 can be achieved with 1 kHz sampling frequency and 75 beats per minute. These optimization methods can be used in different engineering fields where the sum of Gaussians is used.

Cardiac magnetic resonance features of left dominant arrhythmogenic cardiomyopathy: differential diagnosis with myocarditis

Objectives To identify potential imaging features at cardiac magnetic resonance (CMR) specific for left-dominant arrhythmogenic cardiomyopathy (LDAC) diagnosis. Materials and methods Between January 2011 and May 2016, we considered 36 consecutive stable patients with a recent diagnosis of significant VA and ECG morphology consistent with a LV origin, detection of potential LV arrhythmic substrate at CMR, undergoing a clinically-indicated LV endomyocardial biopsy. Exclusion criteria were history of known cardiac disease, contraindications to CMR and impaired CMR image quality. After application of these criteria, in 9 patients endomyocardial biopsy showed tissue abnormalities consistent with the diagnosis of LDAC. From the same CMR-endomyocardial biopsy registry, a second group of 9 consecutive patients with a histological diagnosis of previous myocarditis were identified. Results Mid-wall LGE in the interventricular septum was detected in 5 myocarditis, without findings in LDAC group (p=0.03), whereas subepicardial LGE at the level of posterolateral wall of LV was detected in 8 cases of LDAC vs. 2 cases of myocarditis (p=0.02). Fat infiltration, and particularly subepicardial posterolateral fat infiltration, was found in all LDAC patients vs. one myocarditis only (p<0.01). No differences in other CMR findings or in any clinical or echocardiographic parameters were found between patients with a biopsy consistent with LDAC vs. patients in whom biopsy suggested myocarditis. Conclusions In patients with significant VA and ECG morphology consistent with a LV origin, identification of morpho-functional involvement of the subepicardial layer of LV posterolateral wall at CMR (LGE, fat infiltration, wall dyskinesis) is consistent with a diagnosis of LDAC. Funding Acknowledgement Type of funding source: None

Is the Correct Anatomical Placement of the Electrocardiogram (ECG) Electrodes Essential to Diagnosis in the Clinical Setting A Systematic Review

Background: Anatomical misplacement of the Electrocardiogram (ECG) electrode(s) is common, with significant impact on clinical diagnosis. Reasons are multi-faceted, with this review examining the consequential effects of misplacement to ECG morphology, diagnosis, prognosis, patient outcomes, and potential impact to patient care pathway. Objectives: This review examined the significance of misplacement, its’ commonality and ensuing effect on patient safety, accurate ECG acquisition and diagnosis, with evaluation of reasons for such misplacement.Methodology: Review of available literature was conducted using electronic databases. In-line with the Preferred Reporting Items for Systematic reviews and Meta – analysis protocols (PRISMA) 2015 checklist, this review was conducted with search criteria, search terms, eligibility for inclusion/ exclusion criteria, extraction and data analysis predetermined by the authors. Keywords were arranged according to grouping of terms surrounding ECG, anatomical placement, and diagnosis. The search strategy was conducted during September/October 2019. Scoping searches were conducted alongside reference lists of included studies hand searched (Snowballing) for further relevant studies. The Critical Appraisal Skills Programme (CASP) was used to methodically appraise papers (CASP, 2019). Screening of titles and abstracts of identified citations was performed by a single reviewer. Eligible articles then full text screened independently by two reviewers. Disagreements were discussed and resolved by a third reviewer. In instances of unclear reporting, authors were contacted to provide further information and clarity. Assessment of relevant literature and critical appraisal of primary research, pertaining to the clinical diagnosis and effects of anatomical misplacement of ECG electrodes, formulate the thematic discussion drawn by this review. Results: This review identified a plethora of causes, ranging from: operator error; lack of anatomical awareness; inaccurate assessment of anatomical landmarks; obesity; differences in anatomy/gender; levels of undress and lack of appreciation of consequences of misplacement, both modifiable and non-modifiable attributable to electrode misplacement. Clinical diagnosis can be altered owing to erroneous placement of electrodes. ECG morphology is altered due to incorrect anatomical misplacement, culminating substandard practice, a missed diagnosis or misdiagnosis and potential harm. Conclusion: Correct anatomical placement of ECG electrodes is essential to diagnosis in the clinical setting. Peer-led educational intervention with mandatory training is essential to improve practice. PROSPERO Registration Number: CRD42019152461