Evaluating the Impacts of Digital ECG Denoising on the Interpretive Capabilities of Healthcare Professionals

Overview

Journal Eur Heart J Digit Health

Publisher Oxford University Press

Specialty Cardiology & Vascular Diseases

Date 2024 Sep 25

PMID 39318698

Authors

Stacey McKenna

Naomi McCord

Jordan Diven

Matthew Fitzpatrick

Holly Easlea

Austin Gibbs

Andrew R J Mitchell

Affiliations

Soon will be listed here.

Abstract

Aims: Electrocardiogram (ECG) interpretation is an essential skill across multiple medical disciplines; yet, studies have consistently identified deficiencies in the interpretive performance of healthcare professionals linked to a variety of educational and technological factors. Despite the established correlation between noise interference and erroneous diagnoses, research evaluating the impacts of digital denoising software on clinical ECG interpretation proficiency is lacking.

Methods And Results: Forty-eight participants from a variety of medical professions and experience levels were prospectively recruited for this study. Participants' capabilities in classifying common cardiac rhythms were evaluated using a sequential blinded and semi-blinded interpretation protocol on a challenging set of single-lead ECG signals (42 × 10 s) pre- and post-denoising with robust, cloud-based ECG processing software. Participants' ECG rhythm interpretation performance was greatest when raw and denoised signals were viewed in a combined format that enabled comparative evaluation. The combined view resulted in a 4.9% increase in mean rhythm classification accuracy (raw: 75.7% ± 14.5% vs. combined: 80.6% ± 12.5%, = 0.0087), a 6.2% improvement in mean five-point graded confidence score (raw: 4.05 ± 0.58 vs. combined: 4.30 ± 0.48, < 0.001), and 9.7% reduction in the mean proportion of undiagnosable data (raw: 14.2% ± 8.2% vs. combined: 4.5% ± 2.4%, < 0.001), relative to raw signals alone. Participants also had a predominantly positive perception of denoising as it related to revealing previously unseen pathologies, improving ECG readability, and reducing time to diagnosis.

Conclusion: Our findings have demonstrated that digital denoising software improves the efficacy of rhythm interpretation on single-lead ECGs, particularly when raw and denoised signals are provided in a combined viewing format, warranting further investigation into the impact of such technology on clinical decision-making and patient outcomes.

Citing Articles

Preprocessing and Denoising Techniques for Electrocardiography and Magnetocardiography: A Review.

Jia Y, Pei H, Liang J, Zhou Y, Yang Y, Cui Y Bioengineering (Basel). 2024; 11(11).

PMID: 39593769 PMC: 11591354. DOI: 10.3390/bioengineering11111109.

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