Cargando…

Improving efficiency, confidence, and readability in ECG interpretation; the role of signal processing

FUNDING ACKNOWLEDGEMENTS: Type of funding sources: Private company. Main funding source(s): Project privately funded by B-Secur Ltd BACKGROUND: Electrocardiogram (ECG) interpretation is a crucial component in the cardiac clinical pathway that enables the triaging, diagnosis, and treatment of numerou...

Descripción completa

Detalles Bibliográficos
Autores principales: Easlea, H, Mccord, N, Wallace, E, Mckenna, S, Gibbs, A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10206719/
http://dx.doi.org/10.1093/europace/euad122.570
_version_ 1785046290402377728
author Easlea, H
Mccord, N
Wallace, E
Mckenna, S
Gibbs, A
author_facet Easlea, H
Mccord, N
Wallace, E
Mckenna, S
Gibbs, A
author_sort Easlea, H
collection PubMed
description FUNDING ACKNOWLEDGEMENTS: Type of funding sources: Private company. Main funding source(s): Project privately funded by B-Secur Ltd BACKGROUND: Electrocardiogram (ECG) interpretation is a crucial component in the cardiac clinical pathway that enables the triaging, diagnosis, and treatment of numerous medical conditions. However, noise contamination during signal acquisition can hinder clinical interpretation by hiding or distorting the pathology of the underlying ECG. By removing noise to uncover the true beat morphology, signal processing algorithms maximize the diagnostic value of the acquired ECG and reduce clinical burden by eliminating the need for costly and time-consuming repeat investigations. PURPOSE: To evaluate the impact of robust signal processing software on the clinical interpretation and diagnosis of lead I ECGs. Additionally, to investigate whether signal processing could streamline the diagnostic process by revealing pathologies not previously seen in the ECG, improving the speed of diagnosis, and enhancing the readability of the ECG. METHODS: ECG strips (42 x 10 s) representative of a variety of beat morphologies, arrhythmias, and noise types were taken from a proprietary database and provided to healthcare professionals (N = 35) pre- and post-signal processing. Participants possessed varying degrees of experience (12 x Junior (<5 years), 10 x Experienced (5-10 years), 13 x Senior (>10 years)) and specialization in cardiology. Participants were asked to provide a rhythm annotation and corresponding confidence score for each strip when provided in a blinded, randomized order. Participants then provided an additional rhythm annotation when the raw and processed signals were presented side by side, in addition to answering three subjective questions on the impact of signal processing on the ECG interpretation process. RESULTS: Across all participants, 80.2% of processed ECG strips were able to be given a confident diagnosis. This increased to 86% when pre- and post-processed signals were provided alongside one another – an improvement of 10.8% over the raw signals (75.2%). In response to the questions, participants agreed that the processed signal had a positive or very positive impact on; i) helping to reveal a pathology not previously seen in the raw ECG (57% of strips), ii) speeding up the diagnosis (71% of strips), and iii) improving the readability of the ECG (80% of strips). CONCLUSION: By effectively removing noise whilst retaining true beat morphology, signal processing increased the amount of clinically diagnostic ECG data and allowed clinicians to make a more efficient, confident diagnosis. With the positive impacts observed across all participant experience levels, the results suggest that robust signal processing has the potential to streamline the clinical interpretation of ECGs.
format Online
Article
Text
id pubmed-10206719
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-102067192023-05-25 Improving efficiency, confidence, and readability in ECG interpretation; the role of signal processing Easlea, H Mccord, N Wallace, E Mckenna, S Gibbs, A Europace 38.7.99 - Remote Patient Monitoring and Telehealth, Other FUNDING ACKNOWLEDGEMENTS: Type of funding sources: Private company. Main funding source(s): Project privately funded by B-Secur Ltd BACKGROUND: Electrocardiogram (ECG) interpretation is a crucial component in the cardiac clinical pathway that enables the triaging, diagnosis, and treatment of numerous medical conditions. However, noise contamination during signal acquisition can hinder clinical interpretation by hiding or distorting the pathology of the underlying ECG. By removing noise to uncover the true beat morphology, signal processing algorithms maximize the diagnostic value of the acquired ECG and reduce clinical burden by eliminating the need for costly and time-consuming repeat investigations. PURPOSE: To evaluate the impact of robust signal processing software on the clinical interpretation and diagnosis of lead I ECGs. Additionally, to investigate whether signal processing could streamline the diagnostic process by revealing pathologies not previously seen in the ECG, improving the speed of diagnosis, and enhancing the readability of the ECG. METHODS: ECG strips (42 x 10 s) representative of a variety of beat morphologies, arrhythmias, and noise types were taken from a proprietary database and provided to healthcare professionals (N = 35) pre- and post-signal processing. Participants possessed varying degrees of experience (12 x Junior (<5 years), 10 x Experienced (5-10 years), 13 x Senior (>10 years)) and specialization in cardiology. Participants were asked to provide a rhythm annotation and corresponding confidence score for each strip when provided in a blinded, randomized order. Participants then provided an additional rhythm annotation when the raw and processed signals were presented side by side, in addition to answering three subjective questions on the impact of signal processing on the ECG interpretation process. RESULTS: Across all participants, 80.2% of processed ECG strips were able to be given a confident diagnosis. This increased to 86% when pre- and post-processed signals were provided alongside one another – an improvement of 10.8% over the raw signals (75.2%). In response to the questions, participants agreed that the processed signal had a positive or very positive impact on; i) helping to reveal a pathology not previously seen in the raw ECG (57% of strips), ii) speeding up the diagnosis (71% of strips), and iii) improving the readability of the ECG (80% of strips). CONCLUSION: By effectively removing noise whilst retaining true beat morphology, signal processing increased the amount of clinically diagnostic ECG data and allowed clinicians to make a more efficient, confident diagnosis. With the positive impacts observed across all participant experience levels, the results suggest that robust signal processing has the potential to streamline the clinical interpretation of ECGs. Oxford University Press 2023-05-24 /pmc/articles/PMC10206719/ http://dx.doi.org/10.1093/europace/euad122.570 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle 38.7.99 - Remote Patient Monitoring and Telehealth, Other
Easlea, H
Mccord, N
Wallace, E
Mckenna, S
Gibbs, A
Improving efficiency, confidence, and readability in ECG interpretation; the role of signal processing
title Improving efficiency, confidence, and readability in ECG interpretation; the role of signal processing
title_full Improving efficiency, confidence, and readability in ECG interpretation; the role of signal processing
title_fullStr Improving efficiency, confidence, and readability in ECG interpretation; the role of signal processing
title_full_unstemmed Improving efficiency, confidence, and readability in ECG interpretation; the role of signal processing
title_short Improving efficiency, confidence, and readability in ECG interpretation; the role of signal processing
title_sort improving efficiency, confidence, and readability in ecg interpretation; the role of signal processing
topic 38.7.99 - Remote Patient Monitoring and Telehealth, Other
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10206719/
http://dx.doi.org/10.1093/europace/euad122.570
work_keys_str_mv AT easleah improvingefficiencyconfidenceandreadabilityinecginterpretationtheroleofsignalprocessing
AT mccordn improvingefficiencyconfidenceandreadabilityinecginterpretationtheroleofsignalprocessing
AT wallacee improvingefficiencyconfidenceandreadabilityinecginterpretationtheroleofsignalprocessing
AT mckennas improvingefficiencyconfidenceandreadabilityinecginterpretationtheroleofsignalprocessing
AT gibbsa improvingefficiencyconfidenceandreadabilityinecginterpretationtheroleofsignalprocessing