Hyperacute T Wave in the Early Diagnosis of Acute Myocardial Infarction.

STUDY OBJECTIVE: The diagnostic performance of T-wave amplitudes for the detection of myocardial infarction is largely unknown. We aimed to address this knowledge gap. METHODS: T-wave amplitudes were automatically measured in 12-lead ECGs of patients presenting with acute chest discomfort to the emergency department within a prospective diagnostic multicenter study. The final diagnosis was centrally adjudicated by 2 independent cardiologists. Patients with left ventricular hypertrophy, complete left bundle branch block, or paced ventricular depolarization were excluded. The performance for lead-specific 95th-percentile thresholds were reported as likelihood ratios (lr), specificity, and sensitivity. RESULTS: Myocardial infarction was the final diagnosis in 445 (18%) of 2457 patients. In most leads, T-wave amplitudes tended to be greater in patients without myocardial infarction than those with myocardial infarction, and T-wave amplitude exceeding the 95th percentile had positive and negative lr close to 1 or with confidence intervals (CIs) crossing 1. The exceptions were leads III, aVR, and V1, which had positive lrs of 3.8 (95% CI, 2.7 to 5.3), 4.3 (95% CI, 3.1 to 6.0) and 2.0 (95% CI, 1.4 to 2.9), respectively. These leads normally have inverted T waves, so T-wave amplitude exceeding the 95th percentile reflects upright rather than increased-amplitude hyperacute T waves. CONCLUSION: Hyperacute T waves, when defined as increased T-wave amplitude exceeding the 95th percentile, did not provide useful information in diagnosing myocardial infarction in this sample.

The ΔWaveECG: The differences to the normal 12­lead ECG amplitudes.

BACKGROUND: The QRS, ST segment, and T-wave waveforms of electrocardiogram are difficult to interpret, especially for non-ECG experts readers, like general practitioners. As the ECG waveforms are influenced by many factors, like body build, age, sex, electrode placement, even for experience ECG readers the waveform is difficult to interpret. In this research we have created a novel method to distinguish normal from abnormal ECG waveforms for an individual ECG based on the ECG amplitude distribution derived from normal standard 12­lead ECG recordings. AIM: Creation of a normal ECG amplitude distribution to enable the distinction by non-ECG experts of normal from abnormal waveforms of the standard 12­lead ECG. METHODS: The ECGs of healthy normal controls in the PTB-XL database were used to construct a normal amplitude distribution of the 12 lead ECG for males and females. All ECGs were resampled to have the same number of samples to enable the classification of an individual ECG as either normal or abnormal, i.e. within the normal amplitude distribution or outside, the ΔWaveECG. RESULTS: From the same PTB-XL database six ECG's were selected, normal, left and right bundle branch block, and three with a myocardial infarction. The normal ECG was obviously within the normal distribution, and all other five showed clear abnormal ECG amplitudes outside the normal distribution in any of the ECG segments (QRS, ST segment and remaining STT segment). CONCLUSION: The ΔWaveECG can distinguish the abnormal from normal ECG waveform segments, making the ECG easier to classify as normal or abnormal. Conduction disorders and ST changes due to ischemia and abnormal T-waves are effortless to detect, also by non-ECG expert readers, thus improving the early detection of cardiac patients.

Incremental value of high-frequency QRS analysis for diagnosis and prognosis in suspected exercise-induced myocardial ischaemia.

AIM: Exercise stress testing is used to detect myocardial ischaemia, but is limited by low sensitivity and specificity. The authors investigated the value of the analysis of high-frequency QRS components as a marker of abnormal depolarization in addition to standard ST-deviations as a marker of abnormal repolarization to improve the diagnostic accuracy. METHODS AND RESULTS: Consecutive patients undergoing bicycle exercise stress nuclear myocardial perfusion imaging were prospectively enrolled. Presence of myocardial ischaemia, the primary diagnostic endpoint, was adjudicated using MPI and coronary angiography. Automated high-frequency QRS analysis was performed in a blinded fashion. The prognostic endpoint was major adverse cardiac events (MACEs) during two years of follow-up. Exercise-induced ischaemia was detected in 147/662 patients (22%). The sensitivity of high-frequency QRS was similar to ST-deviations (46% vs. 43%, p=0.59), while the specificity was lower (75% vs. 87%, p<0.001). The combined use of high-frequency QRS and ST-deviations classified 59% of patients as 'rule-out' (both negative), 9% as 'rule-in' (both positive) and 32% in an intermediate zone (one test positive). The sensitivity for 'rule-out' and the specificity for 'rule-in' improved to 63% and 97% compared with ST-deviation analysis alone (both p<0.001). MACE-free survival was 90%, 80% and 42% in patients in the 'rule-out', intermediate and 'rule-in' groups (p<0.001). After adjustment for age, gender, ST-deviations and clinical post-test probability of ischaemia, high-frequency QRS remained an independent predictor for the occurrence of MACEs. CONCLUSION: The use of high-frequency QRS analysis in addition to ST-deviation analysis improves the diagnostic accuracy during exercise stress testing and adds independent prognostic information.

Man vs machine: Performance of manual vs automated electrocardiogram analysis for predicting the chamber of origin of idiopathic ventricular arrhythmia.

BACKGROUND: Radiofrequency catheter ablation of idiopathic ventricular arrhythmias (VAs) is performed to eliminate symptoms and to prevent or reverse arrhythmia-induced cardiomyopathy. Preprocedural prediction of the chamber of VA origin is critical for patient counseling, procedure planning, and guidance of invasive mapping. OBJECTIVE: We aimed to assess the performance of manual expert versus automated 12-lead electrocardiogram (ECG) analysis in the prediction of VA origin. METHODS: Patients with ablation of idiopathic VA and sustained success were included. The VA origin was defined as the site where ablation caused arrhythmia suppression. Standard baseline 12-lead ECGs with documentation of the VA were analyzed manually in a blinded fashion by three electrophysiologists and three electrophysiology (EP) fellows. In addition, the same standard 12-lead ECG was analyzed by an automated computer algorithm using a vectorcardiographic approach. RESULTS: Thirty-eight patients (median age, 47 [interquartile range, 37-58]; 68% female) were enrolled. The VA originated from the right ventricle in 24 (63%) and the left ventricle in 14 (37%) patients. The electrophysiologists and EP fellows identified the VA chamber of origin with a similar accuracy of 73% and 72% (P = .72). The automated algorithm showed a higher accuracy of 89% (P = .03 compared with electrophysiologists and EP fellows). This resulted in a sensitivity of 95% and specificity of 86%. CONCLUSION: While the manual ECG analysis of the standard 12-lead ECG by both electrophysiologists and EP fellows correctly identified the chamber of VA origin in around 75% of cases, an automated vectorcardiographic computer algorithm achieved an accuracy of 89% with clinically acceptable diagnostic parameters.

Prospective validation of current quantitative electrocardiographic criteria for ST-elevation myocardial infarction.

BACKGROUND: Rapid and reliable diagnosis of ST-elevation myocardial infarction (STEMI) as a surrogate for acute coronary occlusion is critical for early reperfusion therapy. OBJECTIVES: We aimed to examine the diagnostic performance of current guideline-recommended Electrocardiogram (ECG) STEMI criteria. METHODS: In a prospective diagnostic multicenter study, we objectively quantified the extent of ST-segment elevation in all ECG leads using an automated software-based analysis of the digital 12-lead-ECG in adult patients presenting to the emergency department (ED) with suspected myocardial infarction (MI). Classification according to current guideline-recommended ECG criteria for STEMI at ED presentation was compared against a final diagnosis adjudicated by two independent cardiologists after reviewing all available medical records including serial ECGs, cardiac imaging and coronary angiograms. RESULTS: Among 2486 patients, 52 (2%) were found to have significant ST-segment elevation on ECG at ED presentation according to current guideline-recommended ECG criteria for STEMI. Eighty-one (3%) patients received a final adjudicated diagnosis of STEMI. Only 35% (28 of 81) of all patients with a final diagnosis of STEMI were correctly identified (PPV 54% (95% CI 41-66%), sensitivity 35% (95% Cl 24-46%), NPV 97.8% (95% CI 97.5-98.1%). Four reasons for missing STEMIs emerged: timing (significant STE at an earlier/later time point) in 25%, incorrect measurement points in 30%, non or borderline-significant STE in 36% and inferoposterior MI localisation in 9%. CONCLUSIONS: A computerized analysis of current guideline-recommended ECG criteria for STEMI showed suboptimal diagnostic performance when applied to a single 12­lead ECG performed at ED presentation. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00470587.

Incremental diagnostic and prognostic value of the QRS-T angle, a 12-lead ECG marker quantifying heterogeneity of depolarization and repolarization, in patients with suspected non-ST-elevation myocardial infarction.

BACKGROUND: The value of the 12-lead ECG in the diagnosis of non-ST-elevation myocardial infarction (NSTEMI) is limited due to insufficient sensitivity and specificity of standard ECG criteria. The QRS-T angle reflects depolarization-repolarization heterogeneity and might assist in detecting patients with a NSTEMI (diagnosis) as well as predicting patients with an increased mortality risk (prognosis). METHODS: We prospectively enrolled 2705 consecutive patients with symptoms suggestive of NSTEMI. The QRS-T angle was automatically derived from the standard 10 s 12-lead ECG recorded at presentation to the ED. Patients were followed up for all-cause mortality for 2 years. RESULTS: NSTEMI was the final diagnosis in 15% (n = 412) of patients. QRS-T angles were significantly greater in patients with NSTEMI compared to those without (p < 0.001). The use of the QRS-T angle in addition to standard ECG criteria indicative of ischemia improved the diagnostic accuracy for NSTEMI as quantified by the area under the ROC curve from 0.68 to 0.72 (p < 0.001). An algorithm for the combined use of standard ECG criteria and the QRS-T angle improved the sensitivity of the ECG for NSTEMI from 45% to 78% and the specificity from 86% to 91% (p < 0.001 for both comparisons). The 2-year survival rates were 98%, 97% and 87% according to QRS-T angle tertiles (p < 0.001). CONCLUSION: In patients with suspected NSTEMI, the QRS-T angle derived from the standard 12-lead ECG provides incremental diagnostic accuracy on top of standard ECG criteria indicative of ischemia, and independently predicts all-cause mortality during 2 years of follow-up.

Automatically computed ECG algorithm for the quantification of myocardial scar and the prediction of mortality.

BACKGROUND: Myocardial scar is associated with adverse cardiac outcomes. The Selvester QRS-score was developed to estimate myocardial scar from the 12-lead ECG, but its manual calculation is difficult. An automatically computed QRS-score would allow identification of patients with myocardial scar and an increased risk of mortality. OBJECTIVES: To assess the diagnostic and prognostic value of the automatically computed QRS-score. METHODS: The diagnostic value of the QRS-score computed automatically from a standard digital 12-lead was prospectively assessed in 2742 patients with suspected myocardial ischemia referred for myocardial perfusion imaging (MPI). The prognostic value of the QRS-score was then prospectively tested in 1151 consecutive patients presenting to the emergency department (ED) with suspected acute heart failure (AHF). RESULTS: Overall, the QRS-score was significantly higher in patients with more extensive myocardial scar: the median QRS-score was 3 (IQR 2-5), 4 (IQR 2-6), and 7 (IQR 4-10) for patients with 0, 5-20 and > 20% myocardial scar as quantified by MPI (p < 0.001 for all pairwise comparisons). A QRS-score ≥ 9 (n = 284, 10%) predicted a large scar defined as > 20% of the LV with a specificity of 91% (95% CI 90-92%). Regarding clinical outcomes in patients presenting to the ED with symptoms suggestive of AHF, mortality after 1 year was 28% in patients with a QRS-score ≥ 3 as opposed to 20% in patients with a QRS-score < 3 (p = 0.001). CONCLUSIONS: The QRS-score can be computed automatically from the 12-lead ECG for simple, non-invasive and inexpensive detection and quantification of myocardial scar and for the prediction of mortality. TRIAL-REGISTRATION: http://www.clinicaltrials.gov . Identifier, NCT01838148 and NCT01831115.

Diagnostic and prognostic value of QRS duration and QTc interval in patients with suspected myocardial infarction.

BACKGROUND: While prolongation of QRS duration and QTc interval during acute myocardial infarction (AMI) has been reported in animals, limited data is available for these readily available electrocardiography (ECG) markers in humans. METHODS: Diagnostic and prognostic value of QRS duration and QTc interval in patients with suspected AMI in a prospective diagnostic multicentre study were prospectively assessed. Digital 12-lead ECGs were recorded at presentation. QRS duration and QTc interval were automatically calculated in a blinded fashion. Final diagnosis was adjudicated by two independent cardiologists. The prognostic endpoint was all-cause mortality during 24 months of follow-up. RESULTS: Among 4042 patients, AMI was the final diagnosis in 19% of patients. Median QRS duration and median QTc interval were significantly greater in patients with AMI compared to those with other final diagnoses (98 ms [IQR 88-108] vs. 94 ms [IQR 86-102] and 436 ms [IQR 414-462] vs. 425 ms [IQR 407-445], p < 0.001 for both comparisons). The diagnostic value of both ECG signatures however was only modest (AUC 0.56 and 0.60). Cumulative mortality rates after 2 years were 15.9% vs. 5.6% in patients with a QRS > 120 ms compared to a QRS duration ≤ 120 ms (p < 0.001), and 11.4% vs. 4.3% in patients with a QTc > 440 ms compared to a QRS duration ≤ 440 ms (p < 0.001). After adjustment for age and important ECG and clinical parameters, the QTc interval but not QRS duration remained an independent predictor of mortality. CONCLUSIONS: Prolongation of QRS duration > 120 ms and QTc interval > 440 ms predict mortality in patients with suspected AMI, but do not add diagnostic value.

Diagnostic value of the cardiac electrical biomarker, a novel ECG marker indicating myocardial injury, in patients with symptoms suggestive of non-ST-elevation myocardial infarction.

BACKGROUND: The cardiac electrical biomarker (CEB) is a novel electrocardiographic (ECG) marker quantifying the dipolar activity of the heart with higher levels indicating myocardial injury. METHODS: We prospectively enrolled 1097 patients presenting with suspected non-ST-elevation myocardial infarction (NSTEMI) to the emergency department (ED). Digital 12-lead ECGs were recorded at presentation and the CEB values were calculated in a blinded fashion. The final diagnosis was adjudicated by two independent cardiologists. The prognostic endpoint was all-cause mortality during 2 years of follow-up. RESULTS: NSTEMI was the final diagnosis in 14% of patients. CEB levels were higher in patients with NSTEMI compared to other causes of chest pain (median 44 (IQR 21-98) vs. 30 (IQR 16-61), p < .001). A weak but significant correlation between levels of high-sensitivity cardiac troponin T (hs-cTnT) at admission to the ED and the CEB was found (r = .23, p < .001). The use of the CEB in addition to conventional ECG criteria improved the diagnostic accuracy for the diagnosis of NSTEMI as quantified by the area under the receiver operating characteristics curve from 0.66 to 0.71 (p < .001) and the sensitivity improved from 43% to 79% (p < .001). CONCLUSION: In conclusion, the CEB, an ECG marker of myocardial injury, significantly improves the accuracy and sensitivity of the ECG for the diagnosis of NSTEMI.

Debatable issues in automated ECG reporting.

Although automated ECG analysis has been available for many years, there are some aspects which require to be re-assessed with respect to their value while newer techniques which are worthy of review are beginning to find their way into routine use. At the annual International Society of Computerized Electrocardiology conference held in April 2017, four areas in particular were debated. These were a) automated 12 lead resting ECG analysis; b) real time out of hospital ECG monitoring; c) ECG imaging; and d) single channel ECG rhythm interpretation. One speaker presented the positive aspects of each technique and another outlined the more negative aspects. Debate ensued. There were many positives set out for each technique but equally, more negative features were not in short supply, particularly for out of hospital ECG monitoring.

Biometric verification by cross-correlation analysis of 12-lead ECG patterns: Ranking of the most reliable peripheral and chest leads.

BACKGROUND: Electrocardiogram (ECG)-based biometrics relies on the most stable and unique beat patterns, i.e. those with maximal intra-subject and minimal inter-subject waveform differences seen from different leads. We investigated methodology to evaluate those differences, aiming to rank the most prominent single and multi-lead ECG sets for biometric verification across a large population. METHODS: A clinical standard 12-lead resting ECG database, including 460 pairs of remote recordings (distanced 1year apart) was used. Inter-subject beat waveform differences were studied by cross-correlation and amplitude relations of average PQRST (500ms) and QRS (100ms) patterns, using 8 features/lead in 12-leads. Biometric verification models based on stepwise linear discriminant classifier were trained on the first half of records. True verification rate (TVR) on the remaining test data was further reported as a common mean of the correctly verified equal subjects (true acceptance rate) and correctly rejected different subjects (true rejection rate). RESULTS AND CONCLUSIONS: In single-lead ECG human identity applications, we found maximal TVR (87-89%) for the frontal plane leads (I, -aVR, II) within (0-60°) sector. Other leads were ranked: inferior (85%), lateral to septal (82-81%), with intermittent V3 drop (77.6%), suggesting anatomical landmark displacements. ECG pattern view from multi-lead sets improved TVR: chest (91.3%), limb (94.6%), 12-leads (96.3%).

Diagnostic value of ST-segment deviations during cardiac exercise stress testing: Systematic comparison of different ECG leads and time-points.

BACKGROUND: Exercise ECG stress testing is the most widely available method for evaluation of patients with suspected myocardial ischemia. Its major limitation is the relatively poor accuracy of ST-segment changes regarding ischemia detection. Little is known about the optimal method to assess ST-deviations. METHODS: A total of 1558 consecutive patients undergoing bicycle exercise stress myocardial perfusion imaging (MPI) were enrolled. Presence of inducible myocardial ischemia was adjudicated using MPI results. The diagnostic value of ST-deviations for detection of exercise-induced myocardial ischemia was systematically analyzed 1) for each individual lead, 2) at three different intervals after the J-point (J+40ms, J+60ms, J+80ms), and 3) at different time points during the test (baseline, maximal workload, 2min into recovery). RESULTS: Exercise-induced ischemia was detected in 481 (31%) patients. The diagnostic accuracy of ST-deviations was highest at +80ms after the J-point, and at 2min into recovery. At this point, ST-amplitude showed an AUC of 0.63 (95% CI 0.59-0.66) for the best-performing lead I. The combination of ST-amplitude and ST-slope in lead I did not increase the AUC. Lead I reached a sensitivity of 37% and a specificity of 83%, with similar sensitivity to manual ECG analysis (34%, p=0.31) but lower specificity (90%, p<0.001). CONCLUSION: When using ECG stress testing for evaluation of patients with suspected myocardial ischemia, the diagnostic accuracy of ST-deviations is highest when evaluated at +80ms after the J-point, and at 2min into recovery.

Diagnostic and Prognostic Value of Lead aVR During Exercise Testing in Patients Suspected of Having Myocardial Ischemia.

We aimed to assess the diagnostic and prognostic value of ST-segment deviation in aVR, a lead often ignored in clinical practice, during exercise testing and to compare it to the most widely used criterion of ST-segment depression in V5. We enrolled 1,596 patients with suspected myocardial ischemia referred for nuclear perfusion imaging undergoing bicycle stress testing. ST-segment amplitudes in leads aVR and V5 were automatically measured. The presence of inducible myocardial ischemia was the diagnostic end point and adjudicated based on nuclear perfusion imaging and coronary angiography. Major adverse cardiac events (MACE) during 2 years of follow-up including death, acute myocardial infarction, and coronary revascularization were the prognostic end point. Exercise-induced myocardial ischemia was detected in 470 patients (29%). Median ST amplitudes for leads aVR and V5 differed significantly among patients with and without ischemia (p <0.01). The diagnostic accuracy of ST changes for myocardial ischemia as quantified by the area under the receiver operating characteristic curve was highest 2 minutes into recovery and similar in aVR and V5 (0.62, 95% confidence interval CI 0.60 to 0.65 vs 0.60, 95% confidence interval 0.58 to 0.63, p = 0.08 for comparison). In multivariate analysis, ST changes in lead aVR, but not lead V5, contributed independent diagnostic information on top of clinical parameters and manual electrocardiographic interpretation. Within 2 years of follow-up, MACE occurred in 33% of patients with ST elevations in aVR and in 16% without (p <0.001). In conclusion, ST elevation in lead aVR during exercise testing indicates inducible myocardial ischemia independently of ST depressions in lead V5 and clinical factors and also predicts MACE during follow-up.

Diagnostic and prognostic values of the V-index, a novel ECG marker quantifying spatial heterogeneity of ventricular repolarization, in patients with symptoms suggestive of non-ST-elevation myocardial infarction.

BACKGROUND: The V-index is an ECG marker quantifying spatial heterogeneity of ventricular repolarization. We prospectively assessed the diagnostic and prognostic values of the V-index in patients with suspected non-ST-elevation myocardial infarction (NSTEMI). METHODS: We prospectively enrolled 497 patients presenting with suspected NSTEMI to the emergency department (ED). Digital 12-lead ECGs of five-minute duration were recorded at presentation. The V-index was automatically calculated in a blinded fashion. Patients with a QRS duration >120ms were ruled out from analysis. The final diagnosis was adjudicated by two independent cardiologists. The prognostic endpoint was all-cause mortality during 24months of follow-up. RESULTS: NSTEMI was the final diagnosis in 14% of patients. V-index levels were higher in patients with AMI compared to other causes of chest pain (median 23ms vs. 18ms, p<0.001). The use of the V-index in addition to conventional ECG-criteria improved the diagnostic accuracy for the diagnosis of NSTEMI as quantified by area under the ROC curve from 0.66 to 0.73 (p=0.001) and the sensitivity of the ECG for AMI from 41% to 86% (p<0.001). Cumulative 24-month mortality rates were 99.4%, 98.4% and 88.3% according to tertiles of the V-index (p<0.001). After adjustment for age and important ECG and clinical parameters, the V-index remained an independent predictor of death. CONCLUSIONS: The V-index, an ECG marker quantifying spatial heterogeneity of ventricular repolarization, significantly improves the accuracy and sensitivity of the ECG for the diagnosis of NSTEMI and independently predicts mortality during follow-up.

Quantification of the first-order high-pass filter's influence on the automatic measurements of the electrocardiogram.

BACKGROUND AND OBJECTIVE: The first-order high-pass filter (AC coupling) has previously been shown to affect the ECG for higher cut-off frequencies. We seek to find a systematic deviation in computer measurements of the electrocardiogram when the AC coupling with a 0.05 Hz first-order high-pass filter is used. METHODS: The standard 12-lead electrocardiogram from 1248 patients and the automated measurements of their DC and AC coupled version were used. We expect a large unipolar QRS-complex to produce a deviation in the opposite direction in the ST-segment. RESULTS: We found a strong correlation between the QRS integral and the offset throughout the ST-segment. The coefficient for J amplitude deviation was found to be -0.277 µV/(µV⋅s). CONCLUSIONS: Potential dangerous alterations to the diagnostically important ST-segment were found. Medical professionals and software developers for electrocardiogram interpretation programs should be aware of such high-pass filter effects since they could be misinterpreted as pathophysiology or some pathophysiology could be masked by these effects.

Pseudo-real-time low-pass filter in ECG, self-adjustable to the frequency spectra of the waves.

The electrocardiogram (ECG) acquisition is often accompanied by high-frequency electromyographic (EMG) noise. The noise is difficult to be filtered, due to considerable overlapping of its frequency spectrum to the frequency spectrum of the ECG. Today, filters must conform to the new guidelines (2007) for low-pass filtering in ECG with cutoffs of 150 Hz for adolescents and adults, and to 250 Hz for children. We are suggesting a pseudo-real-time low-pass filter, self-adjustable to the frequency spectra of the ECG waves. The filter is based on the approximation procedure of Savitzky-Golay with dynamic change in the cutoff frequency. The filter is implemented pseudo-real-time (real-time with a certain delay). An additional option is the automatic on/off triggering, depending on the presence/absence of EMG noise. The analysis of the proposed filter shows that the low-frequency components of the ECG (low-power P- and T-waves, PQ-, ST- and TP-segments) are filtered with a cutoff of 14 Hz, the high-power P- and T-waves are filtered with a cutoff frequency in the range of 20-30 Hz, and the high-frequency QRS complexes are filtered with cutoff frequency of higher than 100 Hz. The suggested dynamic filter satisfies the conflicting requirements for a strong suppression of EMG noise and at the same time a maximal preservation of the ECG high-frequency components.

A Correction Formula for the ST-Segment Measurements of AC-Coupled Electrocardiograms.

GOAL: The ST segment of an electrocardiogram (ECG) is very important for the correct diagnosis of an acute myocardial infarction. Most clinical ECGs are recorded using an ACcoupled ECG amplifier. It is well known, that first-order high-pass filters used for the AC coupling can affect the ST segment of an ECG. This effect is stronger the higher the filter's cut-off frequency is and the larger the QRS integral is. We present a formula that estimates these changes in the ST segment and therefore allows for correcting ST measurements that are based on an ACcoupled ECG. METHODS: The presented correction formula can be applied when only four parameters are known: the possibly estimated QRS area A, the QRS duration W, the beat-to-beat interval TRR, and the filter time constant T, further, the time point Tj to correct-after the J point-must be specified. RESULTS: The formula is correct within 0.6% until 40% ms after the J point and within 6% until 80 ms after the J point. CONCLUSION AND SIGNIFICANCE: It is not necessary to have the raw data available and the formula therefore opens up the possibility of reevaluating studies that are based on ACcoupled ECGs and compare the results of such studies with studies that are based on newer, DC-coupled ECGs.

Intersubject variability and intrasubject reproducibility of 12-lead ECG metrics: Implications for human verification.

BACKGROUND: Electrocardiogram (ECG) biometrics is an advanced technology, not yet covered by guidelines on criteria, features and leads for maximal authentication accuracy. OBJECTIVE: This study aims to define the minimal set of morphological metrics in 12-lead ECG by optimization towards high reliability and security, and validation in a person verification model across a large population. METHODS: A standard 12-lead resting ECG database from 574 non-cardiac patients with two remote recordings (>1year apart) was used. A commercial ECG analysis module (Schiller AG) measured 202 morphological features, including lead-specific amplitudes, durations, ST-metrics, and axes. Coefficient of variation (CV, intersubject variability) and percent-mean-absolute-difference (PMAD, intrasubject reproducibility) defined the optimization (PMAD/CV→min) and restriction (CV<30%) criteria for selection of the most stable and distinctive features. Linear discriminant analysis (LDA) validated the non-redundant feature set for person verification. RESULTS AND CONCLUSIONS: Maximal LDA verification sensitivity (85.3%) and specificity (86.4%) were validated for 11 optimal features: R-amplitude (I,II,V1,V2,V3,V5), S-amplitude (V1,V2), Tnegative-amplitude (aVR), and R-duration (aVF,V1).

Inter-lead correlation analysis for automated detection of cable reversals in 12/16-lead ECG.

BACKGROUND AND OBJECTIVE: A crucial factor for proper electrocardiogram (ECG) interpretation is the correct electrode placement in standard 12-lead ECG and extended 16-lead ECG for accurate diagnosis of acute myocardial infarctions. In the context of optimal patient care, we present and evaluate a new method for automated detection of reversals in peripheral and precordial (standard, right and posterior) leads, based on simple rules with inter-lead correlation dependencies. METHODS: The algorithm for analysis of cable reversals relies on scoring of inter-lead correlations estimated over 4s snapshots with time-coherent data from multiple ECG leads. Peripheral cable reversals are detected by assessment of nine correlation coefficients, comparing V6 to limb leads: (I, II, III, -I, -II, -III, -aVR, -aVL, -aVF). Precordial lead reversals are detected by analysis of the ECG pattern cross-correlation progression within lead sets (V1-V6), (V4R, V3R, V3, V4), and (V4, V5, V6, V8, V9). Disturbed progression identifies the swapped leads. RESULTS: A test-set, including 2239 ECGs from three independent sources-public 12-lead (PTB, CSE) and proprietary 16-lead (Basel University Hospital) databases-is used for algorithm validation, reporting specificity (Sp) and sensitivity (Se) as true negative and true positive detection of simulated lead swaps. Reversals of limb leads are detected with Se = 95.5-96.9% and 100% when right leg is involved in the reversal. Among all 15 possible pairwise reversals in standard precordial leads, adjacent lead reversals are detected with Se = 93.8% (V5-V6), 95.6% (V2-V3), 95.9% (V3-V4), 97.1% (V1-V2), and 97.8% (V4-V5), increasing to 97.8-99.8% for reversals of anatomically more distant electrodes. The pairwise reversals in the four extra precordial leads are detected with Se = 74.7% (right-sided V4R-V3R), 91.4% (posterior V8-V9), 93.7% (V4R-V9), and 97.7% (V4R-V8, V3R-V9, V3R-V8). Higher true negative rate is achieved with Sp > 99% (standard 12-lead ECG), 81.9% (V4R-V3R), 91.4% (V8-V9), and 100% (V4R-V9, V4R-V8, V3R-V9, V3R-V8), which is reasonable considering the low prevalence of lead swaps in clinical environment. CONCLUSIONS: Inter-lead correlation analysis is able to provide robust detection of cable reversals in standard 12-lead ECG, effectively extended to 16-lead ECG applications that have not previously been addressed.

Real-time arrhythmia detection with supplementary ECG quality and pulse wave monitoring for the reduction of false alarms in ICUs.

False intensive care unit (ICU) alarms induce stress in both patients and clinical staff and decrease the quality of care, thus significantly increasing both the hospital recovery time and rehospitalization rates. In the PhysioNet/CinC Challenge 2015 for reducing false arrhythmia alarms in ICU bedside monitor data, this paper validates the application of a real-time arrhythmia detection library (ADLib, Schiller AG) for the robust detection of five types of life-threatening arrhythmia alarms. The strength of the application is to give immediate feedback on the arrhythmia event within a scan interval of 3 s-7.5 s, and to increase the noise immunity of electrocardiogram (ECG) arrhythmia analysis by fusing its decision with supplementary ECG quality interpretation and real-time pulse wave monitoring (quality and hemodynamics) using arterial blood pressure or photoplethysmographic signals. We achieved the third-ranked real-time score (79.41) in the challenge (Event 1), however, the rank was not officially recognized due to the 'closed-source' entry. This study shows the optimization of the alarm decision module, using tunable parameters such as the scan interval, lead quality threshold, and pulse wave features, with a follow-up improvement of the real-time score (80.07). The performance (true positive rate, true negative rate) is reported in the blinded challenge test set for different arrhythmias: asystole (83%, 96%), extreme bradycardia (100%, 90%), extreme tachycardia (98%, 80%), ventricular tachycardia (84%, 82%), and ventricular fibrillation (78%, 84%). Another part of this study considers the validation of ADLib with four reference ECG databases (AHA, EDB, SVDB, MIT-BIH) according to the international recommendations for performance reports in ECG monitors (ANSI/AAMI EC57). The sensitivity (Se) and positive predictivity (+P) are: QRS detector QRS (Se, +P) > 99.7%, ventricular ectopic beat (VEB) classifier VEB (Se, +P) = 95%, and ventricular fibrillation detector VFIB (P + = 94.8%) > VFIB (Se = 86.4%), adjusted to the clinical setting requirements, giving preference to low false positive alarms.