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This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health (“mHealth”) technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/ Heart Rhythm Society/ European Heart Rhythm Association/ Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored. Varma, N (corresponding author), Cleveland Clin, Cleveland, OH 44106 USA. varman@ccf.org

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

Videoplethysmography (VPG) is an emerging technology that uses a video camera to capture subtle skin color variations caused by blood volume flow. VPG offers a seamless, non invasive long term cardiac monitoring solution which is necessary to capture a-symptomatic heart conditions such as early stages of Atrial Fibrillation (AF). In this work we investigate the ability of VPG based on high end Basler RGB camera to identify AF in a controlled hospital setting. We conduct a clinical study and explore various modern Machine Learning (ML) algorithms and feature extraction methods to provide classification among three groups: healthy subjects, subjects with AF before and after they undergo direct current cardioversion. Our results reveal that when features represent statistical, dimensional and time-frequency properties of the underlying VPG signal, all non-linear and ensemble classifiers under test achieve close to perfect performance in both 2- and 3-class classification. Among them, random forest and extreme gradient boosting classifier consistently attain the highest accuracy, sensitivity and specificity of almost 100%. These results suggest that the VPG technology relying on a high quality camera combined with intelligent ML classifiers and smart feature selection can be used to facilitate diagnosis of heart conditions within a controlled hospital environment and has a great potential to go beyond.

Background The risk of ventricular arrhythmias in patients on QT prolonging drugs is indicated to be increased early after cardioversion (CV) of atrial fibrillation (AF) to sinus rhythm (SR). Sotalol, used to prevent AF relapse, prolongs cardiac repolarization and corrected QT interval (QTc). A pronounced QTc prolongation is an established marker of pro‐arrhythmias. Our objective was to use novel technique to quantify and evaluate the diurnal variation of the QTc interval after elective CV to SR in patients on sotalol or metoprolol. Methods Fifty patients underwent twelve‐lead Holter recording for 24 hr after elective CV for persistent AF. All patients had the highest tolerable stable dose of sotalol (n = 27) or metoprolol (n = 23). Measurements of QT and RR intervals were performed on all valid beats. Results A clear diurnal variation of both HR and QTc was seen in both groups, more pronounced in patients on sotalol, where a high percentage of heartbeats with QTc >500 ms was observed, especially at night. Six patients (22%) on sotalol but none on metoprolol had >20% of all heart beats within the 24‐hour recording with QTc >500 ms. Conclusion Twenty‐four‐hour Holter recordings with QT‐measurement immediately after CV demonstrated that one in five patients on sotalol had >20% of all heart beats with prolonged QTc >500 ms, especially during night‐time. The QTc diurnal variation was retained in patients on β‐blockade or a potent class III anti‐arrhythmic drug with β‐blocking properties.

The JTpeak interval has been proposed as a new biomarker to demonstrate mixed ion channel effects, potentially leading to reduced late-stage electrocardiogram (ECG) monitoring for mildly QT-prolonging drugs. ECG waveforms from the IQ-CSRC study were used. Twenty healthy subjects were enrolled with 6 subjects on placebo and 9 subjects on each of 5 mildly QT-prolonging drugs - moxifloxacin, dofetilide, ondansetron, dolasetron, and quinine - and 1 negative drug, levocetirizine. A vector magnitude lead was derived from 12-lead ECGs, and measurements were made on a median beat from three 10-second replicates. Data were analyzed using a linear concentration-response model with QTcF and heart rate corrected JTpeak (JTpeak_c) as dependent variables. For moxifloxacin, dofetilide, and ondansetron, all pure hERG blockers, slopes of the concentration (C)-QTcF and C-JTpeak_c relationships were positive and statistically significant. With the prespecified linear model, the predicted effects on ΔΔQTcF and ΔΔJTpeak_c were 11.4 and 9.4 milliseconds for moxifloxacin at the geometric mean Cmax on day 1, 9.0 and 11.7 milliseconds for dofetilide and 11.5, and 7.9 milliseconds for ondansetron, respectively. In contrast, dolasetron and quinine, both with additional ion channel effects, prolonged QTcF with a positive C-ΔQTcF slope and predicted ΔΔQTcF effect on day 1 of 6.2 and 11.4 milliseconds, whereas the C-ΔJTpeak_c slope and the predicted ΔΔJTpeak on day 1 were negative (-0.3 and -7.5 milliseconds per ng/mL). Pure hERG-blocking drugs prolonged both the QTc and the JTpeak_c intervals, whereas drugs with mixed ion channel effects, including peak sodium inhibition, prolonged QTcF but not the JTpeak_c interval.

In this article, we reflect on a pilot project implementing a mindfulness-based stress reduction program among traumatized youth in foster and kinship care. We adapted a mindfulness intervention to teach self-regulation skills in a supportive, interactive, social group setting environment. Our hypothesis was that teaching mindfulness skills would enhance youth competency in stress management by giving them tools for self-regulation. In response to youth request for social groups, we adapted a mindfulness intervention aimed at stress reduction to include supervised social activities. Our program was marked by two adverse events: raising considerations regarding safety and supervision when in group settings with youth who previously experienced adverse childhood experiences and are prone to extreme reactivity and escalating behaviors. We share our experiences and recommendations for future research and practice, including recruitment considerations, opinions of group versus individual therapy, intensity of supervision of high-risk youth, training and support for graduate student volunteers working with youth in the child welfare system, and expectations for foster and adoptive family support of these youth. Our collective goal is to promote the health and wellness of these young people, equipping them with self-efficacy skills for future success, which may include mindfulness training. We realize that there is no one best approach to reaching this goal, and we need to consider safety and practicality when designing programs for youth in foster and kinship care.

Perhexiline has been used to treat hypertrophic cardiomyopathy. In addition to its effect on carnitine-palmitoyltransferase-1, it has mixed ion channel effects through inhibition of several cardiac ion currents. Effects on cardiac ion channels expressed in mammalian cells were assayed using a manual patch-clamp technique, action potential duration (APD) was measured in ventricular trabeculae of human donor hearts, and electrocardiogram effects were evaluated in healthy subjects in a thorough QT (TQT) study. Perhexiline blocked several cardiac ion currents at concentrations within the therapeutic range (150-600 ng/mL) with IC50 for hCav1.2 ∼ hERG < late hNav1.5. A significant APD shortening was observed in perhexiline-treated cardiomyocytes. The TQT study was conducted with a pilot part in 9 subjects to evaluate a dosing schedule that would achieve therapeutic and supratherapeutic perhexiline plasma concentrations on days 4 and 6, respectively. Guided by the results from the pilot, 104 subjects were enrolled in a parallel-designed part with a nested crossover comparison for the positive control. Perhexiline caused QTc prolongation, with the largest effect on ΔΔQTcF, 14.7 milliseconds at therapeutic concentrations and 25.6 milliseconds at supratherapeutic concentrations and a positive and statistically significant slope of the concentration-ΔΔQTcF relationship (0.018 milliseconds per ng/mL; 90%CI, 0.0119-0.0237 milliseconds per ng/mL). In contrast, the JTpeak interval was shortened with a negative concentration-JTpeak relationship, a pattern consistent with multichannel block. Further studies are needed to evaluate whether this results in a low proarrhythmic risk.

This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/ Heart Rhythm Society/ European Heart Rhythm Association/ Asia Pacific Heart Rhythm Society describes the current status of mobile health ("mHealth") technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

Background Risk stratification in non‐ischemic myocardial disease poses a challenge. While cardiovascular magnetic resonance (CMR) is a comprehensive tool, the electrocardiogram (ECG) provides quick impactful clinical information. Studying the relationships between CMR and ECG can provide much‐needed risk stratification. We evaluated the electrocardiographic signature of myocardial fibrosis defined as presence of late gadolinium enhancement (LGE) or extracellular volume fraction (ECV) ≥29%. Methods We evaluated 240 consecutive patients (51% female, 47.1 ± 16.6 years) referred for a clinical CMR who underwent 12‐lead ECGs within 90 days. ECG parameters studied to determine association with myocardial fibrosis included heart rate, QRS amplitude/duration, T‐wave amplitude, corrected QT and QT peak, and Tpeak‐Tend. Abnormal T‐wave was defined as low T‐wave amplitude ≤200 µV or a negative T wave, both in leads II and V5. Results Of the 147 (61.3%) patients with myocardial fibrosis, 67 (28.2%) had ECV ≥ 29%, and 132 (54.6%) had non‐ischemic LGE. An abnormal T‐wave was more prevalent in patients with versus without myocardial fibrosis (66% versus 42%, p

The convergence between wearable and medical device technologies is a natural progression. Miniaturization has allowed the design of small, compact monitoring systems that can record physiological signals over longer periods of time. Thus, the potential for these devices to expand the understanding of disease progression and patients' clinical status is very high. The accuracy of these devices, however, is dependent upon the computer algorithms utilized in the analysis of the large volume of physiological data monitored and/or recorded by the devices. Automated interpretation of the data by these new technologies, therefore, necessitates closer examination by regulatory organizations. The current requirements for the validation of novel Ambulatory ECG (A-ECG) annotation algorithms are based on the AAMI/ANSI-EC57 and IEC60601-2-47 Standard. These standards are being updated, but they rely on a very limited set of digitized ECG recordings from a couple of ECG databases built in the first half of the 70's. These reference signals are obsolete. We are developing a validation tool for computerized methods designed to detect and monitor cardiac activities based on body-surface ECGs. We will rely on a set of existing digital high-resolution 12‑lead A-ECG recordings acquired in cardiac patients and healthy individuals. These ECG signals include a large and unique set of electrocardiographic events. This tool is being qualified by the Center for Devices and Radiological Health of the United States Food and Drug Administration (FDA) as a Medical Device Development Tool (MDDT). This document provides insights into the design of the M.A.D.A.E. database, its functionalities, and its ultimate role in enabling the next generations of automatic interpretation of ECG signals.

This paper is based on a presentation held at the Annual Safety Pharmacology Society meeting in September 2017, at which challenges for the clinical component of CiPA were presented. FDA has published an automated algorithm for measurement of the J-Tpeak interval on a median beat from a vector magnitude lead derived from a 12-lead ECG. CiPA proposes that J-Tpeak prolongation 10 ms can be used for drugs with a QTc effect 20 ms to differentiate between safe and unsafe delayed repolarization and to reduce the level of ECG monitoring in late stage clinical trials.We applied FDA's algorithm, complemented with iCOMPAS, to moxifloxacin and dolasetron data from the IQ-CSRC study with 9 subjects on active and 6 on placebo. The effect on QTcF and corrected J-Tpeak (J-Tpeak_c) was analyzed using concentration-effect modeling.There was a good correlation between QTcF and J-Tpeak_c prolongation after oral dosing of 400 mg moxifloxacin with placebo-adjusted, change-from-baseline (ΔΔ) J-Tpeak_c of ~12 ms at concentrations that caused ΔΔQTcF of ~20 ms. On dolasetron, J-Tpeak_c was highly variable, no prolongation was seen and an effect on ΔΔJ-Tpeak_c 10 ms could be excluded across the observed plasma concentration range.In this limited analysis performed on the IQ-CSRC study waveforms using FDA's automated algorithm, J-Tpeak prolongation was observed on moxifloxacin, but not on dolasetron, despite clinical observations of proarrhythmias with both drugs. Challenges for the implementation of the J-Tpeak interval as a replacement or complement to the QTc interval, include to demonstrate that the proposed clinical algorithm using a J-Tpeak threshold of 10 ms, can be used to categorize drugs with a QT effect up to ~20 ms as having low pro-arrhythmic risk.

Background Cardiac Resynchronization Therapy (CRT) is widely used for treating selected heart failure patients, but patients with myocardial scar respond worse to treatment. The Selvester QRS scoring system estimates myocardial scar burden using 12-lead ECG. This study's objective was to investigate the scores correlation to mortality in a CRT population. Methods and results Data on consecutive CRT patients was collected. 401 patients with LBBB and available ECG data were included in the study. QuAReSS software was used to perform Selvester scoring. Mean Selvester score was 6.4, corresponding to 19% scar burden. The endpoint was death or heart transplant; outcome was analyzed using Cox proportional hazards models. A Selvester score > 8 was significantly associated with higher risk of the combined endpoint (HR 1.59, p = .014, CI 1.09–2.3). Conclusion Higher Selvester scores correlate to mortality in CRT patients with strict LBBB and might be of value in prognosticating survival.

Introduction Sleep disordered breathing (SDB) is associated with increased mortality. Obstructive apneas/hypopneas have been associated with an increase in both QTc duration and QT variability. These markers of ventricular repolarization are associated with arrhythmias and death. It is unknown whether SDB-related QTc changes are responsible for the relationship between QTc/QT variability and cardiovascular death (CVD). Methods From the Sleep Heart Health Study, we randomly selected 200 subjects in each of four groups based on overall apnea/hypopnea index: those with no SDB and those in either, mild, moderate or severe SDB at baseline, matched for gender, age and BMI. Respiratory-related channels and electrocardiograms (ECG) from each polysomnography were analyzed. QTc was calculated using Bazett’s heart rate correction. The following measures of QT variability were obtained: i) standard deviation of QT intervals (SDQT) at 1- and 5-minute intervals and ii) short-term interval QT variability (STVQT) at 5-minute intervals. Cox proportional hazards regression models were used to evaluate potential predictors of CVD. Results Twenty-nine subjects were excluded either due to missing data or low quality ECG. The 771 subjects included were 68±10 years of age, half were female. During follow-up, 220 subjects (28.5%) died of CVD among whom, 67 (30.5%) had comorbid severe SDB, 45 (20.5%) had no SDB, and the remaining CVD deaths had mild (47, 21.4%) and moderate 61 (27.7%) SDB. The CVD patients were more likely to be older(p Conclusion SDB was not a factor in the relationship between QTc prolongation/QT variability and CVD. Support (if any) American Academy of Sleep Medicine Foundation (203-JF-18), National Institutes of Health (HL126140), University of Arizona Health Sciences Career and Development Award (5299903)

The JTp interval gained interest as a marker differentiating effects of drugs on cardiac ion channels. For JTp interval, both the beginning - identification of J point and identification of T wave end remains the subject of substantial variability. We aimed to analyze diagnostic and prognostic performance of JTp interval in the International LQTS Registry data. ECGs from 804 gene carriers and 1139 non-carriers from LQT1 families, 735 carriers and 1145 non-carriers from LQT2 families, and 238 carriers and 554 non-carriers from LQT3 families were evaluated. The diagnostic performance of JTpc was similar to QTc in LQT1 and LQT3 patients but inferior in LQT2 patients, whereas repolarization duration in general had limited diagnostic performance in LQT3 patients. The prognostic significance for predicting cardiac events in LQT1 and LQT2 patients was similar for JTpc and QTc. In LQT3 patients, JTpc fails to be associated with arrhythmic events.

Aims To test the value of Periodic Repolarization Dynamics (PRD), a recently validated electrocardiographic marker of sympathetic activity, as a novel approach to predict sudden cardiac death (SCD) and non-sudden cardiac death (N-SCD) and to improve identification of patients that profit from ICD-implantation. Methods and results We included 856 post-infarction patients with left-ventricular ejection fraction (LVEF) ≤30% of the MADIT-II trial in sinus rhythm. Of these, 507 and 348 patients were randomized to ICD or conventional treatment. PRD was assessed from multipolar 10-min baseline ECGs. Primary and secondary endpoints were total mortality, SCD and N-SCD. Multivariable analyses included treatment group, QRS-duration, New York Heart Association classification, blood-urea nitrogen, diabetes mellitus, beta-blocker therapy and LVEF. During follow-up of 20.4 months, 119 patients died (53 SCD and 36 N-SCD). On multivariable analyses, increased PRD was a significant predictor of mortality (standardized coefficient 1.37[1.19–1.59]; P Conclusion In post-infarction patients with impaired LVEF, PRD is a significant predictor of SCD and N-SCD. Assessment of PRD is a promising tool to identify post-MI patients with reduced LVEF who might benefit from intensified treatment.

Item does not contain fulltext INTRODUCTION: We evaluated the association between a novel electrocardiographic (ECG) marker of late, rightward electrocardiographic forces (termed the lead one ratio [LOR]), and left ventricular ejection fraction (LVEF), myocardial scar, and clinical outcomes in patients with left bundle branch block (LBBB). METHODS AND RESULTS: LOR was calculated in patients with LBBB from a derivation cohort (n = 240) and receiver operator characteristic curves identified optimal threshold values for predicting myocardial scar and LVEF less than 35%. An independent validation cohort of patients with LBBB (n = 196) was used to test the association of LOR with the myocardial scar, LVEF, and the likelihood of death, heart transplant or left ventricular assist device (LVAD) implantation. The optimal thresholds in the derivation cohort were LOR less than 13.7 for identification of scar (sensitivity 55%, specificity 80%), and LOR less than 12.1 for LVEF less than 35% (sensitivity 49%, specificity 80%). In the validation cohort, LOR less than 13.7 was not associated with scar size or presence (P > 0.05 for both). LOR less than 12.1 was associated with lower LVEF (30 [20-40] versus 40 [25-55]%; P = 0.002) and predicted LVEF less than 35% in univariable (odds ratio [OR], 2.2 [1.2-4.1]; P = 0.01) and multivariable analysis (OR, 2.2 [1.2-4.3]; P = 0.02). LOR less than 12.1 was associated with scar presence when patients with nonischemic cardiomyopathy were excluded (OR = 7.2 [1.5-33.2]; P = 0.002). LOR less than 12.1 had an adjusted hazard ratio of 1.53 ([1.05-2.21]; P = 0.03) for death, transplant or LVAD implantation. CONCLUSIONS: In conclusion, ECG LOR less than 12.1 predicts reduced-LV systolic function and poorer prognosis in patients with LBBB.

Background The incidence of permanent pacemaker (PPM) implantation is higher following mitral valve surgery (MVS) with ablation for atrial fibrillation (AF) compared with MVS alone. Objectives This study identified risk factors and outcomes associated with PPM implantation in a randomized trial that evaluated ablation for AF in patients who underwent MVS. Methods A total of 243 patients with AF and without previous PPM placement were randomly assigned to MVS alone (n = 117) or MVS + ablation (n = 126). Patients in the ablation group were further randomized to pulmonary vein isolation (PVI) (n = 62) or the biatrial maze procedure (n = 64). Using competing risk models, this study examined the association among PPM and baseline and operative risk factors, and the effect of PPM on time to discharge, readmissions, and 1-year mortality. Results Thirty-five patients received a PPM within the first year (14.4%), 29 (83%) underwent implantation during the index hospitalization. The frequency of PPM implantation was 7.7% in patients randomized to MVS alone, 16.1% in MVS + PVI, and 25% in MVS + biatrial maze. The indications for PPM were similar among patients who underwent MVS with and without ablation. Ablation, multivalve surgery, and New York Heart Association functional (NYHA) functional class III/IV were independent risk factors for PPM implantation. Length of stay post-surgery was longer in patients who received PPMs, but it was not significant when adjusted for randomization assignment (MVS vs. ablation) and age (hazard ratio [HR]: 0.81; 95% confidence interval [CI]: 0.61 to 1.08; p = 0.14). PPM implantation did not increase 30-day readmission rate (HR: 1.43; 95% CI: 0.50 to 4.05; p = 0.50). The need for PPM was associated with a higher risk of 1-year mortality (HR: 3.21; 95% CI: 1.01 to 10.17; p = 0.05) after adjustment for randomization assignment, age, and NYHA functional class. Conclusions AF ablation, multivalve surgery, and NYHA functional class III/IV were associated with an increased risk for permanent pacing. PPM implantation following MVS was associated with a significant increase in 1-year mortality. (Surgical Ablation Versus No Surgical Ablation for Patients With Atrial Fibrillation Undergoing Mitral Valve Surgery; NCT00903370)

Epidemiologic evidence of an adverse association between exposure to methylmercury (MeHg) from consuming fish and heart rate variability (HRV) is inconclusive. We aimed to evaluate MeHg exposure in relation to HRV parameters in a large cohort of young adults from a high fish consuming population in the Republic of Seychelles. Main Cohort participants in the Seychelles Child Development Study were evaluated at a mean age of 19 years. Prenatal MeHg exposure was determined in maternal hair growing during pregnancy and recent exposure in participant’s hair taken at the evaluation. The evaluation consisted of short (~2 hours) and long (overnight) Holter recordings obtained in 514 and 203 participants, respectively. Multivariable analyses examined the association of prenatal and recent MeHg exposure (in separate models) with time-domain and frequency-domain HRV parameters in different physiologic circumstances: supine position, standing position, mental stress when undergoing a mathematics test, sleep, and long recording. Prenatal MeHg exposure was not associated with any of the 23 HRV parameters studied after adjustment for multiplicity. The recent MeHg showed a trend toward significance only for few variables in the primary model. However, after additional adjustment for activity levels, polyunsaturated fatty acids, and multiplicity none were significant after a Bonferroni adjustment. In conclusion, prenatal and recent MeHg exposure had no consistent pattern of associations to support the hypothesis that they are adversely associated with heart rate variability in this study population that consumes large amounts of fish.

Introduction The apneas and hypopneas that characterize sleep-disordered breathing (SDB) are associated with QTc prolongation and increased QT variability. There have been mixed results as to whether QTc and QT variability increase with increasing SDB severity. This study assesses whether QTc prolongation and QT variability are likely to increase with increasing severity of SDB in a large multi-center cohort. Methods 200 subjects with no SDB and approximately 600 with three levels of SDB (mild, moderate, severe) were randomly selected from the Sleep Heart Health study and matched by age, gender and BMI. SDB was defined as an apnea/hypopnea index ≥5. Respiratory and electrocardiograms (ECG) signals from polysomnography studies were analyzed. Bazett’s heart rate correction was used to calculate QTc. QT variability was measured as standard deviation of QT intervals (SDQT) and short-term interval QT variability (STVQT), at 5-minute intervals. Subjects were excluded if there were missing data or low-quality ECG. Results Seven hundred and seventy-one subjects (age 68±10 years, 51% female, 92% Caucasian) were included. One hundred and sixty-five subjects had no SDB, 235 mild, 195 moderate and 176 had severe SDB. The mean (SD) QTc was 422(29), 411(26), 419 (34) and 418 (36) ms for the no SDB, mild, moderate, and severe SDB groups, respectively (p=0.017). The mean (SD) STVQT was 7 (9), 11 (16), 8 (9) and 9 (11) for the no SDB, mild, moderate severe SDB groups, respectively (p= Conclusion QTc duration and QT variability were not increased with SDB severity. Support (if any) American Academy of Sleep Medicine Foundation (203-JF-18), National Institutes of Health (HL126140), University of Arizona Health Sciences Career Development Award (5299903), and University of Arizona Faculty Seed Grant (5833261)

Supplemental Digital Content is available in the text., This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society describes the current status of mobile health technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self-management are novel aspects of mobile health. The promises of predictive analytics but also operational challenges in embedding mobile health into routine clinical care are explored.

In-silico models of human cardiac electrophysiology are now being considered for prediction of cardiotoxicity as part of the preclinical assessment phase of all new drugs. We ask the question whether any of the available models are actually fit for this purpose. We tested three models of the human ventricular action potential, the O'hara-Rudy (ORD11), the Grandi-Bers (GB10) and the Ten Tusscher (TT06) models. We extracted clinical QT data for LQTS1 and LQTS2 patients with nonsense mutations that would be predicted to cause 50% loss of function in IKs and IKr respectively. We also obtained clinical QT data for LQTS3 patients. We then used a global optimization approach to improve the existing in silico models so that they reproduced all three clinical data sets more closely. We also examined the effects of adrenergic stimulation in the different LQTS subsets. All models, in their original form, produce markedly different and unrealistic predictions of QT prolongation for LQTS1, 2 and 3. After global optimization of the maximum conductances for membrane channels, all models have similar current densities during the action potential, despite differences in kinetic properties of the channels in the different models, and more closely reproduce the prolongation of repolarization seen in all LQTS subtypes. In-silico models of cardiac electrophysiology have the potential to be tremendously useful in complementing traditional preclinical drug testing studies. However, our results demonstrate they should be carefully validated and optimized to clinical data before they can be used for this purpose.

Background The QT interval is a risk marker for cardiac events such as torsades de pointes. However, QT measurements obtained from a 12-lead ECG during clinic hours may not capture the full extent of a patient's daily QT range. Objective The purpose of this study was to evaluate the utility of 24-hour Holter ECG recording in patients with long QT syndrome (LQTS) to identify dynamic changes in the heart rate–corrected QT interval and to investigate methods of visualizing the resulting datasets. Methods Beat-to-beat QTc (Bazett) intervals were automatically measured across 24-hour Holter recordings from 202 LQTS type 1, 89 type 2, and 14 type 3 genotyped patients and a reference group of 200 healthy individuals. We measured the percentage of beats with QTc greater than the gender-specific threshold (QTc ≥470 ms in women and QTc ≥450 ms in men). The percentage of beats with QTc prolongation was determined across the 24-hour recordings. Results Based on the median percentage of heartbeats per patient with QTc prolongation, LQTS type 1 patients showed more frequent QTc prolongation during the day (~3 PM) than they did at night (~3 AM): 97% vs 48%, P ~10 –4 for men, and 68% vs 30%, P ~10 –5 for women. LQTS type 2 patients showed less frequent QTc prolongation during the day compared to nighttime: 87% vs 100%, P ~10 –4 for men, and 62% vs 100%, P ~10 –3 for women. Conclusion In patients with genotype-positive LQTS, significant differences exist in the degree of daytime and nocturnal QTc prolongation. Holter monitoring using the "QT clock" concept may provide an easy, fast, and accurate method for assessing the true personalized burden of QTc prolongation.

Introduction Patients with untreated obstructive sleep apnea (OSA) have a 2-3—fold increased risk of cardiovascular mortality (CVD) compared with individuals without OSA. QTc prolongation and increased QT variability among OSA patients may contribute to this association. Methods Patients with OSA from the Sleep Heart Health study were identified based on polysomnography criteria and their continuous electrocardiograms (ECG) analyzed for QTc duration and QT variability. Both Fridericia’s and Bazett’s heart rate corrections were used to calculate QTc. QT variability was measured as standard deviation of QT intervals (SDQT) and normalized QT interval variance (QTVN) at 1- and 5-minute intervals and short-term interval beat-to-beat QT variability (STVQT) was measured at 5-minute intervals. Lasso with elastic-net regularization was used as the variable/covariate selection method. Cox proportional hazards regression models were used to determine predictors of CVD. Results Data from 365 patients with OSA were screened. Ninety-seven patients were excluded from analysis due to low quality ECG data (n=50) or extremely high (> ln (10)) variability in QT/QTc and/or QT variability (n=12). Fifty two percent of the sample was male with mean age 65 years (±10). Fifty-six of these patients died of CVD. The mean (SD) QTc in the group that died was 411 (30) ms and 416 (34) ms compared to 406 (24) ms and 411 (25) ms using Fridericia (Cox LR p-value 0.055) and Bazett (p=0.090), respectively. Gender, age, race, diabetes, SDQT and STVQT were significant predictors for CVD. We fit models with the covariates and SDQT (at both 1 and 5 min) and STVQT as three models and demonstrate that both SDQT and STVQT are significantly associated with CVD death (p-values of 0.0048, 0.0089, and 0.0113, respectively) and all models had high area under the curve (0.8095, 0.8085, and 0.8125, respectively). Conclusion In patients with OSA, QT variability was associated with CVD. Support American Academy of Sleep Medicine Foundation

The presence of left bundle branch block (LBBB) is an important predictor of benefit from cardiac resynchronization therapy (CRT). New “strict” electrocardiographic (ECG) criteria for LBBB have been shown to better predict benefit from CRT. The “strict” LBBB criteria include: QRS duration ≥140 ms (men) or ≥130 ms (women), QS- or rS-configurations of the QRS complex in leads V1 and V2, and mid-QRS notching or slurring in ≥2 of leads V1, V2, V5, V6, I and aVL. The “strict” LBBB criteria are not regularly used and most hospital automated ECG systems and physicians still use more conventional LBBB criteria. As part of the 43rd International Society for Computerized Electrocardiology (ISCE) meeting, we conducted an initiative on the automated detection of “strict” LBBB where industry and academic investigators could present their algorithm results on digital 12-lead ECGs with varying QRS morphologies from the MADIT-CRT trial (300 training and 302 test set ECGs that were manually adjudicated for “strict” LBBB presence). The results revealed a 64–82% accuracy, 48–76% sensitivity and 46–87% specificity for automated “strict” LBBB detection from 7 participants. Most mismatches were likely attributed to differences in detection and absence of specific definitions for notches and slurs while differences in QRS duration and S-waves in leads V1 and V2 were less problematic. The full unblinded training and test datasets including all ECG signals are being made available through the Telemetric and Holter ECG Warehouse (THEW) for further exploration.

INTRODUCTION Adverse electrical remodeling (AER), represented here as the sum absolute QRST integral (SAI QRST), has previously been shown to be directly associated with the risk for ventricular arrhythmia (VA). Cardiac resynchronization therapy (CRT) is known to reduce the risk for VA through various mechanisms, including reverse remodeling, and we aimed to evaluate the association between baseline AER and the risk for VA in CRT recipients. METHODS AND RESULTS The study population comprised 961 CRT-D implanted patients from the MADIT CRT study. The relationship between SAI QRST, VA risk, and VA risk/death was evaluated as a continuous and as a categorical variable-tertiles (T1 ≤ 0.527, T2 0.528-0.766, T3 > 0.766). In a multivariable model, AER was inversely associated with the risk of VA. Each unit increase in SAI QRST was associated with 64% (P = 0.007) and 54% (P = 0.003) decrease in the risk of VA and VA/death, respectively. Patients with high SAI QRST (T3) and medium SAI QRST (T2) had 52% (P

Item does not contain fulltext AIMS: We aimed to improve the electrocardiographic 2009 left bundle branch block (LBBB) Selvester QRS score (2009 LBSS) for scar assessment. METHODS: We retrospectively identified 325 LBBB patients with available ECG and cardiovascular magnetic resonance imaging (CMR) with late gadolinium enhancement from four centers (142 [44%] with CMR scar). Forty-four semi-automatically measured ECG variables pre-selected based on the 2009 LBSS yielded one multivariable model for scar detection and another for scar quantification. RESULTS: The 2009 LBSS achieved an area under the curve (AUC) of 0.60 (95% confidence interval 0.54-0.66) for scar detection, and R(2)=0.04, p

Background Estimation of the infarct size from body-surface ECGs in post-myocardial infarction patients has become possible using the Selvester scoring method. Automation of this scoring has been proposed in order to speed-up the measurement of the score and improving the inter-observer variability in computing a score that requires strong expertise in electrocardiography. In this work, we evaluated the quality of the QuAReSS software for delivering correct Selvester scoring in a set of standard 12-lead ECGs. Method Standard 12-lead ECGs were recorded in 105 post-MI patients prescribed implantation of an implantable cardiodefibrillator (ICD). Amongst the 105 patients with standard clinical left bundle branch block (LBBB) patterns, 67 had a LBBB pattern meeting the strict criteria. The QuAReSS software was applied to these 67 tracings by two independent groups of cardiologists (from a clinical group and an ECG core laboratory) to measure the Selvester score semi-automatically. Using various level of agreement metrics, we compared the scores between groups and when automatically measured by the software. Results The average of the absolute difference in Selvester scores measured by the two independent groups was 1.4 ± 1.5 score points, whereas the difference between automatic method and the two manual adjudications were 1.2 ± 1.2 and 1.3 ± 1.2 points. Eighty-two percent score agreement was observed between the two independent measurements when the difference of score was within two point ranges, while 90% and 84% score agreements were reached using the automatic method compared to the two manual adjudications. Conclusion The study confirms that the QuAReSS software provides valid measurements of the Selvester score in patients with strict LBBB with minimal correction from cardiologists.