The R″ wave in V1 and the negative terminal QRS vector in aVF combine to a novel 12-lead ECG algorithm to identify slow conducting anatomical isthmus 3 in patients with tetralogy of Fallot.

AIMS: Patients with repaired tetralogy of Fallot (rTOF) have an increased risk of ventricular tachycardia (VT), with slow conducting anatomical isthmus (SCAI) 3 as dominant VT substrate. In patients with right bundle branch block (RBBB), SCAI 3 leads to local activation delay with a shift of terminal RV activation towards the lateral RV outflow tract which may be detected by terminal QRS vector changes on sinus rhythm electrocardiogram (ECG). METHODS AND RESULTS: Consecutive rTOF patients aged ≥16 years with RBBB who underwent electroanatomical mapping at our institution between 2017-2022 and 2010-2016 comprised the derivation and validation cohort, respectively. Forty-six patients were included in the derivation cohort (aged 40±15 years, QRS duration 165±23 ms). Among patients with SCAI 3 (n = 31, 67%), 17 (55%) had an R″ in V1, 18 (58%) had a negative terminal QRS portion (NTP) ≥80 ms in aVF, and 12 (39%) had both ECG characteristics, compared to only 1 (7%), 1 (7%), and 0 patient without SCAI, respectively.Combining R″ in V1 and/or NTP ≥80 ms in aVF into a diagnostic algorithm resulted in a sensitivity of 74% and specificity of 87% in detecting SCAI 3. The inter-observer agreement for the diagnostic algorithm was 0.875. In the validation cohort [n = 33, 18 (55%) with SCAI 3], the diagnostic algorithm had a sensitivity of 83% and specificity of 80% for identifying SCAI 3. CONCLUSION: A sinus rhythm ECG-based algorithm including R″ in V1 and/or NTP ≥80 ms in aVF can identify rTOF patients with a SCAI 3 and may contribute to non-invasive risk stratification for VT.

An initial exploration of subtraction electrocardiography to detect myocardial ischemia in the prehospital setting.

BACKGROUND: In the prehospital triage of patients presenting with symptoms suggestive of acute myocardial ischemia, reliable myocardial ischemia detection in the electrocardiogram (ECG) is pivotal. Due to large interindividual variability and overlap between ischemic and nonischemic ECG-patterns, incorporation of a previous elective (reference) ECG may improve accuracy. The aim of the current study was to explore the potential value of serial ECG analysis using subtraction electrocardiography. METHODS: SUBTRACT is a multicenter retrospective observational study, including patients who were prehospitally evaluated for acute myocardial ischemia. For each patient, an elective previously recorded reference ECG was subtracted from the ambulance ECG. Patients were classified as myocardial ischemia cases or controls, based on the in-hospital diagnosis. The diagnostic performance of subtraction electrocardiography was tested using logistic regression of 28 variables describing the differences between the reference and ambulance ECGs. The Uni-G ECG Analysis Program was used for state-of-the-art single-ECG interpretation of the ambulance ECG. RESULTS: In 1,229 patients, the mean area-under-the-curve of subtraction electrocardiography was 0.80 (95%CI: 0.77-0.82). The performance of our new method was comparable to single-ECG analysis using the Uni-G algorithm: sensitivities were 66% versus 67% (p-value > .05), respectively; specificities were 80% versus 81% (p-value > .05), respectively. CONCLUSIONS: In our initial exploration, the diagnostic performance of subtraction electrocardiography for the detection of acute myocardial ischemia proved equal to that of state-of-the-art automated single-ECG analysis by the Uni-G algorithm. Possibly, refinement of both algorithms, or even integration of the two, could surpass current electrocardiographic myocardial ischemia detection.

Serial electrocardiography to detect newly emerging or aggravating cardiac pathology: a deep-learning approach.

BACKGROUND: Serial electrocardiography aims to contribute to electrocardiogram (ECG) diagnosis by comparing the ECG under consideration with a previously made ECG in the same individual. Here, we present a novel algorithm to construct dedicated deep-learning neural networks (NNs) that are specialized in detecting newly emerging or aggravating existing cardiac pathology in serial ECGs. METHODS: We developed a novel deep-learning method for serial ECG analysis and tested its performance in detection of heart failure in post-infarction patients, and in the detection of ischemia in patients who underwent elective percutaneous coronary intervention. Core of the method is the repeated structuring and learning procedure that, when fed with 13 serial ECG difference features (intra-individual differences in: QRS duration; QT interval; QRS maximum; T-wave maximum; QRS integral; T-wave integral; QRS complexity; T-wave complexity; ventricular gradient; QRS-T spatial angle; heart rate; J-point amplitude; and T-wave symmetry), dynamically creates a NN of at most three hidden layers. An optimization process reduces the possibility of obtaining an inefficient NN due to adverse initialization. RESULTS: Application of our method to the two clinical ECG databases yielded 3-layer NN architectures, both showing high testing performances (areas under the receiver operating curves were 84% and 83%, respectively). CONCLUSIONS: Our method was successful in two different clinical serial ECG applications. Further studies will investigate if other problem-specific NNs can successfully be constructed, and even if it will be possible to construct a universal NN to detect any pathologic ECG change.

Normal values of the ventricular gradient and QRS-T angle, derived from the pediatric electrocardiogram.

BACKGROUND: Normal values of the mathematically-synthesized vectorcardiogram (VCG) are lacking for children. Therefore, the objective of this study was to assess normal values of the pediatric synthesized VCG (spatial QRS-T angle [SA] and ventricular gradient [VG]). METHODS: Electrocardiograms (ECGs) of 1263 subjects (0-24 years) with a normal heart were retrospectively selected. VCGs were synthesized by the Kors matrix. Normal values (presented as 2nd and 98th percentiles) were assessed by quantile regression with smoothing by splines. RESULTS: Our results show that heart rate decreased over age, QRS duration increased and QTc interval remained constant. The SA initially decreased and increased again from the age of 8 years. The VG magnitude was relatively stable until the age of 2 years, after which it increased. CONCLUSION: Normal values of the pediatric ECG and VCG (VG and SA) were established. These normal values could be important for future studies using VG and SA for risk stratification in heart disease in children.

The Olson method for detection of acute myocardial ischemia in patients with coronary occlusion.

An automated ECG-based method may provide diagnostic support in the management of patients with acute coronary syndrome. The Olson method has previously proved to accurately identify the culprit artery in patients with acute coronary occlusion. METHODS: The Olson method was applied to 360 patients without acute myocardial ischemia and 52 patients with acute coronary occlusion. RESULTS: This study establishes the normal variation of the Olson wall scores in patients without acute myocardial ischemia, which provides the basis for implementation of the Olson method for triage of patients with acute coronary syndrome. All patients with acute occlusion had Olson wall scores above the upper limit of normal. CONCLUSION: The Olson method can be used for ischemia detection with very high sensitivity. Future studies are needed to explore specificity in patients with non-ischemic ST elevation.

Position of ST-deviation measurements relative to the J-point: Impact for ischemia detection.

BACKGROUND: There is no consensus about the time instant relative to the J point where ST deviation has to be measured for detection of acute ischemia in the ECG. METHODS: We analyzed 53 ECGs, recorded preceding emergency catheterization of acute coronary syndrome patients with a completely occluded culprit artery (cases), and 88 control ECGs recorded in the cardiology outpatient clinic. ECG-amplitude measurements were made every 10 ms, between 20 ms before till 80 ms after the J point. STEMI-detection algorithms varied from the traditional STEMI criterion (elevations in at least two adjacent ECG leads), via the STEMI equivalent criterion (depressions in V2 and V3), to the most liberal STEMI-detection algorithm in which elevations as well as depressions in two adjacent leads were considered as signs of ischemia. RESULTS: Diagnostic accuracy was highest (93.6%) for the most liberal STEMI-detection algorithm at 10 ms after the J point; sensitivity was 94.3% and specificity was 93.2%. CONCLUSION: The results of our study suggest that STEMI detection close to the J point is optimal.

Heart Rate-Dependent Hysteresis of T-Wave Alternans in Primary Prevention ICD Patients.

BACKGROUND: T-wave alternans (TWA) is usually performed at accelerated heart rates (HR) during exercise, while recovery TWA is typically not analyzed. Consequently, it is still unknown if TWA shows a HR-dependent hysteresis or not. Thus, the aim of the present study was to investigate TWA dependency on HR during both the exercise and recovery phases of an ergometer test, and to evaluate if recovery TWA may contribute to identify subjects at increased risk of arrhythmic events. METHODS: Our HR adaptive match filter was used to identify TWA from electrocardiographic recordings acquired during a bicycle ergometer test in 266 patients with implanted cardio-defibrillator. During the 4-year follow-up, 76 patients developed tachycardia or ventricular fibrillation (ICD_Cases) and 190 did not (ICD_Controls). RESULTS: TWA was statistically lower during exercise than recovery for HRs between 75 and 110 bpm (16-21 µV vs 20-27 µV; P < 0.05), and reverse for HRs between 120 and 130 bpm (41-51 µV vs 28 µV; P < 0.05). ICD_Cases and ICD_Controls showed significantly different TWA at 80 bpm (20 µV vs 15 µV; P < 0.05) and 140 bpm (15 µV vs 22 µV; P < 0.05) during exercise, and at 90 bpm (38 µV vs 21 µV; P < 0.05) and 95 bpm (33-24 µV vs 28 µV; P < 0.05) during recovery. CONCLUSIONS: TWA shows a HR-dependent hysteresis and there is a different behavior of TWA in ICD_Cases and ICD_Controls groups. Consequently, beside exercise TWA also recovery TWA may contribute to identify subjects at increased risk of arrhythmic events.

Predictive Power of f99 Repolarization Index for the Occurrence of Ventricular Arrhythmias.

BACKGROUND: Defects of cardiac repolarization, noninvasively identifiable by analyzing the electrocardiographic (ECG) ST segment and T wave, are among the major causes of sudden cardiac death. Still, no repolarization-based index has so far shown sufficient sensitivity and specificity to justify preventive treatments. Thus, the aim of this work was to evaluate the predictive power of our recently proposed f99 index for the occurrence of ventricular arrhythmias. METHODS: Our study populations included 170 patients with implanted cardiac defibrillator (ICD), 44 of which developed ventricular tachycardia and/or fibrillation during the 4-year follow-up (ICD_Cases) and 126 did not (ICD_Controls). The f99 index, defined as the frequency at which the repolarization normalized cumulative energy reaches 99%, was computed in each of the 15 (I to III, aVl, aVr, aVf, V1 -V6 , X, Y, Z) available ECG leads independently, and then maximized over the 6 precordial leads (f99_MaxV1 -V6 ), 12 standard leads (f99_Max12STD) and three orthogonal leads (f99_MaxXYZ) to avoid dispersion-related issues. Each index predictive power was quantified as the area under the receiving operating characteristic curve (AUC). RESULTS: Median f99_MaxV1 -V6 , f99_Max12STD and f99_MaxXYZ values were significantly higher in the ICD_Cases than in the ICD_Controls (48 Hz vs. 35 Hz, P<0.05; 51 Hz vs. 43 Hz, P<0.05; 45 Hz vs. 31 Hz, P<10(-3) ; respectively), indicating a more fragmented repolarization in the former group. The AUC values were 0.62, 0.63 and 0.68, respectively. CONCLUSIONS: The f99 represents a promising risk index for the occurrence of ventricular arrhythmias, especially when maximized over the three orthogonal leads.

Subtraction electrocardiography: Detection of ischemia-induced ST displacement without the need to identify the J point.

BACKGROUND: When triaging a patient with acute chest pain at first medical contact, an electrocardiogram (ECG) is routinely made and inspected for signs of myocardial ischemia. The guidelines recommend comparison of the acute and an earlier-made ECG, when available. No concrete recommendations for this comparison exist, neither is known how to handle J-point identification difficulties. Here we present a J-point independent method for such a comparison. METHODS: After conversion to vectorcardiograms, baseline and acute ischemic ECGs after 3minutes of balloon occlusion during elective PCI were compared in 81 patients of the STAFF III ECG database. Baseline vectorcardiograms were subtracted from ischemic vectorcardiograms using either the QRS onsets or the J points as synchronization instants, yielding vector magnitude difference signals, ΔH. Output variables for the J-point synchronized differences were ΔH at the actual J point and at 20, 40, 60 and 80ms thereafter. Output variables for the onset-QRS synchronized differences were the ΔH at 80, 100, 120, 140 and 160ms after onset QRS. Finally, linear regressions of all combinations of ΔHJ+… versus ΔHQRS+… were made, and the best combination was identified. RESULTS: The highest correlation, 0.93 (p<0.01), was found between ΔH 40ms after the J point and 160ms after the onset of the QRS complex. With a ΔH ischemia threshold of 0.05mV, 66/81 (J-point synchronized differences) and 68/81 (onset-QRS synchronized differences) subjects were above the ischemia threshold, corresponding to sensitivities of 81% and 84%, respectively. CONCLUSION: Our current study opens an alternative way to detect cardiac ischemia without the need for human expertise for determination of the J point by measuring the difference vector magnitude at 160ms after the onset of the QRS complex.

Dependency of exercise-induced T-wave alternans predictive power for the occurrence of ventricular arrhythmias from heart rate.

BACKGROUND: T-wave alternans (TWA) is a noninvasive index of risk for the occurrence of ventricular arrhythmias. It is known that TWA amplitude (TWAA) increases with heart rate (HR) but how the TWA predictive power varies with HR remains unknown. Thus, the aim of this study was to evaluate the dependency of exercise-induced TWA predictive power for the occurrence of ventricular arrhythmias from HR. METHODS: TWA was identified using our HR adaptive match filter in exercise ECGs from 248 patients with implanted cardiac defibrillator (ICD), of which 72 developed ventricular tachycardia and/or fibrillation during the 4 year follow-up (ICD_Cases) and 176 did not (ICD_Controls). TWA predictive power was evaluated at HRs from 80 to 120 bpm by computing the area under the receiver operating characteristic curve (AUC) obtained using the maximum TWAA (maxTWAA) and the TWAA ratio (TWAAratio; i.e., the ratio between TWAA at a specific HR and at 80 bpm). RESULTS: TWAA increased with HR. At 80 bpm maxTWAA was lower than at 120 bpm in both ICD_Cases (22 µV vs 41 µV; P < 10(-2) ) and ICD_ Controls (16 µV vs 36 µV; P < 10(-4) ). However, only at 80 bpm ICD_Cases showed significantly higher maxTWAA than ICD_Controls (AUC = 0.6486; P = 0.0080). TWAAratio was higher in ICD_Controls than ICD_Cases for all HR but 120 bpm, and its predictive power was maximum at 115 bpm (AUC = 0.6914; P < 0.05). CONCLUSIONS: Exercise-induced TWA predictive power for the occurrence of ventricular arrhythmias, quantified using both maxTWAA and TWAAratio, was higher at low rather than at high HR.

Vectorcardiographic diagnostic & prognostic information derived from the 12-lead electrocardiogram: Historical review and clinical perspective.

In the course of time, electrocardiography has assumed several modalities with varying electrode numbers, electrode positions and lead systems. 12-lead electrocardiography and 3-lead vectorcardiography have become particularly popular. These modalities developed in parallel through the mid-twentieth century. In the same time interval, the physical concepts underlying electrocardiography were defined and worked out. In particular, the vector concept (heart vector, lead vector, volume conductor) appeared to be essential to understanding the manifestations of electrical heart activity, both in the 12-lead electrocardiogram (ECG) and in the 3-lead vectorcardiogram (VCG). Not universally appreciated in the clinic, the vectorcardiogram, and with it the vector concept, went out of use. A revival of vectorcardiography started in the 90's, when VCGs were mathematically synthesized from standard 12-lead ECGs. This facilitated combined electrocardiography and vectorcardiography without the need for a special recording system. This paper gives an overview of these historical developments, elaborates on the vector concept and seeks to define where VCG analysis/interpretation can add diagnostic/prognostic value to conventional 12-lead ECG analysis.

Comparison of model-based and expert-rule based electrocardiographic identification of the culprit artery in patients with acute coronary syndrome.

BACKGROUND AND PURPOSE: Culprit coronary artery assessment in the triage ECG of patients with suspected acute coronary syndrome (ACS) is relevant a priori knowledge preceding percutaneous coronary intervention (PCI). We compared a model-based automated method (Olson method) with an expert-rule based method for the culprit artery assessment. METHODS: In each of the 53 patients who were admitted with the working diagnosis of suspected ACS, scheduled for emergent angiography with a view on revascularization as initial treatment and subsequently found to have an angiographically documented completely occluded culprit artery, culprit artery location was assessed in the preceding ECG by both the model-based Olson method and the expert-rule based method that considered either visual or computer-measured J-point amplitudes. ECG culprit artery estimations were compared with the angiographic culprit lesion locations. Proportions of correct classifications were compared by a Z test at the 5% significance level. RESULTS: The Olson method performed slightly, but not significantly, better, when the expert-rule based method used visual assessment of J-point amplitudes (88.7% versus 81.1% correct; P=0.28). However, the Olson method performed significantly better when the expert-rule based method used computer-measured J-point amplitudes (88.7% versus 71.7% correct; P<0.05). CONCLUSION: The automated model-based Olson method performed at least at the level of expert cardiologists using a manual rule-based method.

Intra-individual ECG changes over 25 years: How long can elective ECGs be used as reference for acute ischemia detection?

BACKGROUND: The guidelines advocate, in patients with chest pain, comparison of the acute ECG with a previously made, non-ischemic ECG that serves as a reference, to corroborate the working diagnosis of acute coronary syndrome (ACS). Our approach of this serial comparison is to compute the differences between the ST vectors at the J point and 60 ms thereafter (∆ST(J+0), ∆ST(J+60)) and between the ventricular gradient (VG) vectors (∆VG). In the current study, we investigate if reference ECGs remain valid in time. METHODS: We studied 6 elective non-ischemic ECGs (ECG0, ECG1, …, ECG5), 5 years apart, in 88 patients. Within each patient, serial comparisons were done 1) between all successive ECGs, and 2) between each of ECG1, ECG2, …, ECG5 and ECG0, computing, in addition to ∆ST(J+0), ∆ST(J+60) and ∆VG, the difference in heart rates, ∆HR. Additionally, relevant clinical events and the diagnoses associated with each ECG were collected. Linear regression was used to assess trends in ∆ST(J+0), ∆ST(J+60) and ∆VG; multiple linear regression was used to assess the influence of the clinical events and diagnoses on ∆ST(J+0), ∆ST(J+60) and ∆VG. RESULTS: There were no trends in the differences between successive ECGs. Positive trends were seen with increasing time lapses between ECGs: ∆ST(J+0), ∆ST(J+60) and ∆VG increased per year by 0.65 µV, 1.45 µV and 3.69 mV∙ms, respectively. Extrapolation to a time lapse of 0 yielded 50.92 µV, 36.63 µV and 20.91 mV∙ms for the short-term reproducibility of ∆ST(J+0), ∆ST(J+60) and ∆VG, respectively. Multiple linear regression revealed that clinical variables could explain only 10%, 17% and 13% of the variability in ∆ST(J+0), ∆ST(J+60) and ∆VG, respectively. CONCLUSION: With a view on ischemia detection thresholds in the order of magnitude of 58 µV for ∆ST and 26 mV·ms for ∆VG, our study suggests that it is important to have a recent ECG available for the detection of myocardial ischemia, as an "aged" ECG may have lost its validity as a reference.

Performance of ST and ventricular gradient difference vectors in electrocardiographic detection of acute myocardial ischemia.

INTRODUCTION: Serial analysis could improve ECG diagnosis of myocardial ischemia caused by acute coronary occlusion. METHODS: We analyzed ECG pairs of 84 cases and 398 controls. In case-patients, who underwent elective percutaneous coronary intervention, ischemic ECGs during balloon occlusion were compared with preceding non-ischemic ECGs. In control-patients, two elective non-ischemic ECGs were compared. In each ECG the ST vector at the J point and the ventricular gradient (VG) vector was computed, after which difference vectors ΔST and ΔVG were computed within patients. Finally, receiver operating characteristic analysis was done. RESULTS: Areas under the curve were 0.906 (P<0.001; CI 0.862-0.949; SE 0.022) for ΔST and 0.880 (P<0.001; CI 0.833-0.926; SE 0.024) for ΔVG. Sensitivity and specificity of conventional ST-elevation myocardial infarction (STEMI) criteria were 70.2% and 89.1%, respectively. At matched serial analysis specificity and STEMI specificity, serial analysis sensitivity was 78.6% for ΔST and 71.4% for ΔVG (not significantly different from STEMI sensitivity). At matched serial analysis sensitivity and STEMI sensitivity, serial analysis specificity was 96.5% for ΔST and 89.3% for ΔVG; ΔST and STEMI specificities differed significantly (P<0.001). CONCLUSION: Detection of acute myocardial ischemia by serial ECG analysis of ST and VG vectors has equal or even superior performance than the STEMI criteria. This concept should be further evaluated in triage ECGs of patients suspected from having acute myocardial ischemia.

Acute coronary syndrome with a totally occluded culprit artery: relation of the ST injury vector with ST-elevation and non-ST elevation ECGs.

BACKGROUND: In acute coronary syndrome (ACS), ST-segment elevation (STE), often associated with a completely occluded culprit artery, is an important ECG criterion for primary percutaneous coronary intervention (PCI). However, several studies showed that in ACS a completely occluded culprit artery can also occur with a non-ST-elevation (NSTE) ECG. In order to elucidate reasons for this discrepancy we examined ST injury vector orientation and magnitude in ACS patients with and without STE, all admitted for primary PCI and having a completely occluded culprit artery. METHODS: We studied the ECGs of 300 ACS patients (214/86 STE/NSTE; 228/72 single/multivessel disease) who had a completely occluded culprit artery during angiography prior to primary PCI. The J+60 injury vector orientation and magnitude were computed from Frank XYZ leads derived from the 10-s standard 12-lead ECG. RESULTS: Demographic and anthropomorphic characteristics of the STE and NSTE patients did not differ. STE patients had a higher rate of right coronary artery occlusions, and a lower rate of left circumflex occlusions than NSTE patients (43 vs. 31%, and 13 vs. 22%, respectively; P<0.05). Injury vector elevation and magnitude were larger in STE than in NSTE patients (32° ± 37° vs. 6° ± 39°, and 304 ± 145 µV vs. 134 ± 72 µV, respectively; P<0.0001). CONCLUSION: STE criteria favor certain injury vector directions and larger injury vector magnitudes. Obviously, several ACS patients with complete culprit artery occlusions requiring primary PCI do not fulfill these criteria. Our study suggests that STE-NSTE-based ACS stratification needs further enhancement.

Normal values of the electrocardiogram for ages 16-90 years.

INTRODUCTION: To establish an up-to-date and comprehensive set of normal values for the clinically current measurements in the adult ECG, covering all ages for both sexes. METHODS: The study population included 13,354 individuals, taken from four population studies in The Netherlands, ranging in age from 16 to 90 years (55% men) and cardiologically healthy by commonly accepted criteria. Standard 12-lead ECGs were available for all participants. The ECGs were processed by a well-validated computer program. Normal limits were taken as the 2nd and 98th percentiles of the measurement distribution per age group. RESULTS: Our study corroborates many findings of previous studies, but also provides more differentiated results, in particular for the older age groups. Age trends were apparent for the QTc interval, QRS axis, and indices of left ventricular hypertrophy. Amplitudes in the left precordial leads showed a substantial increase in the older age groups for women, but not for men. Sex-dependent differences were apparent for most ECG parameters. All results are available on the Website www.normalecg.org, both in tabular and in graphical format. CONCLUSIONS: We determined age- and sex-dependent normal values of the adult ECG. Our study distinguishes itself from other studies by the large size of the study population, comprising both sexes, the broad range of ages, and the exhaustive set of measurements. Our results emphasize that most diagnostic ECG criteria should be age- and sex-specific.

Intra-Individual Comparison of Sinus and Ectopic Beats Probing the Ventricular Gradient's Activation Dependence.

Wilson assumed that the ventricular gradient (VG) is independent of the ventricular activation order. This paradigm has often been refuted and was never convincingly corroborated. We sought to validate Wilson's concept by intra-individual comparison of the VG of sinus beats and ectopic beats, thus assessing the effects of both altered ventricular conduction (caused by the ectopic focus) and restitution (caused by ectopic prematurity). We studied standard diagnostic ECGs of 118 patients with accidental extrasystoles: normally conducted supraventricular ectopic beats (SN, N = 6) and aberrantly conducted supraventricular ectopic beats (SA, N = 20) or ventricular ectopic beats (V, N = 92). In each patient, we computed the VG vectors of the predominant beat, VGp→, of the ectopic beat, VGe→, and of the VG difference vector, ΔVGep→, and compared their sizes. VGe→ of the SA and V ectopic beats were significantly larger than VGp→ (53.7 ± 25.0 vs. 47.8 ± 24.6 mV∙ms, respectively; p < 0.001). ΔVGep→ were three times larger than the difference of VGe→ and VGp→ (19.94 ± 9.76 vs. 5.94 mV∙ms, respectively), demonstrating differences in the VGp→ and VGe→ spatial directions. The amount of ectopic prematurity was not correlated with ΔVGep→, although the larger VG difference vectors were observed for the more premature (<80%) extrasystoles. Electrical restitution properties and electrotonic interactions likely explain our findings. We conclude that the concept of a conduction-independent VG should be tested at equal heart rates and without including premature extrasystoles.

Comparison of standard versus orthogonal ECG leads for T-wave alternans identification.

T-wave alternans (TWA), an electrophysiologic phenomenon associated with ventricular arrhythmias, is usually detected from selected ECG leads. TWA amplitude measured in the 12-standard and the 3-orthogonal (vectorcardiographic) leads were compared here to identify which lead system yields a more adequate detection of TWA as a noninvasive marker for cardiac vulnerability to ventricular arrhythmias. Our adaptive match filter (AMF) was applied to exercise ECG tracings from 58 patients with an implanted cardiac defibrillator, 29 of which had ventricular tachycardia or fibrillation during follow-up (cases), while the remaining 29 were used as controls. Two kinds of TWA indexes were considered, the single-lead indexes, defined as the mean TWA amplitude over each lead (MTWAA), and lead-system indexes, defined as the mean and the maximum MTWAA values over the standard leads and over the orthogonal leads. Significantly (P < 0.05) higher TWA in the cases versus controls was identified only occasionally by the single-lead indexes (odds ratio: 1.0-9.9, sensitivity: 24-76%, specificity: 76-86%), and consistently by the lead-system indexes (odds ratio: 4.5-8.3, sensitivity: 57-72%, specificity: 76%). The latter indexes also showed a significant correlation (0.65-0.83) between standard and orthogonal leads. Hence, when using the AMF, TWA should be detected in all leads of a system to compute the lead-system indexes, which provide a more reliable TWA identification than single-lead indexes, and a better discrimination of patients at increased risk of cardiac instability. The standard and the orthogonal leads can be considered equivalent for TWA identification, so that TWA analysis can be limited to one-lead system.

Role of the vectorcardiogram-derived spatial QRS-T angle in diagnosing left ventricular hypertrophy.

INTRODUCTION: Current criteria for electrocardiographic (ECG) diagnosis of left ventricular hypertrophy (LVH) have a low diagnostic accuracy. Addition of demographic, anthropomorphic, and additional ECG variables may improve accuracy. As hypertrophy affects action potential morphology and intraventricular conduction, QRS prolongation and T-wave morphology may occur and become manifest in the vectorcardiographic variables spatial QRS-T angle (SA) and spatial ventricular gradient. In this study, we attempted to improve the diagnostic accuracy for LVH by using a combination of demographic, anthropomorphic, ECG, and vectorcardiographic variables. METHODS: The study group (n = 196) was divided in 4 subgroups with, on one hand, echocardiographically diagnosed LVH or a normal echocardiogram and, on the other hand, with any of the conventional ECG signs for LVH or with normal ECGs. Each subgroup was randomly split into halves, yielding 2 equally-sized (n = 98) data sets A and B. Age, sex, height, weight, body mass index, body surface area (BSA), frontal QRS axis, QRS duration, QT duration, maximal QRS vector magnitude, SA, and ventricular gradient magnitude and orientation were univariate studied by receiver operating characteristic analysis and were used to build a stepwise linear discriminant model using P < .05 as entry and P > .10 as removal criterion. The discriminant model was built in set A (model A) and tested on set B. Stability checks were done by building a discriminant model on set B and testing on set A and by cross-validation analysis in the complete study group. RESULTS: The discriminant model equation was D = 5.130 × BSA - 0.014 × SA - 8.74, wherein D greater than or equal to 0 predicts a normal echocardiogram and D less than 0 predicts LVH. The diagnostic accuracy (79%) was better than the diagnostic accuracy of conventional ECG criteria for LVH (57%). CONCLUSION: The combination of BSA and SA yields a diagnostic accuracy of LVH that is superior to that of the conventional ECG criteria.