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Background In the awakening era of mobile health, wearables equipped with photoplethysmography (PPG) technology to monitor the heart rate (HR) and rhythm are on the rise. Smartwatches and wristbands enable HR monitoring for consumers at massive scale. Unfortunately, once consumers become patients, physicians are limited by insufficient evidence to support the clinical use of PPG based wearables. Accurate identification of heartbeats is the first step in the interpretation of PPG traces and should be validated. Purpose To assess the agreement between continuous PPG monitoring using a smartwatch and continuous ECG Holter monitoring in the identification of heartbeats and calculation of the HR. Methods One hundred patients (≥18 years) without a pacemaker-dependent heart rhythm who were referred to a university hospital and a large tertiary hospital for elective 24-hour ECG Holter monitoring were asked to wear a continuous PPG monitoring smartwatch (i.e. Samsung GWA2 or Empatica E4) simultaneously with the 24-hour Holter monitor. All activities of daily life were allowed. The ECG trace and PPG waveform were synchronised and fragmented in one-minute fragments. The one-minute ECG fragments were labelled as AF, non-AF, or insufficient quality based on the routine clinical interpretation (i.e. software + physician overreading), and the average HR during each fragment was calculated by Holter algorithm. The PPG fragments were analysed by an artificial intelligence (AI) algorithm (i.e. FibriCheck) that labelled fragments as sufficient or insufficient quality, identified the number of heartbeats and calculated the HR. The agreement between the HR on ECG and PPG in sufficient quality tracings was analysed with linear regression, Pearson's product-moment correlation and Bland-Altman analysis. A subanalysis was performed for AF rhythm and non-AF rhythms. Results A total of 72,725 simultaneous ECG and PPG one-minute fragments were recorded in 96 patients, after excluding 4 patients (due to 3 Holter and 1 smartwatch technical error) and 42,520 minutes (36.9%) of insufficient quality (ECG 1,454 (1.3%); PPG 25,704 (22.3%), ECG and PPG 15,362 (13.3%)). The correlation (r=0.935) between ECG and PPG HR was statistically significant (CI 0.934–0.936; P Conclusion The AI algorithm analysing continuous out-of-hospital PPG tracings can annotate heartbeats and assess HR without a clinically significant bias compared to continuous ECG monitoring, both during AF and non-AF rhythms in a heterogenous patient population. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Research Foundation-Flanders, Strategic Basic Research Fund Correlation plot & Bland-Altman plot

Introduction Atrial fibrillation (AF) is the most common arrhythmia and is associated with high risk of morbidity and mortality. In many patients, AF is of episodic character (paroxysmal AF – PAF), which makes the identification of these patients during sinus rhythm (SR) challenging. Purpose The aim of the present study is to compare the performance of beat-to-beat P-wave analysis with P-wave indices used as predictors of PAF, such as P-wave duration, area, voltage, axis, terminal force in V1, inter-atrial block or orthogonal type, in identifying patients with history of PAF during sinus rhythm. Methods Standard 12-lead ECG and 10-minute orthogonal ECG recordings were obtained from 40 consecutive patients with short history of PAF under no antiarrhythmic medication and 60 age- and sex- matched healthy controls. The P-waves on the 10-minute recordings were analyzed on a beat-to-beat basis and classified as belonging to a primary or secondary morphology according to previous study. Wavelet transform used to further analyze P-wave orthogonal signals of main morphology on a beat-to-beat basis. Results 38 out of 327 studied features were found to differ significantly among the two groups. These features were tested for their diagnostic ability and receiver operating characteristic curves were ploted. Only 3 of them performed adequetly, with an area under curve (AUC) above 0.65; Two of them came from morphology analysis (percentage of beats following main morphology in axis X and Y) and one from wavelet analysis (max energy in high frequency zone -Y axis). Among standard P-wave indices, P-wave area in lead II was the one with the highest AUC (0.64). Conclusion Novel indices derived from beat-to-beat analysis outperform stadard P-wave markers in identifying patients with PAF history during sinus rhythm. Funding Acknowledgement Type of funding sources: None. ROC curves of most significant featuresAUC characteristics of P-wave indices

Background The rapid irregular atrial electrical activity during atrial fibrillation (AF) is associated with an irregular and variable left ventricular (LV) systolic pump function. The effects of cycle length (CL) variations on LV function during AF remain incompletely understood. Purpose To elucidate the physiological mechanisms by which beat-to-beat changes in cycle length affect LV function during AF. We hypothesize that changes in LV preload and afterload cause a large part of the beat-to-beat variability of LV function during AF. Methods Beat-to-beat speckle-tracking echocardiography was performed in 10 patients with persistent AF. In each patient, a hundred consecutive beats were imaged during AF and we evaluated the relation between longitudinal strain in the image plane (4-chamber view) and (pre-)preceding CL in these patients. We used the CircAdapt cardiovascular system model to simulate cardiac mechanics and hemodynamics during AF for each individual patient 1) by imposing the exact irregular sequence of CLs as measured in the patient and 2) by making the atrial myocardium non-contractile. We also simulated generic (i.e. artificially defined) CL sequences (e.g. irregular long CL, irregular short CL) to better understand the determinants of beat-to-beat variations of LV systolic function during AF. Results Generic simulations uncovered the hemodynamic effects of a sudden irregular long or short beat on LV function during the following beat (top). A short beat led to lower LV function in the following beat because of smaller preload, while a longer beat led to larger LV function by Frank-Starling law of contractile myocardium. This CL dependency of LV function was confirmed when analysing clinical data of AF patients (bottom, left). A negative non-linear relation between preceding CL and longitudinal strain was observed (bottom, right). Increased longitudinal strain at high preceding CL (purple box) was explained by a higher preceding EDV (higher preload) (p Conclusions Irregularity in preceding CL leads to changes in LV function through preload and afterload changes. Indeed, as observed in patients during AF, longitudinal LV strain depends non-linearly on the preceding CL. Beat-to-beat changes in preload contribute to variable LV function but changes in afterload also are a key determinant of LV function variability at same preceding CL. Our combined clinical-computational study highlights the variability in longitudinal strain measurement during AF and provides new insight into the physiological mechanisms determining LV function in AF patients. Determinants of LV function in AF Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): NWO-ZonMw, VIDI grant 016.176.340

Background Direct oral anticoagulants (DOACs) have a similar efficacy in terms of stroke and mortality reduction as compared to Vitamin K-Antagonists (VKAs) and improved safety with regards to intracranial haemorrhage in patients with non-valvular atrial fibrillation (AF). Dose of DOACs needs to be adjusted according to age, weight, renal function and concomitant medication. Yet, off-label dosages have been reported in 11 - 45% of patients (on average 20%). Purpose To assess the prevalence of inappropriate DOAC-dosing according to the official prescribing information in two large prospective Swiss AF cohorts (Swiss-AF and BEAT-AF) and to evaluate its correlation with adverse clinical outcomes. Methods All 3267 patients taking oral anticoagulants were stratified at baseline as receiving DOACs (adequately dosed, under- or overdosed) or VKAs. Appropriateness of DOAC dosing was assessed based on age (≥80 years), weight (≤60kg) and renal function (serum creatinine ≥133μmol/l [apixaban]; creatinine clearence ≤50ml/min [all other DOACs]). Clinical outcomes were collected during a median follow-up of 2.96 years. Major adverse clinical events (MACE) consisted of a combination of myocardial infarction, cardiac death, ischemic stroke and systemic embolism. Safety was assessed by occurrence of any bleeding event. Results 1902 patients (58%) were on VKAs and 1365 on DOACs (42%). In the DOAC group, 1149 patients received a dose consistent with drug labelling (84%), 133 (10%) received an inappropriately high and 83 (6%) an inappropriately low dose. Overdosed patients were older than those adequately treated and more likely female, had a lower BMI and a higher CHA2DS2-VASc score (4 vs. 3 points) (p Figure 1. Kaplan-Meier incidence curves Conclusion Inadequate DOACs dosing was found in 1 in 6 patients and correlated with a higher burden of comorbidities at baseline. Underdosing correlated with concomitant antiplatelet therapy. Overdosing was associated with adverse clinical outcome for ischemic and bleeding events.

Rapid atrial pacing is effective in terminating atrial flutter, but often results in transient or permanent atrial fibrillation rather than sinus rhythm. Class Ia antiarrhythmic drugs have earlier been shown to facilitate the direct conversion of atrial flutter to sinus rhythm. The present study was performed to test the hypothesis that flecainide, a group 1c antiarrhythmic drug, increases the direct conversion to sinus rhythm. In a series of 30 consecutive clinical episodes of atrial flutter treated with rapid atrial pacing, 12 episodes were in patients on flecainide treatment (group A), while in 13 episodes no patients were on group 1 antiarrhythmic drugs (group B). Direct conversion to sinus rhythm was achieved more often in group A (75%) than in group B (31%) P = 0.034. Both the flutter rates and the pacing rates used were lower in group A, 240 vs 280 beat. Min−1 and 375 vs 430 b. min−1, respectively. Patients with atrial flutter in whom rapid atrial pacing is to be performed should be considered for pretreatment with flecainide.

Aim: As acute short-lived increase in afterload may be a contributory mechanism to sudden death, we studied an acute 30% systolic pressure increase (SBPI) in a closed chest, closed pericardium porcine model, closed pericardium being essential to the model clinical applicability. Methods: 7 pigs were studied. All had an acute 5 beat 30% SBPI induced by a non-occlusive mid- descending aortic balloon inflation and release. Each challenge was continuously monitored for changes in cardiac morphology and function by cardiac ultrasound (2D, Doppler and Doppler Myocardial Imaging) and changes were correlated with pressure data from 3 Millar catheters (LV/Ao ; LA ; RV/RA). Continuous 12 lead ECG and intracardiac electrograms were also recorded. Results: Balloon inflation caused an acute diastolic pressure increase in all cavities (except pulmonary artery) with early diastolic preceding late changes and a corresponding systolic increase in LV, LA and RA pressures. Acute LV dilatation resulted in pericardial flattening (which is a visualization of the effects of pericardial constraint), a septal shift towards the RV and a decrease in RV size with a 30% reduction in LVEF % (Fig1a). During inflation, pericardial excursion flattened > 40% in basal, mid and apical LV segments, mostly mid wall (from 3.4±1.4 mm to 1.6±0.7 mm, p

In order to establish normal limits for mean 24 h heart rate ( H R ¯ t and pauses, 24 h ambulatory ECG recordings from 260 healthy subjects 40–79 years of age were analysed. The H R ¯ 24h varied from 53 to 95 beats/min (mean±2 s.d.: 74±I8 beats/min). The minimal H R ¯ t varied from 36 to 78 beats/min (mean± 2 s.d.: 56 ±16 beats/min). Analysis of variance showed an additive effect of smoking, sex, leisure-time physical activity and age on both H R ¯ t, and the effect of the three first factors was statistical significant at the 1% level for both heart rate variables. The males, the non-smokers and the physically active subjects had a lower H R ¯ 24h and a lower minimal H R ¯ t than females, smokers and passive subjects. Older subjects had a lower H R ¯ t was non-significant. A total of 77 subjects (30%) had a pause (R-R interval≥1500 ms), but in only 12 (5%) did the pause exceed 1750 ms with the longest pause measuring 2040 ms. Further analysis of the longest pause in each of the 77 subjects with pauses showed that 46 of the longest pauses occurred at night following a gradual decrease in the R-R intervals for a few beats (‘post-acceleration pauses’). In 12 subjects the longest pause was caused by sinus arrest, and in nine cases a blocked atrial premature beat was thought to be present. Wenckebach A- V block was seen in only two subjects. It is concluded that sex, age, smoking and leisure-time physical activity are all factors that have to be considered for a thorough evaluation of heart rate variables in the 24 h ambulatory ECG.

Automatic analysis of heart rate variability from Holter recordings may be invalidated by beat recognition errors and recording artefact, necessitating filtering and editing of the computer-recognized RR interval sequence. Two new methods for heart rate variability analysis have been developed, based on an estimation of the width of the main peak of the frequency distribution curve of the computer-recognized normal-to-normal beat sequence. These methods are independent of a low level of recognition error and artefact, thus removing the need for operator-dependent, time-consuming editing. The value of the new methods (heart variability indices 1 and 2) in identifying patients with serious events (death and symptomatic, sustained documented ventricular tachycardia) during a 6-month follow-up after acute myocardial infarction was assessed in a case-control study comparing 20 patients who had experienced such events (Group I) with 20 patients who, following admission with acute myocardial infarction, had remained free of complications for greater than 6 months after discharge (Group II). Group II was selected to match Group I with regard to age, sex, infarct site, ejection fraction, and beta-blocker treatment. Analysis of the unfiltered computer-recognized normal-to-normal interval sequence showed that heart rate variability indices 1 and 2 were significantly lower (P less than 0.005, P less than 0.002) in those who had experienced events compared with those free from complications. Two other methods of expressing heart rate variability, including the standard deviation method, in combination with four different data-filtering techniques, gave less significant distinction between those with and without events during follow-up. It is concluded that using the methods described, reduced heart rate variability in patients at risk from death or sustained ventricular tachycardia after acute myocardial infarction can be detected automatically from unfiltered Holter tape recordings even in the presence of a low level of beat recognition error and recording artefact.