Context-independent identification of myocardial ischemia in the prehospital ECG of chest pain patients.

Non-traumatic chest pain is a frequent reason for an urgent ambulance visit of a patient by the emergency medical services (EMS). Chest pain (or chest pain-equivalent symptoms) can be innocent, but it can also signal an acute form of severe pathology that may require prompt intervention. One of these pathologies is cardiac ischemia, resulting from a disbalance between blood supply and demand. One cause of a diminished blood supply to the heart is acute coronary syndrome (ACS, i.e., cardiac ischemia caused by a reduced blood supply to myocardial tissue due to plaque instability and thrombus formation in a coronary artery). ACS is dangerous due to the unpredictable process that drives the supply problem and the high chance of fast hemodynamic deterioration (i.e., cardiogenic shock, ventricular fibrillation). This is why an ECG is made at first medical contact in most chest pain patients to include or exclude ischemia as the cause of their complaints. For speedy and adequate triaging and treatment, immediate assessment of this prehospital ECG is necessary, still during the ambulance ride. Human diagnostic efforts supported by automated interpretation algorithms seek to answer questions regarding the urgency level, the decision if and towards which healthcare facility the patient should be transported, and the indicated acute treatment and further diagnostics after arrival in the healthcare facility. In the case of an ACS, a catheter intervention room may be activated during the ambulance ride to facilitate the earliest possible in-hospital treatment. Prehospital ECG assessment and the subsequent triaging decisions are complex because chest pain is not uniquely associated with ACS. The differential diagnosis includes other cardiac, pulmonary, vascular, gastrointestinal, orthopedic, and psychological conditions. Some of these conditions may also involve ECG abnormalities. In practice, only a limited fraction (order of magnitude 10%) of the patients who are urgently transported to the hospital because of chest pain are ACS patients. Given the relatively low prevalence of ACS in this patient mix, the specificity of the diagnostic ECG algorithms should be relatively high to prevent overtreatment and overflow of intervention facilities. On the other hand, only a sufficiently high sensitivity warrants adequate therapy when needed. Here, we review how the prehospital ECG can contribute to identifying the presence of myocardial ischemia in chest pain patients. We discuss the various mechanisms of myocardial ischemia and infarction, the typical patient mix of chest pain patients, the shortcomings of the ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) ECG criteria to detect a completely occluded culprit artery, the OMI ECG criteria (including the STEMI-equivalent ECG patterns) in detecting completely occluded culprit arteries, and the promise of neural networks in recognizing ECG patterns that represent complete occlusions. We also discuss the relevance of detecting any ACS/ischemia, not necessarily caused by a total occlusion, in the prehospital ECG. In addition, we discuss how serial prehospital ECGs can contribute to ischemia diagnosis. Finally, we discuss the diagnostic contribution of a serial comparison of the prehospital ECG with a previously made nonischemic ECG of the patient.

Post hoc labeling an acute ECG as ischemic or non-ischemic based on clinical data: A necessary challenge.

The ECG is crucial in the prehospital (and early inhospital) phase of patients with symptoms suggestive of myocardial ischemia. Therefore, new algorithms for ECG-based myocardial ischemia detection are continuously being researched. Development and validation of these algorithms require a database of acute ECGs (from the prehospital or emergency department setting) including a representative mix of cases (ischemia present) and controls (no ischemia present). Therefore, for every patient in this mix, the "truth" regarding the actual presence or absence of myocardial ischemia during the recording of the acute ECG has to be determined to compare the newly developed algorithm against. This post hoc adjudication process of determining whether an acute (either prehospitally acquired or acquired in the emergency department) ECG was made under ischemic conditions should use all available clinical data (the clinical diagnosis, cardiac imaging data, and laboratory values) of the subsequent patient's admission. Even with all data at hand, post hoc labeling a patient and their acute ECG as a myocardial ischemia case or control cannot be forced into a binary division between definite cases and definite controls. More specifically, to be used for the development of a new algorithm, the patients' ECG has to be scored for the presence or absence of myocardial ischemia at the exact moment of its recording, which renders the classification even more difficult. For instance, even though it may be plausible that myocardial ischemia was present at a given moment during the patient's admission, this is not necessarily proof that the prehospital (or early inhospital) ECG was also made in ischemic conditions: ischemia can be a fluctuating process (as is, e.g., the case in unstable angina pectoris). Therefore, post hoc classification of an acute ECG in terms of the absence or presence of ischemia requires a multipoint scale ranging between definite ischemic to definite non-ischemic, for instance using a 5-point scale (presumed non-ischemic, probably non-ischemic, uncertain, probably ischemic, presumed ischemic). To summarize, the post hoc adjudication process of ECGs of ambulance (and emergency department) patients cannot result in a binary division into definite cases and controls (i.e., patients with or without myocardial ischemia during the recording of the acute ECG), as myocardial ischemia is often dynamic rather than constant. ECGs could be labeled on a multi-point scale, in which the label represents the probability of the actual presence (or absence) of myocardial ischemia at the exact moment of the recording of that ECG. Further development of algorithms for myocardial ischemia detection should consider this concept.

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.

Artificial Neural Network for Atrial Fibrillation Identification in Portable Devices.

Atrial fibrillation (AF) is a common cardiac disorder that can cause severe complications. AF diagnosis is typically based on the electrocardiogram (ECG) evaluation in hospitals or in clinical facilities. The aim of the present work is to propose a new artificial neural network for reliable AF identification in ECGs acquired through portable devices. A supervised fully connected artificial neural network (RSL_ANN), receiving 19 ECG features (11 morphological, 4 on F waves and 4 on heart-rate variability (HRV)) in input and discriminating between AF and non-AF classes in output, was created using the repeated structuring and learning (RSL) procedure. RSL_ANN was created and tested on 8028 (training: 4493; validation: 1125; testing: 2410) annotated ECGs belonging to the "AF Classification from a Short Single Lead ECG Recording" database and acquired with the portable KARDIA device by AliveCor. RSL_ANN performance was evaluated in terms of area under the curve (AUC) and confidence intervals (CIs) of the received operating characteristic. RSL_ANN performance was very good and very similar in training, validation and testing datasets. AUC was 91.1% (CI: 89.1-93.0%), 90.2% (CI: 86.2-94.3%) and 90.8% (CI: 88.1-93.5%) for the training, validation and testing datasets, respectively. Thus, RSL_ANN is a promising tool for reliable identification of AF in ECGs acquired by portable devices.

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.

Prognostic relevance of the interaction between short-term, metronome-paced heart rate variability, and inflammation: results from the population-based CARLA cohort study.

AIMS: To determine the interaction between HRV and inflammation and their association with cardiovascular/all-cause mortality in the general population. METHODS AND RESULTS: Subjects of the CARLA study (n = 1671; 778 women, 893 men, 45-83 years of age) were observed for an average follow-up period of 8.8 years (226 deaths, 70 cardiovascular deaths). Heart rate variability parameters were calculated from 5-min segments of 20-min resting electrocardiograms. High-sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), and soluble tumour necrosis factor-alpha receptor type 1 (sTNF-R1) were measured as inflammation parameters. The HRV parameters determined included the standard deviation of normal-to-normal intervals (SDNN), the root-mean-square of successive normal-interval differences (RMSSD), the low- and high-frequency (HF) power, the ratio of both, and non-linear parameters [Poincaré plot (SD1, SD2, SD1/SD2), short-term detrended fluctuation analysis]. We estimated hazard ratios by using covariate-adjusted Cox regression for cardiovascular and all-cause mortality incorporating an interaction term of HRV/inflammation parameters. Relative excess risk due to interactions (RERIs) were computed. We found an interaction effect of sTNF-R1 with SDNN (RERI: 0.5; 99% confidence interval (CI): 0.1-1.0), and a weaker effect with RMSSD (RERI: 0.4; 99% CI: 0.0-0.9) and HF (RERI: 0.4; 99% CI: 0.0-0.9) with respect to cardiovascular mortality on an additive scale after covariate adjustment. Neither IL-6 nor hsCRP showed a significant interaction with the HRV parameters. CONCLUSION: A change in TNF-α levels or the autonomic nervous system influences the mortality risk through both entities simultaneously. Thus, TNF-α and HRV need to be considered when predicating mortality.

Longitudinal association of short-term, metronome-paced heart rate variability and echocardiographically assessed cardiac structure at a 4-year follow-up: results from the prospective, population-based CARLA cohort.

AIMS: To assess the value of cardiac structure/function in predicting heart rate variability (HRV) and the possibly predictive value of HRV on cardiac parameters. METHODS AND RESULTS: Baseline and 4-year follow-up data from the population-based CARLA cohort were used (790 men, 646 women, aged 45-83 years at baseline and 50-87 years at follow-up). Echocardiographic and HRV recordings were performed at baseline and at follow-up. Linear regression models with a quadratic term were used. Crude and covariate adjusted estimates were calculated. Missing values were imputed by means of multiple imputation. Heart rate variability measures taken into account consisted of linear time and frequency domain [standard deviation of normal-to-normal intervals (SDNN), high-frequency power (HF), low-frequency power (LF), LF/HF ratio] and non-linear measures [detrended fluctuation analysis (DFA1), SD1, SD2, SD1/SD2 ratio]. Echocardiographic parameters considered were ventricular mass index, diastolic interventricular septum thickness, left ventricular diastolic dimension, left atrial dimension systolic (LADS), and ejection fraction (Teichholz). A negative quadratic relation between baseline LADS and change in SDNN and HF was observed. The maximum HF and SDNN change (an increase of roughly 0.02%) was predicted at LADS of 3.72 and 3.57 cm, respectively, while the majority of subjects experienced a decrease in HRV. There was no association between further echocardiographic parameters and change in HRV, and there was no evidence of a predictive value of HRV in the prediction of changes in cardiac structure. CONCLUSION: In the general population, LADS predicts 4-year alteration in SDNN and HF non-linearly. Because of the novelty of the result, analyses should be replicated in other populations.

Galen Wagner, M.D., Ph.D. (1939-2016) as international mentor of young investigators in electrocardiology.

This paper describes a substantial part of the international mentoring network of students and young investigators in electrocardiology that developed around Dr. Galen Wagner (1939-2016), including many experiences of his mentees and co-mentors. The paper is meant to stimulate thinking about international mentoring as a means to achieve important learning experiences and personal development of young investigators, to intensify international scientific cooperation, and to stimulate scientific production.

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.

Detection of elevated pulmonary pressures by the ECG-derived ventricular gradient: A comparison of conversion matrices in patients with suspected pulmonary hypertension.

BACKGROUND: The aim was to assess the diagnostic value of the Inverse Dower (INVD)-derived vectorcardiogram (VCG) and the Kors-derived VCG to detect elevated systolic pulmonary artery pressure (SPAP) in suspected pulmonary hypertension (PH). METHODS: In 132 patients, morphologic variables were evaluated by comparing the VCG parameters synthesized by INVD and Kors matrix. Comparison of the diagnostic accuracy of detecting SPAP ≥50mmHg between the matrices was performed by ROC curve analysis and logistic regression analysis. RESULTS: Most VCG parameters differed significantly between INVD and Kors. ROC analysis for detection of SPAP ≥50mmHg by VG projected on the X-axis demonstrated no difference (p=0.99) between INVD (AUC=0.80) and Kors (AUC=0.80). Both the INVD- and Kors-derived VCG provided significant diagnostic information on the presence of SPAP ≥50mmHg (INVD, OR 1.05, 95%CI 1.03-1.07; P<0.001; Kors, OR 1.05, 95%CI 1.03-1.08; P<0.001). CONCLUSION: Although there were significant differences in measures of vector morphology, both INVD- and Kors-derived VCG demonstrated equal clinical performance in case of elevated SPAP.

Association between autonomic nervous dysfunction and cellular inflammation in end-stage renal disease.

BACKGROUND: Alterations in autonomic nervous function are common in hemodialysis (HD) patients. Sympathetic as well as parasympathetic activation may be associated with immune and inflammatory responses. We intended to confirm a role of autonomous dysregulation for inflammation in HD patients. METHODS: 30 HD patients (including 15 diabetics) and 15 healthy controls were studied for heart rate variability (HRV) using 5 min ECG recordings. Heart rate variability was estimated by time-domain parameters (the standard deviation of the RR intervals (SDNN) and the percentage of pairs of adjacent RR intervals differing by >50 ms (pNN50)) and frequency-domain-analysis (high- and low-frequency variation of RR intervals, HF and LF). Inflammation was detected as serum C-reactive Protein (CRP), IL-6 and circulating monocyte subpopulation numbers. Immune cells were characterized by ACh receptor expression. RESULTS: Patients differed from controls in terms of age (68.0 [14.8] yrs vs. 58.0 [13.0] yrs, p < 0.001; Median [IQR]) and sex. However, HRV parameters were different in controls and HD patients (SDNN controls 34.0 [14.0] ms, HD patients 15.5 [14.8] ms, p < 0.01). This finding was not restricted to patients with diabetes mellitus (diab), although diabetes is an important cause of autonomous dysfunction (SDNN, diab 13.0 [14.0] ms, non-diab 18.0 [15.3] ms, p = 0.8). LF and HF were reduced by the same magnitude to 1/3 of those in controls. Patients suffered from chronic inflammation (CRP 9.4 [12.9] mg/l, controls 1.6 [2.4] mg/l, p < 0.001) and expanded proinflammatory monocyte subpopulations (CD14++/CD16+ cells: patients 41 [27]/µl, controls 24 [18]/µl, p < 0.01). ECG parameters did not correlate with inflammation in patients, but monocyte ACh receptor expression was enhanced, indicating potentially elevated responsiveness of this cell type to parasympathetic regulation. CONCLUSIONS: HD patients have strongly impaired HRV. Chronic inflammation is not related to autonomous dysfunction, although monocytes express the ACh receptor at enhanced density making them potentially more sensitive to parasympathetic effects. TRIAL REGISTRATION: This study was listed with ClinicalTrials.gov ( NCT00878033 ).

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.

Scientific STAFF and MALT meetings - past, present, and future.

The scientific STAFF and MALT meetings were created around the turn of the century for scientists engaged in enhancing the role of the 12-lead ECG for detection and quantification of involved myocardium in patients with acute coronary syndrome. These meetings were initially focused on computer processing of data from two single-center databases. The STAFF database was collected in the mid-nineties on patients with prolonged total coronary occlusion; high-resolution 12-lead ECGs were collected before, during, and after 5 minutes of occlusion. The MALT database was created in the early years of this century on consecutive patients with chest pain admitted to a large teaching hospital. Delayed enhancement magnetic resonance imaging and electrocardiograms were recorded in these acutely ill patients. The paper highlights the first 2 decades of the STAFF and MALT meetings and details the meeting format.

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.

Mechanisms of exercise-recovery hysteresis in the ECG: ISCE 2015 paper.

This paper gives an overview of multiple factors, like the mechanisms governing rate adaptation of ventricular action potentials and autonomic mechanisms, which play a role in the genesis of exercise-recovery hysteresis in the ECG. It also discusses the possible association between exercise-recovery ECG hysteresis and arrhythmogeneity.

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.