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Demographic and Methodological Heterogeneity in Electrocardiogram Signals From Guinea Pigs.

ABSTRACT: Electrocardiograms (ECG) are universally used to measure the electrical activity of the heart; however, variations in recording techniques and/or subject demographics can affect ECG interpretation. In this study, we investigated variables that are likely to influence ECG metric measurements in cardiovascular research, including recording technique, use of anesthesia, and animal model characteristics. Awake limb lead ECG recordings were collected in vivo from adult guinea pigs using a platform ECG system, while recordings in anesthetized animals were performed using both a platform and needle ECG system. We report significant heterogeneities in ECG metric values that are attributed to methodological differences (e.g., ECG lead configuration, ECG recording platform, presence or absence of anesthesia) that persist even within the same cohort of animals. Further, we report that variability in animal demographics is preserved in vivo ECG recordings-with animal age serving as a significant contributor, while sex-specific influences were less pronounced. Methodological approaches and subject demographics should be fully considered when interpreting ECG values in animal models, comparing datasets between studies, or developing artificial intelligence algorithms that utilize an ECG database.

SUBMITTER: Haq KT

PROVIDER: S-EPMC9202081 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Demographic and Methodological Heterogeneity in Electrocardiogram Signals From Guinea Pigs.

Haq Kazi T KT Cooper Blake L BL Berk Fiona F Roberts Anysja A Swift Luther M LM Posnack Nikki Gillum NG

Frontiers in physiology 20220602

Electrocardiograms (ECG) are universally used to measure the electrical activity of the heart; however, variations in recording techniques and/or subject demographics can affect ECG interpretation. In this study, we investigated variables that are likely to influence ECG metric measurements in cardiovascular research, including recording technique, use of anesthesia, and animal model characteristics. Awake limb lead ECG recordings were collected <i>in vivo</i> from adult guinea pigs using a plat ...[more]

PMID: 35721548

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Project description:UnlabelledEbola virus (EBOV) transmission is currently poorly characterized and is thought to occur primarily by direct contact with infectious material; however transmission from swine to nonhuman primates via the respiratory tract has been documented. To establish an EBOV transmission model for performing studies with statistical significance, groups of six guinea pigs (gps) were challenged intranasally (i.n.) or intraperitoneally (i.p.) with 10,000 times the 50% lethal dose (LD50) of gp-adapted EBOV, and naive gps were then introduced as cage mates for contact exposure at 1 day postinfection (p.i.). The animals were monitored for survival and clinical signs of disease and quantitated for virus shedding postexposure. Changes in the duration of contact of naive gps with infected animals were evaluated for their impact on transmission efficiency. Transmission was more efficient from i.n.- than from i.p.-challenged gps, with 17% versus 83% of naive gps surviving exposure, respectively. Virus shedding was detected beginning at 3 days p.i. from both i.n.- and i.p.-challenged animals. Contact duration positively correlated with transmission efficiency, and the abrogation of direct contact between infected and naive animals through the erection of a steel mesh was effective at stopping virus spread, provided that infectious animal bedding was absent from the cages. Histopathological and immunohistochemical findings show that i.n.-infected gps display enhanced lung pathology and EBOV antigen in the trachea, which supports increased virus transmission from these animals. The results suggest that i.n.-challenged gps are more infectious to naive animals than their systemically infected counterparts and that transmission occurs through direct contact with infectious materials, including those transported through air movement over short distances.ImportanceEbola is generally thought to be spread between humans though infectious bodily fluids. However, a study has shown that Ebola can be spread from pigs to monkeys without direct contact. Further studies have been hampered, because an economical animal model for Ebola transmission is not available. To address this, we established a transmission model in guinea pigs and determined the mechanisms behind virus spread. The survival data, in addition to microscopic examination of lung and trachea sections, show that mucosal infection of guinea pigs is an efficient model for Ebola transmission. Virus spread is increased with longer contact times with an infected animal and is possible without direct contact between an infected and a naive host but can be stopped if infectious materials are absent. These results warrant consideration for the development of future strategies against Ebola transmission and for a better understanding of the parameters involved in virus spread.

Project description:BackgroundThe standard configuration's set of twelve electrocardiogram (ECG) leads is optimal for the medical diagnosis of diverse cardiac conditions. However, it requires ten electrodes on the patient's limbs and chest, which is uncomfortable and cumbersome. Interlead conversion methods can reconstruct missing leads and enable more comfortable acquisitions, including in wearable devices, while still allowing for adequate diagnoses. Currently, methodologies for interlead ECG conversion either require multiple reference (input) leads and/or require input signals to be temporally aligned considering the ECG landmarks.MethodsUnlike the methods in the literature, this paper studies the possibility of converting ECG signals into all twelve standard configuration leads using signal segments from only one reference lead, without temporal alignment (blindly-segmented). The proposed methodology is based on a deep learning encoder-decoder U-Net architecture, which is compared with adaptations based on convolutional autoencoders and label refinement networks. Moreover, the method is explored for conversion with one single shared encoder or multiple individual encoders for each lead.ResultsDespite the more challenging settings, the proposed methodology was able to attain state-of-the-art level performance in multiple target leads, and both lead I and lead II seem especially suitable to convert certain sets of leads. In cross-database tests, the methodology offered promising results despite acquisition setup differences. Furthermore, results show that the presence of medical conditions does not have a considerable effect on the method's performance.ConclusionsThis study shows the feasibility of converting ECG signals using single-lead blindly-segmented inputs. Although the results are promising, further efforts should be devoted towards the improvement of the methodologies, especially the robustness to diverse acquisition setups, in order to be applicable to cardiac health monitoring in wearable devices and less obtrusive clinical scenarios.

Dataset Information

Demographic and Methodological Heterogeneity in Electrocardiogram Signals From Guinea Pigs.

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Demographic and Methodological Heterogeneity in Electrocardiogram Signals From Guinea Pigs.

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