Screening for Atrial Fibrillation: Improving Efficiency of Manual Review of Handheld Electrocardiograms

algorithms atrial fibrillation electrocardiography handheld sensors screening

Journal

Engineering proceedings
ISSN: 2673-4591
Titre abrégé: Eng Proc
Pays: Switzerland
ID NLM: 101776621

Informations de publication

Date de publication:
2020
Historique:
entrez: 29 3 2021
pubmed: 30 3 2021
medline: 30 3 2021
Statut: epublish

Résumé

Atrial fibrillation (AF) is a common irregular heart rhythm associated with a five-fold increase in stroke risk. It is often not recognised as it can occur intermittently and without symptoms. A promising approach to detect AF is to use a handheld electrocardiogram (ECG) sensor for screening. However, the ECG recordings must be manually reviewed, which is time-consuming and costly. Our aims were to: (i) evaluate the manual review workload; and (ii) evaluate strategies to reduce the workload. In total, 2141 older adults were asked to record their ECG four times per day for 1-4 weeks in the SAFER (Screening for Atrial Fibrillation with ECG to Reduce stroke) Feasibility Study, producing 162,515 recordings. Patients with AF were identified by: (i) an algorithm classifying recordings based on signal quality (high or low) and heart rhythm; (ii) a nurse reviewing recordings to correct algorithm misclassifications; and (iii) two cardiologists independently reviewing recordings from patients with any evidence of rhythm abnormality. It was estimated that 30,165 reviews were required (20,155 by the nurse, and 5005 by each cardiologist). The total number of reviews could be reduced to 24,561 if low-quality recordings were excluded from review; 18,573 by only reviewing ECGs falling under certain pathological classifications; and 18,144 by only reviewing ECGs displaying an irregularly irregular rhythm for the entire recording. The number of AF patients identified would not fall considerably: from 54 to 54, 54 and 53, respectively. In conclusion, simple approaches may help feasibly reduce the manual workload by 38.4% whilst still identifying the same number of patients with undiagnosed, clinically relevant AF.

Identifiants

pubmed: 33778802
doi: 10.3390/ecsa-7-08195
pmc: PMC7610434
mid: EMS117822
doi:

Types de publication

Journal Article

Langues

eng

Pagination

78

Subventions

Organisme : British Heart Foundation
ID : FS/20/20/34626
Pays : United Kingdom

Déclaration de conflit d'intérêts

Conflicts of Interest: Hannah Clair Lindén is employed by Zenicor Medical Systems AB. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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Auteurs

Madhumitha Pandiaraja (M)

Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.

James Brimicombe (J)

Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.

Martin Cowie (M)

Faculty of Medicine, National Heart & Lung Institute, Imperial College London, London SW3 6LY, UK.

Andrew Dymond (A)

Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.

Hannah Clair Lindén (HC)

Zenicor Medical Systems AB, 113 59 Stockholm, Sweden.

Gregory Y H Lip (GYH)

Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart and Chest Hospital, Liverpool L69 7TX, UK.

Jonathan Mant (J)

Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.

Kate Williams (K)

Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.

Peter H Charlton (PH)

Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.

Classifications MeSH