Prediction of breath‐holding spells based on electrocardiographic parameters using machine‐learning model

Author:

Khalilian Mohammad Reza1ORCID,Tofighi Saeed2ORCID,Attar Elham Zohur3,Nikkhah Ali4,Hajipour Mahmoud5,Ghazavi Mohammad6,Samimi Sahar2

Affiliation:

1. Department of Pediatrics, School of Medicine Shahid Beheshti University of Medical Sciences Tehran Iran

2. Department of Cardiology, School of Medicine Tehran University of Medical Sciences Tehran Iran

3. Department of Pediatrics, Mofid Children Hospital Shahid Beheshti University of Medical Sciences Tehran Iran

4. Mofid Children Hospital Shahid Beheshti University of Medical Sciences Tehran Iran

5. Hepatology and Nutrition Research Center, Institute for Children's Health Shahid Beheshti University of Medical Sciences Tehran Iran

6. Department of Pediatrics, School of Medicine Kashan University of Medical Sciences and Health Services Kashan Iran

Abstract

AbstractBackgroundBreath‐holding spells (BHS) are common in infancy and early childhood and may appear like seizures. Factors such as autonomic dysfunction and iron deficiency anemia are thought to contribute to the incidence of BHS. In this study, electrocardiographic (ECG) parameters of patients with BHS were compared to those of healthy, normal children. Logistic regression and machine‐learning (ML) models were then created to predict these spells based on ECG characteristics.MethodsIn this case–control study, 52 BHS children have included as the case and 150 healthy children as the control group. ECG was taken from all children along with clinical examinations. Multivariate logistic regression model was used to predict BHS occurrence based on ECG parameters. ML model was trained and validated using the Gradient‐Boosting algorithm, in the R programming language.ResultsIn BHS and control groups, the average age was 11.90 ± 6.63 and 11.33 ± 6.17 months, respectively (p = .58). Mean heart rate, PR interval, and QRS interval on ECGs did not differ significantly between the two groups. BHS patients had significantly higher QTc, QTd, TpTe, and TpTe/QT (all p‐values < .001). Evaluation of the ML model for prediction of BHS, fitting on the testing data showed AUC, specificity, and sensitivity of 0.94, 0.90, and 0.94 respectively.ConclusionThere are repolarization changes in patients with BHS, as the QTc, QTd, TpTe, and TpTe/QT ratio were significantly higher in these patients, which might be noticeable for future arrhythmia occurrence. In this regard, we developed a successful ML model to predict the possibility of BHS in suspected subjects.

Publisher

Wiley

Subject

Physiology (medical),Cardiology and Cardiovascular Medicine,General Medicine

Reference27 articles.

1. Increased QT dispersion in breath-holding spells

2. Ventricular repolarization changes in children with breath holding spells

3. Cardiac repolarization changes in the children with breath‐holding spells;Amoozgar H.;Iranian Journal of Pediatrics,2013

4. Breath holding spells: Evaluation of autonomic nervous system function;Anil B.;Indian Pediatrics,2005

5. Breath-holding spells

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3