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.
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