Automated detection of ventricular pre-excitation in pediatric 12-lead ECG.
Background: With increased interest in screening of young people for potential causes of sudden death, accurate automated detection of ventricular pre-excitation (VPE) or Wolff-Parkinson-White syndrome (WPW) in the pediatric resting ECG is important. Several recent studies have shown interobserver v...
| Publicado en: | Journal of Electrocardiology Vol. 49; no. 1; pp. 37 - 42 |
|---|---|
| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
W B Saunders
Jan/Feb2016
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=112052023&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 112052023 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00220736 1276 jtl: Journal of Electrocardiology issn: 00220736 maglogo: N pubinfo: dt: Jan/Feb2016 vid: 49 iid: 1 pid: 1351 pub: W B Saunders place: Philadelphia, Pennsylvania artinfo: ui: 112052023 112052023 NLM26320370 112052023 10.1016/j.jelectrocard.2015.08.006 NLM26320370 112052023 ppf: 37 ppct: 5 formats: tig: atl: Automated detection of ventricular pre-excitation in pediatric 12-lead ECG. aug: au: Gregg, Richard E. Zhou, Sophia H. Dubin, Anne M. affil: Advanced Algorithm Research Center, Philips Healthcare, Andover, MA, USA sug: subj: Pre-Excitation Syndromes Algorithms Methods Electrocardiography Software Methods Information Science Diagnosis, Computer Assisted Information Science Methods Algorithms Reproducibility of Results Electrocardiography Methods Diagnosis, Computer Assisted Methods Pre-Excitation Syndromes Diagnosis Reproducibility of Results Methods Sensitivity and Specificity Software Sensitivity and Specificity Methods Validation Studies Comparative Studies Evaluation Research Multicenter Studies Male Female Child Child, Preschool Adolescence Infant Infant, Newborn Human Child: 6-12 years Child, Preschool: 2-5 years Adolescent: 13-18 years Infant: 1-23 months Infant, Newborn: birth-1 month Male Female ab: Background: With increased interest in screening of young people for potential causes of sudden death, accurate automated detection of ventricular pre-excitation (VPE) or Wolff-Parkinson-White syndrome (WPW) in the pediatric resting ECG is important. Several recent studies have shown interobserver variability when reading screening ECGs and thus an accurate automated reading for this potential cause of sudden death is critical. We designed and tested an automated algorithm to detect pediatric VPE optimized for low prevalence.Methods: Digital ECGs with 12 leads or 15 leads (12-lead plus V3R, V4R and V7) were selected from multiple hospitals and separated into a testing and training database. Inclusion criterion was age less than 16 years. The reference for algorithm detection of VPE was cardiologist annotation of VPE for each ECG. The training database (n=772) consisted of VPE ECGs (n=37), normal ECGs (n=492) and a high concentration of conduction defects, RBBB (n=232) and LBBB (n=11). The testing database was a random sample (n=763). All ECGs were analyzed with the Philips DXL ECG Analysis algorithm for basic waveform measurements. Additional ECG features specific to VPE, mainly delta wave scoring, were calculated from the basic measurements and the average beat. A classifier based on decision tree bootstrap aggregation (tree bagger) was trained in multiple steps to select the number of decision trees and the 10 best features. The classifier accuracy was measured on the test database.Results: The new algorithm detected pediatric VPE with a sensitivity of 78%, a specificity of 99.9%, a positive predictive value of 88% and negative predictive value of 99.7%.Conclusion: This new algorithm for detection of pediatric VPE performs well with a reasonable positive and negative predictive value despite the low prevalence in the general population. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|