Improved pre-test likelihood estimation of coronary artery disease using phonocardiography

Bjarke Skogstad Larsen*, Simon Winther, Louise Nissen, Axel Diederichsen, Morten Bøttcher, Matthias Renker, Johannes Jan Struijk, Mads Græsbøll Christensen, Samuel Emil Schmidt

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

2 Citations (Scopus)
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Abstract

AIMS: Current early risk stratification of coronary artery disease (CAD) consists of pre-test probability scoring such as the 2019 ESC guidelines on chronic coronary syndromes (ESC2019), which has low specificity and thus rule-out capacity. A newer clinical risk factor model (risk factor-weighted clinical likelihood, RF-CL) showed significantly improved rule-out capacity over the ESC2019 model. The aim of the current study was to investigate if the addition of acoustic features to the RF-CL model could improve the rule-out potential of the best performing clinical risk factor models.

METHODS AND RESULTS: Four studies with heart sound recordings from 2222 patients were pooled and distributed into two data sets: training and test. From a feature bank of 40 acoustic features, a forward-selection technique was used to select three features that were added to the RF-CL model. Using a cutoff of 5% predicted risk of CAD, the developed acoustic-weighted clinical likelihood (A-CL) model showed significantly ( P < 0.05) higher specificity of 48.6% than the RF-CL model (specificity of 41.5%) and ESC 2019 model (specificity of 6.9%) while having the same sensitivity of 84.9% as the RF-CL model. Area under the curve of the receiver operating characteristic for the three models was 72.5% for ESC2019, 76.7% for RF-CL, and 79.5% for A-CL.

CONCLUSION: The proposed A-CL model offers significantly improved rule-out capacity over the ESC2019 model and showed better overall performance than the RF-CL model. The addition of acoustic features to the RF-CL model was shown to significantly improve early risk stratification of symptomatic patients suspected of having stable CAD.

Original languageEnglish
JournalEuropean Heart Journal - Digital Health
Volume3
Issue number4
Pages (from-to)600-609
Number of pages10
ISSN2634-3916
DOIs
Publication statusPublished - Dec 2022

Bibliographical note

© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.

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