Identification of exercise-induced ischemia using QRS slopes.
In this work we studied a computer-aided approach using QRS slopes as unconventional ECG features to identify the exercise-induced ischemia during exercise stress testing and demonstrated that the performance is comparable to the experts' manual analysis using standard criteria involving ST-segment...
| Publicado en: | Journal of Electrocardiology Vol. 49; no. 1; pp. 55 - 60 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
W B Saunders
Jan/Feb2016
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| 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=112052016&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 112052016 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: 112052016 112052016 NLM26607407 112052016 10.1016/j.jelectrocard.2015.09.001 NLM26607407 112052016 ppf: 55 ppct: 5 formats: tig: atl: Identification of exercise-induced ischemia using QRS slopes. aug: au: Firoozabadi, Reza Gregg, Richard E. Babaeizadeh, Saeed affil: Advanced Algorithm Research Center, Philips Healthcare, Andover, MA, USA sug: subj: Reproducibility of Results Methods Algorithms Methods Ischemia Myocardial Ischemia Diagnosis Exercise Test Methods Information Science Myocardial Ischemia Electrocardiography Methods Sensitivity and Specificity Electrocardiography Information Science Methods Ischemia Diagnosis Diagnosis, Computer Assisted Sensitivity and Specificity Methods Diagnosis, Computer Assisted Methods Exercise Test Validation Studies Comparative Studies Evaluation Research Multicenter Studies Human ab: In this work we studied a computer-aided approach using QRS slopes as unconventional ECG features to identify the exercise-induced ischemia during exercise stress testing and demonstrated that the performance is comparable to the experts' manual analysis using standard criteria involving ST-segment depression. We evaluated the performance of our algorithm using a database including 927 patients undergoing exercise stress tests and simultaneously collecting the ECG recordings and SPECT results. High resolution 12-lead ECG recordings were collected continuously throughout the rest, exercise, and recovery phases. Patients in the database were classified into three categories of moderate/severe ischemia, mild ischemia, and normal according to the differences in sum of the individual segment scores for the rest and stress SPECT images. Philips DXL 16-lead diagnostic algorithm was run on all 10-s segments of 12-lead ECG recordings for each patient to acquire the representative beats, ECG fiducial points from the representative beats, and other ECG parameters. The QRS slopes were extracted for each lead from the averaged representative beats and the leads with highest classification power were selected. We employed linear discriminant analysis and measured the performance using 10-fold cross-validation. Comparable performance of this method to the conventional ST-segment analysis exhibits the classification power of QRS slopes as unconventional ECG parameters contributing to improved identification of exercise-induced ischemia. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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