Sudden cardiac death multiparametric classification system for Chagas heart disease's patients based on clinical data and 24-hours ECG monitoring

Resource type
Title
Sudden cardiac death multiparametric classification system for Chagas heart disease's patients based on clinical data and 24-hours ECG monitoring
Abstract
<abstract><p>About 6.5 million people are infected with Chagas disease (CD) globally, and WHO estimates that $ &gt; million people worldwide suffer from ChHD. Sudden cardiac death (SCD) represents one of the leading causes of death worldwide and affects approximately 65% of ChHD patients at a rate of 24 per 1000 patient-years, much greater than the SCD rate in the general population. Its occurrence in the specific context of ChHD needs to be better exploited. This paper provides the first evidence supporting the use of machine learning (ML) methods within non-invasive tests: patients' clinical data and cardiac restitution metrics (CRM) features extracted from ECG-Holter recordings as an adjunct in the SCD risk assessment in ChHD. The feature selection (FS) flows evaluated 5 different groups of attributes formed from patients' clinical and physiological data to identify relevant attributes among 57 features reported by 315 patients at HUCFF-UFRJ. The FS flow with FS techniques (variance, ANOVA, and recursive feature elimination) and Naive Bayes (NB) model achieved the best classification performance with 90.63% recall (sensitivity) and 80.55% AUC. The initial feature set is reduced to a subset of 13 features (4 Classification; 1 Treatment; 1 CRM; and 7 Heart Tests). The proposed method represents an intelligent diagnostic support system that predicts the high risk of SCD in ChHD patients and highlights the clinical and CRM data that most strongly impact the final outcome.</p></abstract>
Publication
Mathematical Biosciences and Engineering
Volume
20
Issue
5
Pages
9159-9178
Date
2023
Journal Abbr
MBE
Language
en
DOI
10.3934/mbe.2023402
ISSN
1551-0018
Accessed
3/21/23, 4:22 PM
Library Catalog
Rights
2023 The Author(s)
Extra
Cc_license_type: cc_by Number: mbe-20-05-402 Primary_atype: Mathematical Biosciences and Engineering Subject_term: Research article Subject_term_id: Research article
Citation
Cavalcante, C. H. L., Primo, P. E. O., Sales, C. A. F., Caldas, W. L., Silva, J. H. M., Souza, A. H., Marinho, E. S., Pedrosa, R. C., Marques, J. A. L., Santos, H. S., Madeiro, J. P. V., Cavalcante, C. H. L., Primo, P. E. O., Sales, C. A. F., Caldas, W. L., Silva, J. H. M., Souza, A. H., Marinho, E. S., Pedrosa, R. C., … Madeiro, J. P. V. (2023). Sudden cardiac death multiparametric classification system for Chagas heart disease’s patients based on clinical data and 24-hours ECG monitoring. Mathematical Biosciences and Engineering, 20(5), 9159–9178. https://doi.org/10.3934/mbe.2023402