Principal Component Analysis of the T Wave in Patients with Chest Pain and Conduction Disturbances

There is a need for markers reflecting the increased risk in patients with conduction disturbances. Conduction disturbances presumably cause inhomogeneous repolarization that may create an arrhythmogenic substrate. In patients with normal conduction, parameters derived from principal components analysis (PCA) of the T wave contain prognostic information. The nondipolar PCA components are assumed to reflect repolarization inhomogeneity. This study examined the PCA parameters in relation to conduction disturbances. PCA was performed on continuously recorded 12‐lead ECGs in 800 patients with chest pain and nondiagnostic ECG on admission. The patients with conduction disturbance on admission were classified into separate groups and related to comparison groups without conduction disturbance recruited from the same series. For each patient, the dipolar and nondipolar components were quantified by medians of the ratio of the two largest eigenvalues (S2/S1 Median), the residue that summarizes the eigenvalues S4–S8 (TWRabsMedian) and the ratio of this residue to the total power of the T wave (TWRrelMedian). The parameters were assessed with respect to common clinical and ECG parameters, discharge diagnosis, and total mortality during a 35‐month follow‐up. TWRabsMedian increased with increasing conduction disturbance. In 135 patients with conduction disturbances, ROC curves for TWRabsMedian as indicator of mortality exhibited areas under a curve of 0.66, 0.65, and 0.56 at 6‐month, 24‐month, and 35‐month follow‐up. Conduction disturbances were associated with increased nondipolar PCA component and, thus, with increased repolarization inhomogeneity. The nondipolar PCA component contained a moderate amount of prognostic information not present in a simple ECG diagnosis of a conduction disturbance.

[1]  M. Malik,et al.  Spatial, temporal and wavefront direction characteristics of 12-lead T-wave morphology , 1999, Medical & Biological Engineering & Computing.

[2]  P. Arini,et al.  Role of Dipolar and Nondipolar Components of the T Wave in Determining the T Wave Residuum in an Isolated Rabbit Heart Model , 2004, Journal of cardiovascular electrophysiology.

[3]  B. Lindahl,et al.  QT dispersion measured by an automatic continuous method early in patients admitted for chest pain. , 2002, International journal of cardiology.

[4]  Pentti M Rautaharju,et al.  Why did QT dispersion die? , 2002, Cardiac electrophysiology review.

[5]  Wojciech Zareba,et al.  Repolarization Dynamics in Patients with Long QT Syndrome , 2002, Journal of cardiovascular electrophysiology.

[6]  Katerina Hnatkova,et al.  Analysis of T-Wave Morphology From the 12-Lead Electrocardiogram for Prediction of Long-Term Prognosis in Male US Veterans , 2002, Circulation.

[7]  Luigi Tavazzi,et al.  Left bundle-branch block is associated with increased 1-year sudden and total mortality rate in 5517 outpatients with congestive heart failure: a report from the Italian network on congestive heart failure. , 2002, American heart journal.

[8]  Richard B. Devereux,et al.  Principal Component Analysis of the T Wave and Prediction of Cardiovascular Mortality in American Indians: The Strong Heart Study , 2002, Circulation.

[9]  A. Siegbahn,et al.  Markers of myocardial damage and inflammation in relation to long-term mortality in unstable coronary artery disease. FRISC Study Group. Fragmin during Instability in Coronary Artery Disease. , 2000, The New England journal of medicine.

[10]  M Malik,et al.  Analysis of 12-Lead T-Wave Morphology for Risk Stratification After Myocardial Infarction , 2000, Circulation.

[11]  A J Camm,et al.  QT Dispersion Does Not Represent Electrocardiographic Interlead Heterogeneity of Ventricular Repolarization , 2000, Journal of cardiovascular electrophysiology.

[12]  B V Howard,et al.  Assessment of QT interval and QT dispersion for prediction of all-cause and cardiovascular mortality in American Indians: The Strong Heart Study. , 2000, Circulation.

[13]  L. Wallentin,et al.  ST-segment monitoring with continuous 12-lead ECG improves early risk stratification in patients with chest pain and ECG nondiagnostic of acute myocardial infarction. , 1999, Journal of the American College of Cardiology.

[14]  A. Hall,et al.  QT dispersion as a predictor of long-term mortality in patients with acute myocardial infarction and clinical evidence of heart failure. , 1999, European heart journal.

[15]  G. Herpen,et al.  QT dispersion as an attribute of T-loop morphology. , 1999, Circulation.

[16]  P W Macfarlane,et al.  Influence of lead selection and population on automated measurement of QT dispersion. , 1998, Circulation.

[17]  G Yi,et al.  T Wave Complexity in Patients with Hypertrophic Cardiomyopathy , 1998, Pacing and clinical electrophysiology : PACE.

[18]  A J Camm,et al.  Computerised measurements of QT dispersion in healthy subjects , 1998, Heart.

[19]  J. Camm,et al.  The prognostic value of the QT interval and QT interval dispersion in all-cause and cardiac mortality and morbidity in a population of Danish citizens. , 1998, European heart journal.

[20]  M Malik,et al.  Agreement and reproducibility of automatic versus manual measurement of QT interval and QT dispersion. , 1998, The American journal of cardiology.

[21]  A. Hofman,et al.  QTc dispersion predicts cardiac mortality in the elderly: the Rotterdam Study. , 1998, Circulation.

[22]  Q Xue,et al.  Algorithms for computerized QT analysis. , 1998, Journal of electrocardiology.

[23]  C Ceriotti,et al.  Mapping of ventricular repolarization potentials in patients with arrhythmogenic right ventricular dysplasia: principal component analysis of the ST-T waves. , 1997, Circulation.

[24]  S. Priori,et al.  Evaluation of the spatial aspects of T-wave complexity in the long-QT syndrome. , 1997, Circulation.

[25]  M. Viitasalo,et al.  QT dispersion as a risk factor for sudden cardiac death and fatal myocardial infarction in a coronary risk population. , 1997, Heart.

[26]  M. Fishbein,et al.  Anisotropic repolarization in ventricular tissue. , 1997, The American journal of physiology.

[27]  K. Szydło,et al.  Dispersion of the QT Interval as a Predictor of Cardiac Death in Patients with Coronary Heart Disease , 1996, Pacing and clinical electrophysiology : PACE.

[28]  S. Priori,et al.  Principal component analysis identifies abnormal complexity of repolarization in post myocardial infarction patients , 1996 .

[29]  M. Rosenqvist,et al.  Diagnostic value of programmed ventricular stimulation in patients with bifascicular block: a prospective study of patients with and without syncope. , 1995, Journal of the American College of Cardiology.

[30]  K. Harumi,et al.  Dipolarity of the T wave. , 1986, Japanese heart journal.

[31]  T. Musha,et al.  Dipolarity and dipole location during QRS and T waves in normal men estimated from body surface potential distribution. , 1985, Japanese heart journal.

[32]  B. Surawicz,et al.  Characteristics and Possible Mechanism of Ventricular Arrhythmia Dependent on the Dispersion of Action Potential Durations , 1983, Circulation.

[33]  M. Spach,et al.  The nature of electrical propagation in cardiac muscle. , 1983, The American journal of physiology.

[34]  S. Rahimtoola,et al.  Natural history of "high-risk" bundle-branch block: final report of a prospective study. , 1982, The New England journal of medicine.

[35]  S. Swiryn,et al.  Significance of the HV Interval in 517 Patients with Chronic Bifascicular Block , 1980, Circulation.

[36]  The significance of T-loop change in Frank's lead exercise electrocardiography. , 1976, Japanese heart journal.

[37]  H. Zimmerman,et al.  Morphologic features of the vectorcardiographic T loop in arteriosclerotic heart disease. , 1969, The American journal of cardiology.

[38]  D A BRODY,et al.  Principal Factor Waveforms of the Thoracic QRS Complex , 1964, Circulation research.

[39]  A. C. Young,et al.  Factor Analysis of the Electrocardiogram: Test of Electrocardiographic Theory Normal Hearts , 1960, Circulation research.