INTRODUCTION: The aim of our study was to assess the effectiveness of the nonlinear analysis (NLA) of ECG in predicting the results of invasive electrophysiologic study (EPS) in patients with ventricular arrhythmias. METHODS: We evaluated 25 patients with history of cardiac arrest, syncope, sustained, or nonsustained ventricular tachycardia (VT). All patients underwent electrophysiologic study (EPS) and nonlinear analysis (NLA) of ECG. The study group was compared with a control group of 25 healthy subjects, in order to define the normal range of NLA. ECG was processed in order to obtain numerical values, which were analyzed by nonlinear mathematical functions. Patients were classified through the application of a clustering procedure to the whole set of functions, and the correlation between the results of nonlinear analysis of ECG and EPS was tested. RESULTS: NLA assigned all patients with negative EPS to the same class of healthy subjects, whereas the patients in whom VT was inducible had been correctly and clearly isolated into a separate cluster. In our study, the result of NLA with application of the clustering technique was significantly correlated to that of EPS (P < 0.001), and was able to predict the result of EPS, with a negative predictive value of 100% and a positive predictive value of 100%. CONCLUSIONS: NLA can predict the results of EPS with good negative and positive predictive value. However, further studies are needed in order to verify the usefulness of this noninvasive tool for sudden death risk stratification in patients with ventricular arrhythmias.
INTRODUCTION: The aim of our study was to assess the effectiveness of the nonlinear analysis (NLA) of ECG in predicting the results of invasive electrophysiologic study (EPS) in patients with ventricular arrhythmias. METHODS: We evaluated 25 patients with history of cardiac arrest, syncope, sustained, or nonsustained ventricular tachycardia (VT). All patients underwent electrophysiologic study (EPS) and nonlinear analysis (NLA) of ECG. The study group was compared with a control group of 25 healthy subjects, in order to define the normal range of NLA. ECG was processed in order to obtain numerical values, which were analyzed by nonlinear mathematical functions. Patients were classified through the application of a clustering procedure to the whole set of functions, and the correlation between the results of nonlinear analysis of ECG and EPS was tested. RESULTS: NLA assigned all patients with negative EPS to the same class of healthy subjects, whereas the patients in whom VT was inducible had been correctly and clearly isolated into a separate cluster. In our study, the result of NLA with application of the clustering technique was significantly correlated to that of EPS (P < 0.001), and was able to predict the result of EPS, with a negative predictive value of 100% and a positive predictive value of 100%. CONCLUSIONS: NLA can predict the results of EPS with good negative and positive predictive value. However, further studies are needed in order to verify the usefulness of this noninvasive tool for sudden death risk stratification in patients with ventricular arrhythmias.
Authors: Douglas P Zipes; A John Camm; Martin Borggrefe; Alfred E Buxton; Bernard Chaitman; Martin Fromer; Gabriel Gregoratos; George Klein; Arthur J Moss; Robert J Myerburg; Silvia G Priori; Miguel A Quinones; Dan M Roden; Michael J Silka; Cynthia Tracy; Jean-Jacques Blanc; Andrzej Budaj; Veronica Dean; Jaap W Deckers; Catherine Despres; Kenneth Dickstein; John Lekakis; Keith McGregor; Marco Metra; Joao Morais; Ady Osterspey; Juan Luis Tamargo; José Luis Zamorano; Sidney C Smith; Alice K Jacobs; Cynthia D Adams; Elliott M Antman; Jeffrey L Anderson; Sharon A Hunt; Jonathan L Halperin; Rick Nishimura; Joseph P Ornato; Richard L Page; Barbara Riegel Journal: Eur Heart J Date: 2006-09 Impact factor: 29.983
Authors: Zhong-Kai Wu; Saila Vikman; Jari Laurikka; Erkki Pehkonen; Tiina Iivainen; Heikki V Huikuri; Matti R Tarkka Journal: Eur J Cardiothorac Surg Date: 2005-04-08 Impact factor: 4.191
Authors: Francesco Furlanello; Giorgio Galanti; Paolo Manetti; Andrea Capalbo; Nicola Pucci; Antonio Michelucci; Daniele Marangoni; Francesco Terrasi; Giacinto Pettinati; Riccardo Cappato Journal: Ann Noninvasive Electrocardiol Date: 2004-07 Impact factor: 1.468
Authors: Daniel E Vigo; Leonardo Nicola Siri; M Soledad Ladrón De Guevara; José A Martínez-Martínez; Rodolfo D Fahrer; Daniel P Cardinali; Osvaldo Masoli; Salvador M Guinjoan Journal: Am J Cardiol Date: 2004-03-15 Impact factor: 2.778