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Background: Continuous monitoring for atrial fibrillation (AF) using photoplethysmography (PPG) from smartwatches or other wearables is challenging due to periods of poor signal quality during motion or suboptimal wearing. As a result, many consumer wearables sample infrequently and only analyze when the user is at rest, which limits the ability to perform continuous monitoring or to quantify AF., Objectives: This study aimed to compare 2 methods of continuous monitoring for AF in free-living patients: a well-validated signal processing (SP) heuristic and a convolutional deep neural network (DNN) trained on raw signal., Methods: We collected 4 weeks of continuous PPG and electrocardiography signals in 204 free-living patients. Both SP and DNN models were developed and validated both on holdout patients and an external validation set., Results: The results show that the SP model demonstrated receiver-operating characteristic area under the curve (AUC) of 0.972 (sensitivity 99.6%, specificity: 94.4%), which was similar to the DNN receiver-operating characteristic AUC of 0.973 (sensitivity 92.2, specificity: 95.5%); however, the DNN classified significantly more data (95% vs 62%), revealing its superior tolerance of tracings prone to motion artifact. Explainability analysis revealed that the DNN automatically suppresses motion artifacts, evaluates irregularity, and learns natural AF interbeat variability. The DNN performed better and analyzed more signal in the external validation cohort using a different population and PPG sensor (AUC, 0.994; 97% analyzed vs AUC, 0.989; 88% analyzed)., Conclusions: DNNs perform at least as well as SP models, classify more data, and thus may be better for continuous PPG monitoring., Competing Interests: Funding Support and Author Disclosures Dr Olgin is supported by a grant from the Mark Cuban Foundation. Dr Tison is supported by National Institutes of Health grant K23HL135274. Dr Avram is supported by the Fonds de la recherche en santé du Québec (grant no. 312758–Montreal Heart Institute Research Centre, the Montreal Heart Institute Foundation). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Continuous electrocardiographic (ECG) monitoring is used to identify ventricular tachycardia (VT), but false alarms occur frequently., Objective: The purpose of this study was to assess the rate of 30-day in-hospital mortality associated with VT alerts generated from bedside ECG monitors to those from a new algorithm among intensive care unit (ICU) patients., Methods: We conducted a retrospective cohort study in consecutive adult ICU patients at an urban academic medical center and compared current bedside monitor VT alerts, VT alerts from a new-unannotated algorithm, and true-annotated VT. We used survival analysis to explore the association between VT alerts and mortality., Results: We included 5679 ICU admissions (mean age 58 ± 17 years; 48% women), 503 (8.9%) experienced 30-day in-hospital mortality. A total of 30.1% had at least 1 current bedside monitor VT alert, 14.3% had a new-unannotated algorithm VT alert, and 11.6% had true-annotated VT. Bedside monitor VT alert was not associated with increased rate of 30-day mortality (adjusted hazard ratio [aHR] 1.06; 95% confidence interval [CI] 0.88-1.27), but there was an association for VT alerts from our new-unannotated algorithm (aHR 1.38; 95% CI 1.12-1.69) and true-annotated VT(aHR 1.39; 95% CI 1.12-1.73)., Conclusion: Unannotated and annotated-true VT were associated with increased rate of 30-day in-hospital mortality, whereas current bedside monitor VT was not. Our new algorithm may accurately identify high-risk VT; however, prospective validation is needed., (© 2023 Heart Rhythm Society. Published by Elsevier Inc.)

Background: False ventricular tachycardia (VT) alarms are common during in-hospital electrocardiographic (ECG) monitoring. Prior research shows that the majority of false VT can be attributed to algorithm deficiencies., Purpose: The purpose of this study was: (1) to describe the creation of a VT database annotated by ECG experts and (2) to determine true vs. false VT using a new VT algorithm created by our group., Methods: The VT algorithm was processed in 5320 consecutive ICU patients with 572,574 h of ECG and physiologic monitoring. A search algorithm identified potential VT, defined as: heart rate >100 beats/min, QRSs > 120 ms, and change in QRS morphology in >6 consecutive beats compared to the preceding native rhythm. Seven ECG channels, SpO 2 , and arterial blood pressure waveforms were processed and loaded into a web-based annotation software program. Five PhD-prepared nurse scientists performed the annotations., Results: Of the 5320 ICU patients, 858 (16.13%) had 22,325 VTs. After three levels of iterative annotations, a total of 11,970 (53.62%) were adjudicated as true, 6485 (29.05%) as false, and 3870 (17.33%) were unresolved. The unresolved VTs were concentrated in 17 patients (1.98%). Of the 3870 unresolved VTs, 85.7% (n = 3281) were confounded by ventricular paced rhythm, 10.8% (n = 414) by underlying BBB, and 3.5% (n = 133) had a combination of both., Conclusions: The database described here represents the single largest human-annotated database to date. The database includes consecutive ICU patients, with true, false, and challenging VTs (unresolved) and could serve as a gold standard database to develop and test new VT algorithms., (© 2023 The Authors. Annals of Noninvasive Electrocardiology published by Wiley Periodicals LLC.)

Background: Impedance pneumography (IP) is the current device-driven method used to measure respiratory rate (RR) in hospitalized patients. However, RR alarms are common and contribute to alarm fatigue. While RR derived from electrocardiographic (ECG) waveforms hold promise, they have not been compared to the IP method., Purpose: Study examined the agreement between the IP and combined-ECG derived (EDR) for normal RR (≥12 or ≤20 breaths/minute [bpm]); low RR (≤5 bpm); and high RR (≥30 bpm)., Methodology: One-hundred intensive care unit patients were included by RR group: (1) normal RR (n = 50; 25 low RR and 25 high RR); (2) low RR (n = 50); and (3) high RR (n = 50). Bland-Altman analysis was used to evaluate agreement., Results: For normal RR, a significant bias difference of -1.00 + 2.11 (95% CI -1.60 to -0.40) and 95% limit of agreement (LOA) of -5.13 to 3.13 was found. For low RR, a significant bias difference of -16.54 + 6.02 (95% CI: -18.25 to -14.83) and a 95% LOA of -28.33 to - 4.75 was found. For high RR, a significant bias difference of 17.94 + 12.01 (95% CI: 14.53 to 21.35) and 95% LOA of -5.60 to 41.48 was found., Conclusion: Combined-EDR method had good agreement with the IP method for normal RR. However, for the low RR, combined-EDR was consistently higher than the IP method and almost always lower for the high RR, which could reduce the number of RR alarms. However, replication in a larger sample including confirmation with visual assessment is warranted., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to declare., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Consumer devices with broad reach may be useful in screening for atrial fibrillation (AF) in appropriate populations. However, currently no consumer devices are capable of continuous monitoring for AF., Objective: The purpose of this study was to estimate the sensitivity and specificity of a smartwatch algorithm for continuous detection of AF from sinus rhythm in a free-living setting., Methods: We studied a commercially available smartwatch with photoplethysmography (W-PPG) and electrocardiogram (W-ECG) capabilities. We validated a novel W-PPG algorithm combined with a W-ECG algorithm in a free-living setting, and compared the results to those of a 28-day continuous ECG patch (P-ECG)., Results: A total of 204 participants completed the free-living study, recording 81,944 hours with both P-ECG and smartwatch measurements. We found sensitivity of 87.8% (95% confidence interval [CI] 83.6%-91.0%) and specificity of 97.4% (95% CI 97.1%-97.7%) for the W-PPG algorithm (every 5-minute classification); sensitivity of 98.9% (95% CI 98.1%-99.4%) and specificity of 99.3% (95% CI 99.1%-99.5%) for the W-ECG algorithm; and sensitivity of 96.9% (95% CI 93.7%-98.5%) and specificity of 99.3% (95% CI 98.4%-99.7%) for W-PPG triggered W-ECG with a single W-ECG required for confirmation of AF. We found a very strong correlation of W-PPG in quantifying AF burden compared to P-ECG (r = 0.98)., Conclusion: Our findings demonstrate that a novel algorithm using a commercially available smartwatch can continuously detect AF with excellent performance and that confirmation with W-ECG further enhances specificity. In addition, our W-PPG algorithm can estimate AF burden. Further research is needed to determine whether this algorithm is useful in screening for AF in select at-risk patients., (Copyright © 2021 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Survival from in-hospital cardiac arrest (IHCA) due to pulseless electrical activity/asystole remains poor. We aimed to evaluate whether electrocardiographic changes provide predictive information for risk of IHCA from pulseless electrical activity/asystole. We conducted a retrospective case-control study, utilizing continuous electrocardiographic data from case and control patients. We selected 3 consecutive 3-hour blocks (block 3, 2, and 1 in that order); block 1 immediately preceded cardiac arrest in cases, whereas block 1 was chosen at random in controls. In each block, we measured dominant positive and negative trends in electrocardiographic parameters, evaluated for arrhythmias, and compared these between consecutive blocks. We created random forest and logistic regression models, and tested them on differentiating case versus control patients (case block 1 vs control block 1), and temporal relation to cardiac arrest (case block 2 vs case block 1). Ninety-one cases (age 63.0 ± 17.6, 58% male) and 1,783 control patients (age 63.5 ± 14.8, 67% male) were evaluated. We found significant differences in electrocardiographic trends between case and control block 1, particularly in QRS duration, QTc, RR, and ST. New episodes of atrial fibrillation and bradyarrhythmias were more common before IHCA. The optimal model was the random forest, achieving an area under the curve of 0.829, 63.2% sensitivity, 94.6% specificity at differentiating case versus control block 1 on a validation set, and area under the curve 0.954, 91.2% sensitivity, 83.5% specificity at differentiating case block 1 versus case block 2. In conclusion, trends in electrocardiographic parameters during the 3-hour window immediately preceding IHCA differ significantly from other time periods, and provide robust predictive information., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Purpose: Obstructive sleep apnea (OSA) syndrome is a common condition that can impact clinical outcomes among patients with cardiovascular disease. Screening all subjects with heart disease via polysomnography (PSG) is costly and resource-limited. We sought to compare a Holter monitor-based algorithm to detect OSA to in-laboratory polysomnography (PSG)., Methods: Prospective cohort study of patients undergoing in-laboratory attended PSG for the evaluation of OSA. A standard 12-lead Holter monitor was attached to patients at the initiation of PSG. Holter-derived respiratory disturbance index (HDRDI) was extracted from the respiratory myogram, based on detecting skeletal muscle "noise" detected on the baseline. Apneic and hypopneic episodes were identified by comparing sudden changes in the myogram to abrupt increases in heart rate. The HDRDI was compared with the PSG-derived apnea-hypopnea index (PDAHI)., Results: Thirty patients underwent simultaneous Holter monitoring and overnight diagnostic PSG. An ROC curve for peak HDRDI was 0.79 (95% CI 0.61, 0.97) for OSA, with sensitivity of 94.4% and specificity of 54.5%. A cutoff value of HDRDI < 10 appeared to identify those individuals without clinically significant sleep-disordered breathing., Conclusion: Holter-derived respiration detected OSA comparable to PSG. Further study is warranted to determine its utility for screening and diagnosing OSA in appropriately selected patients.

Background: The utility of exercise-induced ST-segment depression for diagnosing ischemic heart disease (IHD) in women is unclear., Hypothesis: Based on evidence that IHD pathophysiology in women involves coronary vascular dysfunction, we hypothesized that coronary vascular dysfunction contributes to exercise electrocardiography (Ex-ECG) ST-depression in the absence of obstructive coronary artery disease, so-called false positive results. We tested our hypothesis in a pilot study evaluating the relationship between peripheral vascular endothelial function and Ex-ECG., Methods: Twenty-nine asymptomatic women without cardiac risk factors underwent maximal Bruce protocol exercise treadmill testing and peripheral endothelial function assessment using peripheral arterial tonometry (Itamar EndoPAT 2000) to measure reactive hyperemia index (RHI). The relationship between RHI and Ex-ECG ST-segment depression was evaluated using logistic regression and differences in subgroups using 2-tailed t tests., Results: Mean age was 54 ± 7 years, body mass index 25 ± 4 kg/m 2 , and RHI 2.51 ± 0.66. Three women (10%) had RHI <1.68, consistent with abnormal peripheral endothelial function, whereas 18 women (62%) met criteria for positive Ex-ECG based on ST-segment depression in contiguous leads. Women with and without ST-segment depression had similar baseline and exercise vital signs, metabolic equivalents achieved, and RHI (all P > 0.05). RHI did not predict ST-segment depression., Conclusions: Our pilot study demonstrates high prevalence of exercise-induced ST-segment depression in asymptomatic, middle-aged, overweight women. Peripheral vascular endothelial dysfunction did not predict Ex-ECG ST-segment depression. Further work is needed to investigate the utility of vascular endothelial testing and Ex-ECG for IHD diagnostic and management purposes in women., (© 2018 Wiley Periodicals, Inc.)

Background: Cheyne-Stokes respiration (CSR) has been investigated primarily in outpatients with heart failure. In this study we compare CSR and periodic breathing (PB) between healthy and cardiac groups., Methods: We compared CSR and PB, measured during 24 hr of continuous 12-lead electrocardiographic (ECG) Holter recording, in a group of 90 hospitalized patients presenting to the emergency department with symptoms suggestive of acute coronary syndrome (ACS) to a group of 100 healthy ambulatory participants. We also examined CSR and PB in the 90 patients presenting with ACS symptoms, divided into a group of 39 (43%) with confirmed ACS, and 51 (57%) with a cardiac diagnosis but non-ACS. SuperECG software was used to derive respiration and then calculate CSR and PB episodes from the ECG Holter data. Regression analyses were used to analyze the data. We hypothesized SuperECG software would differentiate between the groups by detecting less CSR and PB in the healthy group than the group of patients presenting to the emergency department with ACS symptoms., Results: Hospitalized patients with suspected ACS had 7.3 times more CSR episodes and 1.6 times more PB episodes than healthy ambulatory participants. Patients with confirmed ACS had 6.0 times more CSR episodes and 1.3 times more PB episodes than cardiac non-ACS patients., Conclusion: Continuous 12-lead ECG derived CSR and PB appear to differentiate between healthy participants and hospitalized patients., (© 2017 Wiley Periodicals, Inc.)

Background: Acute myocardial ischemia is a common cause of ventricular arrhythmias, yet recent ECG methods predicting susceptibility to ventricular tachyarrhythmia have not been fully evaluated during spontaneous ischemia. We sought to evaluate the clinical utility of alternans and non-alternans components of repolarization variability from the standard 10-second 12-lead ECG signals to risk stratify patients with acute chest pain., Methods: We enrolled consecutive, non-traumatic, chest pain patients transported through Emergency Medical Services (EMS) to three tertiary care hospitals with cardiac catheterization lab capabilities in Pittsburgh, PA. ECG signals were manually annotated by an electrophysiologist, then automatically processed using a custom-written software. Both T wave alternans (TWA) and non-alternans repolarization variability (NARV) were calculated using the absolute RMS differences over the repolarization window between odd/even averaged beats and between consecutive averaged pairs, respectively. The primary study outcome was the presence of acute myocardial infarction (AMI) documented by cardiac angiography., Results: After excluding patients with secondary repolarization changes (n=123) and those with excessive noise (n=90), our final sample included 537 patients (age 57±16years, 56% males). Patients with AMI (n=47, 9%) had higher TWA and NARV values (p<0.01). Mean RR correlated with TWA, and noise measures correlated with TWA and NARV, after adjusting for potential confounders. There was a high collinearity between TWA and NARV, and each was separately predictive of AMI after controlling for number of analyzed beats, noise measures, and other clinical variables., Conclusions: Despite limitations imposed by signal quality, TWA and NARV are higher in patients with AMI, even after correction for potential confounders. The clinical value of TWA and NARV derived from standard ECG using our time-domain RMS method is questionable due to the small number of beats and significant noise., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Introduction: The relationship between the autonomic nervous system and restless legs syndrome (RLS) and periodic limb movements of sleep (PLMS) consists of varied and somewhat conflicting reports. In order to further elucidate these complexities, a retrospective analysis of polysomnography (PSG) records and clinical data was performed., Methods: Records from 233 adult subjects were randomly selected and organized into one of four groups ("non-RLS/PLMS" [n=61], "RLS" [n=60], "PLMS" [n=58], and "RLS/PLMS" [n=54]). Heart rate variability (HRV) analysis was based on 5-minute samples of 2-lead electrocardiogram data isolated from PSG recordings during wakefulness and NREM sleep, and included mean RR interval (labeled "NN") and standard deviation of the RR intervals (labeled "SDNN"), and HRV power, very low frequency (VLF), low frequency (LF), and high frequency (HF) spectral bands., Results: A significant reduction in the VLF band in the PLMS group as compared to the non-RLS/PLMS group (542±674 vs . 969±1025 ms 2 , p =0.038) was found in wakefulness. Statistically significant differences were seen in the PLMS group as compared to the non-RLS/PLMS group with a reduction in SDNN ( p =0.001) and the HF ( p =0.001) band, and an increase in HRV power ( p =0.001), and the VLF ( p =0.005) and LF ( p =0.001) bands in NREM sleep., Conclusions: The PLMS group exhibited reduced basal sympathetic activity in wakefulness, but basal sympathetic predominance during NREM sleep, distinguishing this group from the RLS and RLS/PLMS groups.

Blood potassium concentration ([K + ]) influences the electrocardiogram (ECG), particularly T-wave morphology. We developed a new method to quantify [K + ] from T-wave analysis and tested its clinical applicability on data from dialysis patients, in whom [K + ] varies significantly during the therapy. To elucidate the mechanism linking [K + ] and T-wave, we also analysed data from long QT syndrome type 2 (LQT2) patients, testing the hypothesis that our method would have underestimated [K + ] in these patients. Moreover, a computational model was used to explore the physiological processes underlying our estimator at the cellular level. We analysed 12-lead ECGs from 45 haemodialysis and 12 LQT2 patients. T-wave amplitude and downslope were calculated from the first two eigenleads. The T-wave slope-to-amplitude ratio (T S/A ) was used as starting point for an ECG-based [K + ] estimate (K ECG ). Leave-one-out cross-validation was performed. Agreement between K ECG and reference [K + ] from blood samples was promising (error: -0.09 ± 0.59 mM, absolute error: 0.46 ± 0.39 mM). The analysis on LQT2 patients, also supported by the outcome of computational analysis, reinforces our interpretation that, at the cellular level, delayed-rectifier potassium current is a main contributor of K ECG correlation to blood [K + ]. Following a comprehensive validation, this method could be effectively applied to monitor patients at risk for hyper/hypokalemia.

We investigated 17 metrics derived from four leads of electrocardiographic (ECG) signals from hospital patient monitors to develop new ECG alarms for predicting adult bradyasystolic cardiac arrest events.A retrospective case-control study was designed to analyze 17 ECG metrics from 27 adult bradyasystolic and 304 control patients. The 17 metrics consisted of PR interval (PR), P-wave duration (Pdur), QRS duration (QRSdur), RR interval (RR), QT interval (QT), estimate of serum K  +  using only frontal leads (SerumK2), T-wave complexity (T Complex), ST segment levels for leads I, II, V (ST I, ST II, ST V), and 7 heart rate variability (HRV) metrics. These 7 HRV metrics were standard deviation of normal to normal intervals (SDNN), total power, very low frequency power, low frequency power, high frequency power, normalized low frequency power, and normalized high frequency power. Controls were matched by gender, age (±5 years), admission to the same hospital unit within the same month, and the same major diagnostic category. A research ECG analysis software program developed by co-author D M was used to automatically extract the metrics. The absolute value for each ECG metric, and the duration, terminal value, and slope of the dominant trend for each ECG metric, were derived and tested as the alarm conditions. The maximal true positive rate (TPR) of detecting cardiac arrest at a prescribed maximal false positive rate (FPR) based on the trending conditions was reported. Lead time was also recorded as the time between the first time alarm condition was triggered and the event of cardiac arrest.While conditions based on the absolute values of ECG metrics do not provide discriminative information to predict bradyasystolic cardiac arrest, the trending conditions can be useful. For example, with a max FPR  =  5.0%, some derived alarms conditions are: trend duration of PR  >  2.8 h (TPR  =  48.2%, lead time  =  10.0  ±  6.6 h), trend duration of QRSdur  >  2.7 h (TPR  =  40.7%, lead time  =  8.8  ±  6.2 h), trend duration of RR  >  3.5 h (TPR  =  51.9%, lead time  =  6.4  ±  5.5 h), trend duration of T Complex  >  2.9 h (TPR  =  40.7%, lead time  =  6.8  ±  5.5 h), trend duration of ST I  >  3.0 h (TPR of 51.9%, lead time  =  8.4  ±  8.0 h), trend duration of SDNN  >  3.6 h (TPR of 40.7%, lead time  =  11.0  ±  8.6 h), trend duration of HRV total power  >  3.0 h (TPR of 25.9%, lead time  =  7.5  ±  8.1 h), terminal value of ST I  <  -56 µV (TPR  =  22.2%, lead time  =  12.8  ±  8.3 h), and slope of QR  >  19.4 ms h(-1) (TPR  =  25.9%, lead time  =  6.7  ±  6.9 h). Eleven trend duration alarms, eight terminal value alarms, and ten slope alarms, achieved a positive TPR with zero FPR. Furthermore, these alarms conditions with zero PFR can be combined by the 'OR'logic could further improve the TPR without increasing the FPR.The trend duration, terminal value, and slope of the dominant trend of the ECG metrics considered in this study are able to predict a subset of patients with bradyasystolic cardiac arrests with low or even zero FPR, which can be used for developing new ECG alarms.

Objectives: Autonomic dysfunction has been demonstrated in patients with rapid eye movement sleep behavior disorder utilizing heart rate variability parameters. We hypothesized that isolated rapid eye movement sleep without atonia is similarly associated with autonomic dysfunction as demonstrated by a reduction in heart rate variability., Methods: An evaluation of 120 records demonstrating rapid eye movement sleep without atonia during polysomnography was performed. Many (n=99) were discarded owing to factors potentially affecting heart rate variability. The remaining 21 records were matched with 21 records of patients demonstrating normal REM atonia, and subjected to electrocardiogram analysis. The parameters measured included R to R interval (RR) length, RR standard deviation, heart rate variability power, and very low frequency, low frequency, and high frequency bands., Results: Autonomic dysfunction was seen in patients with isolated rapid eye movement sleep without atonia as denoted by a reduction in heart rate variability compared to those with normal REM atonia. Significant differences between the groups were demonstrated in RR standard deviation (mean difference=0.1502 ± 0.317, 95% confidence interval [95% CI]=0.006, 0.295, p=0.042), heart rate variability power (mean difference=0.3005 ± 0.635, 95% CI=0.011, 0.589, p=0.042), and the low frequency band (mean difference=0.3166 ± 0.616 ms(2), 95% CI=0.036, 0.597, p=0.029), and a borderline significant reduction in the high frequency band (mean difference=0.3121 ± 0.686 ms(2), 95% CI=0.000, 0.624, p=0.050)., Conclusions: Our data confirms the hypothesis that heart rate variability is reduced in patients with isolated rapid eye movement sleep without atonia. The values obtained are consistent with previous findings in rapid eye movement behavior sleep disorder patients., Significance: This is the first report of autonomic dysfunction in isolated rapid eye movement sleep without atonia, revealing the need for further evaluation of the clinical significance and potential implications of this finding., (Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Breathing is a critical component of cardiopulmonary function, but few tools exist to evaluate respiration in ambulatory patients. Holter monitoring allows accurate diagnosis of a host of cardiac issues, and several investigators have demonstrated the ability to detect respiratory effort on the electrocardiogram. In this study we introduce a myogram signal derived from 12-lead, high frequency Holter as a means of detecting respiratory effort. Using the combined myogram and ECG signal, four novel variables were created: total number of Cheyne-Stokes episodes; the BWRatio, the ratio of power (above baseline) measured one second after peak-to-peak respiratory power, an assessment of the "shape" of the respiratory effort; DRR, the change in RR interval centering around peak inspiration; and minutes of synchronized breathing, a fixed ratio of heart beats to respiratory cycles. These variables were assessed in 24-hour recordings from three cohorts: healthy volunteers (n=33), heart failure subjects from the GISSI HF trial (n=383), and subjects receiving implantable defibrillators with severely depressed left ventricular function enrolled in the M2Risk trial (n=470). We observed a statistically significant 6-fold increase in the number of Cheyne-Stokes episodes (p=0.01 by ANOVA), decreases in BWRatio (p<0.001), as well as decrease in DRR in heart failure subjects; only minutes of synchronized breathing was not significantly decreased in heart failure. This study provides "proof of concept" that novel variables incorporating Holter-derived respiration can distinguish healthy subjects from heart failure. The utility of these variables for predicting heart failure, arrhythmia, and death risk in prospective studies needs to be assessed., (Published by Elsevier Inc.)

Background and Purpose: Automated measurements of electrocardiographic (ECG) intervals are widely used by clinicians for individual patient diagnosis and by investigators in population studies. We examined whether clinically significant systematic differences exist in ECG intervals measured by current generation digital electrocardiographs from different manufacturers and whether differences, if present, are dependent on the degree of abnormality of the selected ECGs., Methods: Measurements of RR interval, PR interval, QRS duration, and QT interval were made blindly by 4 major manufacturers of digital electrocardiographs used in the United States from 600 XML files of ECG tracings stored in the US FDA ECG warehouse and released for the purpose of this study by the Cardiac Safety Research Consortium. Included were 3 groups based on expected QT interval and degree of repolarization abnormality, comprising 200 ECGs each from (1) placebo or baseline study period in normal subjects during thorough QT studies, (2) peak moxifloxacin effect in otherwise normal subjects during thorough QT studies, and (3) patients with genotyped variants of congenital long QT syndrome (LQTS)., Results: Differences of means between manufacturers were generally small in the normal and moxifloxacin subjects, but in the LQTS patients, differences of means ranged from 2.0 to 14.0 ms for QRS duration and from 0.8 to 18.1 ms for the QT interval. Mean absolute differences between algorithms were similar for QRS duration and QT intervals in the normal and in the moxifloxacin subjects (mean ≤6 ms) but were significantly larger in patients with LQTS., Conclusions: Small but statistically significant group differences in mean interval and duration measurements and means of individual absolute differences exist among automated algorithms of widely used, current generation digital electrocardiographs. Measurement differences, including QRS duration and the QT interval, are greatest for the most abnormal ECGs., (© 2014.)

Purpose: It is not recommended to perform QTc estimation in patients with atrial fibrillation (AF). We evaluated multiple QT interval correction formulas, including a novel time-dependent history approach, in an effort to identify the best method for correcting the QT interval in patients with AF. The ideal correction results in independence between the QTc estimate and HR., Methods: Per-beat characteristics were derived using SuperECG (Mortara Instrument). Offline beat-to-beat QTc interval estimates were constructed using standard formulae and averaged (2-10) groups constructed., Results: Seventy-one patients were included, age 67 ± 10 years, 69% men. Mean-mean QTc intervals varied by correction (range 394-459 ms). Averaging resulted in the same mean-mean QTc estimate, but significantly reduced variability by up to 55%. Time-dependent RR interval history reduced variability the most (Δ 80%), increased QT/RR dynamics (m=.03 vs .17), and was independent with HR (m = 0.0008)., Conclusions: Our data suggests that QTc interval estimation in patients with AF can be performed reliably using time-dependent history (RRc) outperforming other correction methods., (Published by Elsevier Inc.)

Background: Sudden cardiac death represents a major public health problem, but in the general population the identification of those subjects at very high risk remains poor. Simultaneous multiparametric ECG analysis can improve the identification of high-risk patients., Methods: Five-min ECG recordings at a 5 MHz sampling rate (extended length-XL-ECG, Mortara Instruments, Milwaukee, WI, USA) were acquired in 105 healthy subjects (age range 21 to 80 years), equally distributed for age decades and sex, and three additional recordings, 30 min apart, were repeated in 30 subjects on the second day. The following parameters were recorded and analyzed: the RR interval, QRS duration, QT interval corrected according to the Bazett and Fridericia formulae, QT dispersion, T wave complexity, activation-recovery interval dispersion, standard deviation of the RR intervals, filtered QRS duration, the square root of the mean voltage of the last 40 ms of the filtered QRS, and the length of time that the terminal vector magnitude complex remains < 40 microV., Results: QRS duration, activation-recovery interval dispersion, and filtered QRS differed in the two sexes. The standard deviation of the RR intervals, T wave complexity and QT dispersion were significantly correlated with age. The reproducibility was good for each parameter., Conclusions: The XL-ECG allows the simultaneous calculation of eight adequately reproducible different parameters the values of which are in agreement with those of the literature. Thus, XL-ECG is a reliable time- and cost-saving tool.

It is commonly assumed that the presence of high frequency components in body surface potentials implies that fractionated activation fronts, caused by heterogeneously viable tissue, are present in the heart. However, it is possible that non-fractionated activation fronts can also give rise to high frequency surface potentials and that the relative amount of high frequency power is related to the complexity of the activation sequence. In a test of this idea, averaged body surface potentials were recorded during the entire QRS complex of nine Wolff-Parkinson-White (WPW) patients in situations in which fractionated activation fronts should not have been present, but which represent increasing degrees of complexity of ventricular activation: (1) postoperative ectopic pacing from subepicardial wires placed during surgery, when a single coherent activation front was present throughout most of the QRS; (2) Preoperative preexcited rhythm, when a single coherent activation front was present for one portion of the QRS (the delta wave); and (3) postoperative normal rhythm, when two or more activation fronts were present in the ventricles throughout most of the QRS. For comparison, averaged body surface potentials were also analyzed during the last 40 ms of the QRS complex and the ST segment of 14 postinfarction patients with chronic ventricular tachycardia. In the patients with WPW syndrome, relatively high frequency content increased (attenuation -36.7 vs -27.2 vs -18.3 dB) and QRS width decreased (160.7 vs 125.9 vs 94.1 ms) significantly from paced to preoperative to postoperative beats. Significant high frequency content was present in all cases, showing that coherent activation fronts can give rise to high frequencies. Interestingly, the postoperative QRS of WPW patients contained a larger proportion of high frequency power than did the late potentials of the patients with ventricular tachycardia. Thus, while the presence of late fractionated body surface potentials may be a marker for ventricular tachycardia, these potentials by themselves do not necessarily signify that the underlying cardiac activation giving rise to these signals is fractionated.

Background: The type of practitioners who use the standard exercise test is changing. Once a tool of the cardiologist, the standard exercise test is now being performed by internists and other noncardiologists. Because this change could be facilitated by computerization similar to the computerized interpretation programs available for the resting electrocardiograph (ECG), we performed this analysis. A secondary aim was to demonstrate the effects of medication status and resting ECG abnormalities on test diagnostic characteristics because these factors affect utility of the exercise test by the generalist., Methods and Results: A retrospective analysis was performed of consecutive patients referred at 2 university-affiliated Veteran's Affairs Medical Centers and a Hungarian Hospital for evaluation of chest pain and possible ischemic heart disease. There were 1384 consecutive male patients without a prior myocardial infarction with complete data who had exercise tests and coronary angiography between 1987 and 1997. Measurements included clinical, exercise test data, and visual interpretation of the ECG recordings as well as more than 100 computed measurements from the digitized ECG recordings and compilation of angiographic data from clinical reports. The computer measurements had similar diagnostic power compared with visual interpretation. Computerized measurements from maximal exercise or recovery were equivalent or superior to all other measurements. Prediction equations applied by computer were superior to single ECG measurements. Beta-blockers had no effect on test characteristics, whereas resting ST depression was associated with decreased specificity and increased sensitivity., Conclusions: Computerized exercise ST measurements are comparable to visual ST measurements by a cardiologist; computerized scores that included clinical and exercise test results exhibited the greatest diagnostic power. Applying scores with a computer allows the practicing physician to improve the diagnostic characteristics of the standard exercise test. This approach is successful even when there is resting ST depression, thus lessening the need for more expensive nuclear or imaging studies.

Background: The duration of the QT interval is only a gross estimate of repolarization. Besides its limited accuracy and reproducibility, it does not provide information on the morphology of the T wave; thus, morphologic alterations such as notches can be only qualitatively described but not objectively quantified., Methods and Results: To measure the complexity of repolarization in the long-QT syndrome (LQTS) patients, we previously applied principal component analysis to body surface mapping and found it useful in distinguishing normal from abnormal repolarization patterns (sensitivity, 87%). In the present study, we applied principal component analysis to 12-lead Holter recordings. The index of complexity of repolarization that we have developed (CR24h) reflects the average 24-hour complexity of repolarization and is mathematically defined as the average ratio between the second and the first eigenvalue. We studied 36 LQTS patients and 40 control subjects. A mean of 22+/-1.3 ECG recordings at 1-hour intervals was used in each patient, and a total of 1655 recordings were analyzed. CR24h was significantly higher in LQTS than in control subjects (34+/-12% versus 13+/-3%; P<.0001). A CR24h exceeding 2 SD above the mean of the control group (>20%) was present in 32 of 36 patients (88%). The negative predictive value of CR24h in LQTS was 88%, and the combination of prolonged QT and abnormal CR24h identified all LQTS patients from normal subjects, including 4 affected symptomatic individuals with a normal QT interval duration, suggesting that CR24h provides information independent of QT duration., Conclusions: Our data suggest that principal component analysis applied to 24-hour, 12-lead Holter recording adequately quantifies the complexity of ventricular repolarization and may become a useful noninvasive diagnostic tool in LQTS.

Patients in whom early and stable reperfusion through the infarct artery fails after thrombolytic treatment might benefit from further revascularization therapy. A reliable noninvasive technique able to detect both reperfusion and reocclusion would be useful to test this hypothesis. However, no such technique presently exists. ST-segment recovery analysis using continuous digital 12-lead ST monitoring has been shown to be an accurate predictor of infarct artery patency in real time. This method was dependent on a trained clinician's analysis of the recordings on a personal computer. For optimal bedside application, salient principles of this ST-segment recovery analysis were converted into algorithms and built into the ST monitor software. The essentials of these algorithms are described in this report.