Day-to-day measurement of physical activity and risk of atrial fibrillation.

AIMS: The aim of this study was to investigate the association between within-individual changes in physical activity and onset of atrial fibrillation (AF). METHODS AND RESULTS: A total of 1410 participants from the general population (46.2% women, mean age 74.7 ± 4.1 years) with risk factors but with no prior AF diagnosis underwent continuous monitoring for AF episodes along with daily accelerometric assessment of physical activity using an implantable loop recorder during ≈3.5 years. The combined duration of monitoring was ≈1.6 million days, where 10 851 AF episodes lasting ≥60 min were detected in 361 participants (25.6%) with a median of 5 episodes (2, 25) each. The median daily physical activity was 112 (66, 168) min/day. A dynamic parameter describing within-individual changes in daily physical activity, i.e. average daily activity in the last week compared to the previous 100 days, was computed and used to model the onset of AF. A 1-h decrease in average daily physical activity was associated with AF onset the next day [odds ratio 1.24 (1.18-1.31)]. This effect was modified by overall level of activity (P < 0.001 for interaction), and the signal was strongest in the tertile of participants with lowest activity overall [low: 1.62 (1.41-1.86), mid: 1.27 (1.16-1.39), and high: 1.10 (1.01-1.19)]. CONCLUSIONS: Within-individual changes in physical activity are associated with the onset of AF episodes as detected by continuous monitoring in a high-risk population. For each person, a 1-h decrease in daily physical activity during the last week increased the odds of AF onset the next day by ≈25%, while the strongest association was seen in the group with the lowest activity overall. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, identifier: NCT02036450.

Incidence and risk factors for first and recurrent ICD shock therapy in patients with an implantable cardioverter defibrillator.

BACKGROUND: Advances in medical treatment and outcomes in implantable cardioverter-defibrillator (ICD) recipients incentivize a need for improved candidate selection and identification of risk factors for ICD therapy. We examined contemporary rates of and risk factors for ICD therapy. METHODS: Patients with ICD for primary (PP) or secondary prevention (SP), implanted between January 2010 and December 2020, were followed for appropriate and inappropriate incident and recurrent shock. RESULTS: Overall, 2998 patients (mean age 61.8 ± 12.7 years, 20% female, 73% ICD carriers, and 47.1% SP) were analyzed with a median follow-up of 4.3 (interquartile range (IQR) 2.1-7.4) years. A total of 426/2998 (14.2%) patients had shock; 364/2998 (12.1%) had appropriate and 82/2998 (2.7%) inappropriate shock, with annualized event rates of 2.34 (2.11-2.59) and 0.49 (0.39-0.61) per 100 person-years, respectively. Of those with shock, 133/364 (36.5%) experienced recurrent appropriate shock and 8/364 (2.2%) received recurrent inappropriate shock, with event rates of 10.57 (8.85-12.53) and 0.46 (0.20-0.92), respectively. In multivariable analyses, female sex was associated with a reduced risk of incident appropriate shock (hazard ratio 0.69 [95% confidence interval 0.52; 0.91]). Of other variables, only revascularization status was associated with recurrent appropriate shock in PP, and CRT-D with recurrent appropriate shock in the overall cohort. CONCLUSION: One in eight ICD recipients received appropriate shock 2-7 years after guideline-directed implantation. More than one-third of patients with a first shock experienced recurrent shock. Few clinical variables showed potential in predicting shocks, illustrating a need for more advanced tools to select candidates for implantation.

Deep behavioural representation learning reveals risk profiles for malignant ventricular arrhythmias.

We aimed to identify and characterise behavioural profiles in patients at high risk of SCD, by using deep representation learning of day-to-day behavioural recordings. We present a pipeline that employed unsupervised clustering on low-dimensional representations of behavioural time-series data learned by a convolutional residual variational neural network (ResNet-VAE). Data from the prospective, observational SafeHeart study conducted at two large tertiary university centers in the Netherlands and Denmark were used. Patients received an implantable cardioverter-defibrillator (ICD) between May 2021 and September 2022 and wore wearable devices using accelerometer technology during 180 consecutive days. A total of 272 patients (mean age of 63.1 ± 10.2 years, 81% male) were eligible with a total sampling of 37,478 days of behavioural data (138 ± 47 days per patient). Deep representation learning identified five distinct behavioural profiles: Cluster A (n = 46) had very low physical activity levels and a disturbed sleep pattern. Cluster B (n = 70) had high activity levels, mainly at light-to-moderate intensity. Cluster C (n = 63) exhibited a high-intensity activity profile. Cluster D (n = 51) showed above-average sleep efficiency. Cluster E (n = 42) had frequent waking episodes and poor sleep. Annual risks of malignant ventricular arrhythmias ranged from 30.4% in Cluster A to 9.8% and 9.5% for Clusters D-E, respectively. Compared to low-risk profiles (D-E), Cluster A demonstrated a three-to-four fold increased risk of malignant ventricular arrhythmias adjusted for clinical covariates (adjusted HR 3.63, 95% CI 1.54-8.53, p < 0.001). These behavioural profiles may guide more personalised approaches to ventricular arrhythmia and SCD prevention.

Long-term adherence to a wearable for continuous behavioural activity measuring in the SafeHeart implantable cardioverter defibrillator population.

Aims: Wearable health technologies are increasingly popular. Yet, wearable monitoring only works when devices are worn as intended, and adherence reporting lacks standardization. In this study, we aimed to explore the long-term adherence to a wrist-worn activity tracker in the prospective SafeHeart study and identify patient characteristics associated with adherence. Methods and results: This study enrolled 303 participants, instructed to wear a wrist-worn accelerometer day and night for 6 months. Long-term adherence was defined as valid days (≥22 h of wear time) divided by expected days, and daily adherence as mean hours of wear time per 24 h period. Optimal, moderate, and low long-term and daily adherence groups were defined as long-term adherence above or below 95 and 75% and daily adherence above or below 90 and 75%. Regression models were used to identify patient characteristics associated with long-term adherence. In total, 296 participants [median age 64 years; interquartile range (IQR) 57-72; 19% female] were found eligible, yielding 44 003 days for analysis. The median long-term adherence was 88.2% (IQR 74.6-96.5%). A total of 83 (28%), 127 (42.9%), and 86 (29.1%) participants had optimal, moderate, and low long-term adherence, and 163 (55.1%), 87 (29.4%), and 46 (15.5%) had optimal, moderate, and low daily adherence, respectively. Age and smoking habits differed significantly between adherence levels, and increasing changeover intervals improved the degree of long-term adherence. Conclusion: Long-term adherence to a wearable activity tracker was 88.2% over a 6-month period. Older age and longer changeover interval were positively associated with long-term adherence. This serves as a benchmark for future studies that rely on wearable devices. Trial registration number: The National Trial Registration number: NL9218 (https://onderzoekmetmensen.nl/).

Effects of atrial fibrillation screening according to thyroid function: Post-hoc analysis of the randomized LOOP study.

PURPOSE: Subclinical thyroid dysfunction is a marker for atrial fibrillation (AF) and stroke risk. This study explored the effects of AF screening according to thyroid-stimulating hormone (TSH) levels. METHODS: An AF screening trial (the LOOP study) was analyzed post-hoc according to baseline TSH. The primary outcome was stroke or systemic embolism (SE). Secondary outcomes included major bleeding, all-cause death, and the combination of stroke, SE, and cardiovascular death. RESULTS: TSH measurement was available in 6003 of 6004 trial participants, 1500 randomized to implantable loop recorder (ILR) screening for AF and anticoagulation upon detection vs. 4503 to usual care; mean age was 74.7±4.1 years and 2836 (47%) were women. AF detection was approximately triple for ILR vs usual care across TSH tertiles (adjusted p-interaction=0.44). In the first tertile, screening was associated with decreased risk of the primary outcome (hazard ratio 0.52 [0.30-0.90]; p=0.02) and stroke, SE, or cardiovascular death (hazard ratio 0.54 [0.34-0.84]; p=0.006) compared to usual care, while no effect was observed among participants with higher TSH (adjusted p-interaction 0.03 and 0.01, respectively). There was no effect on other outcomes. Analyses of continuous TSH or excluding those with abnormal TSH or thyroid medication showed similar results. CONCLUSION: AF screening and subsequent treatment was associated with decreased stroke risk among participants with low TSH, though the yield of screening was similar across TSH levels. TSH may be useful as a marker to indicate benefit from AF screening vs. overdiagnosis and overtreatment. These findings should be considered exploratory and warrant further study. TRIAL REGISTRATION: ClinicalTrials.gov, identifier: NCT0203645.

Prevalence and Prognostic Significance of Bradyarrhythmias in Patients Screened for Atrial Fibrillation vs Usual Care: Post Hoc Analysis of the LOOP Randomized Clinical Trial.

Importance: There is increasing interest in heart rhythm monitoring and technologies to detect subclinical atrial fibrillation (AF), which may lead to incidental diagnosis of bradyarrhythmias. Objective: To assess bradyarrhythmia prevalence and prognostic significance in persons screened for AF using implantable loop recorder (ILR) compared with unscreened persons. Design, Setting, and Participants: This was a post hoc analysis of the Implantable Loop Recorder Detection of Atrial Fibrillation to Prevent Stroke (LOOP) randomized clinical trial, which took place in 4 sites in Denmark. Participants were 70 years or older without known AF but diagnosed with at least 1 of the following: hypertension, diabetes, heart failure, or prior stroke. Participants were recruited by letter invitation between January 31, 2014, and May 17, 2016. The median (IQR) follow-up period was 65 (59-70) months. Analysis took place between February and June 2022. Interventions: ILR screening for AF with treatment of any bradyarrhythmia left to the discretion of the treating physician (ILR group) vs usual care (control group). Main Outcomes and Measures: Adjudicated bradyarrhythmia episodes, pacemaker implantation, syncope, and sudden cardiovascular death. Results: A total of 6004 participants were randomized (mean [SD] age, 75 [4.1] years; 2837 [47.3%] female; 5444 [90.7%] with hypertension; 1224 [20.4%] with prior syncope), 4503 to control and 1501 to ILR. Bradyarrhythmia was diagnosed in 172 participants (3.8%) in the control group vs 312 participants (20.8%) in the ILR group (hazard ratio [HR], 6.21 [95% CI, 5.15-7.48]; P < .001), and these were asymptomatic in 41 participants (23.8%) vs 249 participants (79.8%), respectively. The most common bradyarrhythmia was sinus node dysfunction followed by high-grade atrioventricular block. Risk factors for bradyarrhythmia included higher age, male sex, and prior syncope. A pacemaker was implanted in 132 participants (2.9%) vs 67 (4.5%) (HR, 1.53 [95% CI, 1.14-2.06]; P < .001), syncope occurred in 120 (2.7%) vs 33 (2.2%) (HR, 0.83 [95% CI, 0.56-1.22]; P = .34), and sudden cardiovascular death occurred in 49 (1.1%) vs 18 (1.2%) (HR, 1.11 [95% CI, 0.64-1.90]; P = .71) in the control and ILR groups, respectively. Bradyarrhythmias were associated with subsequent syncope, cardiovascular death, and all-cause death, with no interaction between bradyarrhythmia and randomization group. Conclusions and Relevance: More than 1 in 5 persons older than 70 years with cardiovascular risk factors can be diagnosed with bradyarrhythmias when long-term continous monitoring for AF is applied. In this study, ILR screening led to a 6-fold increase in bradyarrhythmia diagnoses and a significant increase in pacemaker implantations compared with usual care but no change in the risk of syncope or sudden death.

Using Consumer-Wearable Activity Trackers for Risk Prediction of Life-Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter-Defibrillator: An Exploratory Observational Study.

Ventricular arrhythmia (VA) is a leading cause of sudden death and health deterioration. Recent advances in predictive analytics and wearable technology for behavior assessment show promise but require further investigation. Yet, previous studies have only assessed other health outcomes and monitored patients for short durations (7−14 days). This study explores how behaviors reported by a consumer wearable can assist VA risk prediction. An exploratory observational study was conducted with participants who had an implantable cardioverter-defibrillator (ICD) and wore a Fitbit Alta HR consumer wearable. Fitbit reported behavioral markers for physical activity (light, fair, vigorous), sleep, and heart rate. A case-crossover analysis using conditional logistic regression assessed the effects of time-adjusted behaviors over 1−8 weeks on VA incidence. Twenty-seven patients (25 males, median age 59 years) were included. Among the participants, ICDs recorded 262 VA events during 8093 days monitored by Fitbit (median follow-up period 960 days). Longer light to fair activity durations and a higher heart rate increased the odds of a VA event (p < 0.001). In contrast, lengthier fair to vigorous activity and sleep durations decreased the odds of a VA event (p < 0.001). Future studies using consumer wearables in a larger population should prioritize these outcomes to further assess VA risk.