OBJECTIVE: To compare manual and computer automated techniques for measuring QT dispersion. DESIGN: Assessment of the ability of manual and automatic measurements of QT dispersion to discriminate between a normal group and two cardiac groups. SUBJECTS: 12 simultaneous electrocardiogram leads were recorded from 25 healthy volunteers, 25 subjects after myocardial infarction, and 25 with cardiac arrhythmias. MAIN OUTCOME MEASURES: For each subject, QT dispersion was measured as the difference between the maximum and minimum QT from all 12 leads and separately for only those leads with T amplitudes of > 100 microV and for those > 250 microV. RESULTS: Manual QT dispersion (T > 100 microV) was greater (P < 0.02) in the arrhythmia patients (mean (SD), 45 (21) ms), but not the infarction patients (54 (36) ms), than in the normal subjects (39 (13) ms). There were no significant differences when all T waves were included. QT dispersion was significantly reduced by an average of 30% when T waves < 100 microV were excluded, and by 51% when those < 250 microV were excluded. Automatic techniques gave different measurements for dispersion in comparison with manual measurements. Three of the four automatic techniques detected significant differences between normal and both patient groups when no leads were excluded (P < 0.01) as well as when T waves < 100 microV were excluded (with increased significance, P < 0.002). CONCLUSIONS: Measurements of QT dispersion from small T waves increases measurement variability and reduces the potential for detecting clinical differences. Automatic measurement of QT dispersion gives different results from manual measurement, but can satisfactorily discriminate between normal and abnormal groups with good quality electrocardiograms.
OBJECTIVE: To compare manual and computer automated techniques for measuring QT dispersion. DESIGN: Assessment of the ability of manual and automatic measurements of QT dispersion to discriminate between a normal group and two cardiac groups. SUBJECTS: 12 simultaneous electrocardiogram leads were recorded from 25 healthy volunteers, 25 subjects after myocardial infarction, and 25 with cardiac arrhythmias. MAIN OUTCOME MEASURES: For each subject, QT dispersion was measured as the difference between the maximum and minimum QT from all 12 leads and separately for only those leads with T amplitudes of > 100 microV and for those > 250 microV. RESULTS: Manual QT dispersion (T > 100 microV) was greater (P < 0.02) in the arrhythmiapatients (mean (SD), 45 (21) ms), but not the infarctionpatients (54 (36) ms), than in the normal subjects (39 (13) ms). There were no significant differences when all T waves were included. QT dispersion was significantly reduced by an average of 30% when T waves < 100 microV were excluded, and by 51% when those < 250 microV were excluded. Automatic techniques gave different measurements for dispersion in comparison with manual measurements. Three of the four automatic techniques detected significant differences between normal and both patient groups when no leads were excluded (P < 0.01) as well as when T waves < 100 microV were excluded (with increased significance, P < 0.002). CONCLUSIONS: Measurements of QT dispersion from small T waves increases measurement variability and reduces the potential for detecting clinical differences. Automatic measurement of QT dispersion gives different results from manual measurement, but can satisfactorily discriminate between normal and abnormal groups with good quality electrocardiograms.
Authors: P Laguna; N V Thakor; P Caminal; R Jané; H R Yoon; A Bayés de Luna; V Marti; J Guindo Journal: Med Biol Eng Comput Date: 1990-01 Impact factor: 2.602
Authors: Jose Luis Alonso; Pablo Martínez; Montserrat Vallverdú; Iwona Cygankiewicz; Maria Vittoria Pitzalis; Antoni Bayés Genís; Juan Cinca; Paolo Rizzon; Pere Caminal; Wojciech Zareba; Antoni Bayés de Luna Journal: Ann Noninvasive Electrocardiol Date: 2005-04 Impact factor: 1.468
Authors: Carlos Alberto Pastore; Sandra Regina Arcêncio; Nancy M M O Tobias; Elisabeth Kaiser; Martino Martinelli Filho; Luis Felipe P Moreira; Noedir A Stolf; Edimar Bocchi; José Antonio Franchini Ramires Journal: Ann Noninvasive Electrocardiol Date: 2004-10 Impact factor: 1.468
Authors: K Esposito; G Nicoletti; S Marzano; P Gualdiero; C Carusone; R Marfella; F Beneduce; D Giugliano Journal: J Endocrinol Invest Date: 2002-12 Impact factor: 4.256
Authors: James P Tsikouris; Michael J Peeters; Craig D Cox; Gary E Meyerrose; Charles F Seifert Journal: Ann Noninvasive Electrocardiol Date: 2006-01 Impact factor: 1.468