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Titolo:
SINGLE-BEAT ANALYSIS OF VENTRICULAR LATE POTENTIALS IN THE SURFACE ELECTROCARDIOGRAM USING THE SPECTROTEMPORAL PATTERN-RECOGNITION ALGORITHM IN PATIENTS WITH CORONARY-ARTERY DISEASE
Autore:
STEINBIGLER P; HABERL R; JILGE G; STEINBECK G;
Indirizzi:
UNIV MUNICH,MED HOSP 1,MARCHIONINISTR 15 D-81366 MUNICH GERMANY
Titolo Testata:
European heart journal
fascicolo: 3, volume: 19, anno: 1998,
pagine: 435 - 446
SICI:
0195-668X(1998)19:3<435:SAOVLP>2.0.ZU;2-#
Fonte:
ISI
Lingua:
ENG
Soggetto:
SIGNAL-AVERAGED ELECTROCARDIOGRAM; HIGH-RESOLUTION ELECTROCARDIOGRAPHY; ACUTE MYOCARDIAL-INFARCTION; FREQUENCY-ANALYSIS; THROMBOLYTIC ERA; TERMINAL QRS; TACHYCARDIA; IDENTIFICATION; REGISTRATION; CYCLE;
Keywords:
LATE POTENTIALS; SINGLE BEAT ANALYSIS; SIGNAL AVERAGING; SPECTRAL ANALYSIS; VENTRICULAR TACHYCARDIA;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Citazioni:
41
Recensione:
Indirizzi per estratti:
Citazione:
P. Steinbigler et al., "SINGLE-BEAT ANALYSIS OF VENTRICULAR LATE POTENTIALS IN THE SURFACE ELECTROCARDIOGRAM USING THE SPECTROTEMPORAL PATTERN-RECOGNITION ALGORITHM IN PATIENTS WITH CORONARY-ARTERY DISEASE", European heart journal, 19(3), 1998, pp. 435-446

Abstract

Aims Post-infarction risk stratification can be ascertained from beat-to-beat variations in ventricular late potentials. However, gaining such information by conventional late potential analysis using signal averaging is still not possible. Methods We therefore developed the spectrotemporal pattern recognition algorithm in order to detect beat-to-beat variations in late potentials. Based on the spectrotemporal pattern recognition algorithm two-dimensional correlation function, the typical spectral pattern of late potentials can be identified in spectrotemporal maps of single beats, even in the presence of noise. Results Surface electrocardiograms of 385 patients after myocardial infarction (85 with documented sustained ventricular tachycardia (group 1), 100 with fast, polymorphic ventricular tachycardia (>270 cycles.min(-1)) orprimary ventricular fibrillation (group 2), 200 without ventricular arrhythmias (group 3) and 45 healthy volunteers (group 4), were analysed. The spectrotemporal pattern recognition algorithm detected late potentials in single beats in 89% of group 1 patients, in 79% of group 2,in 22% of group 3 and in 4% of normals. The spectrotemporal pattern recognition algorithm measured late potential frequency and extension of late potentials into the ST segment, which was significantly different between groups 1 and 2. Beat-to-beat variations in late potentials,with respect to frequency and extension into the ST segment, were markedly higher in patients with a history of primary ventricular fibrillation. Conclusion Single-beat analysis using the spectrotemporal pattern recognition algorithm may improve risk stratification of patients after myocardial infarction, and provides information on patients proneto ventricular fibrillation.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 18/09/20 alle ore 10:17:43