Episode-level and clinical characterization of asymptomatic atrial fibrillation events.

INTRODUCTION: Not all patients experience debilitating symptoms during Atrial Fibrillation (AF), some are asymptomatic. The reasons for this inter- and intrasubject variability is unknown. PURPOSE: The study objective was NOAH characterize episode-level and clinical characteristics associated with symptomatic versus asymptomatic episodes of AF in patients with an implantable cardiac monitor (ICM). METHODS: Patients with an AF episode detected on an ICM between 2007 and 2021 with overlapping clinical data from aggregated Electronic Health Records in the Optum® deidentified data set were included. Symptomatic episodes were labeled in real-time by the patient. Heart rate (HR) at onset, mean HR, AF Evidence Score (a measure of beat-to-beat irregularity), episode duration and Activity Index were evaluated for association with symptom status using multivariable regression modeling. RESULTS: 11 267 patients had AF episodes with clinical data available. The 1776 (15.8%) patients who reported symptomatic AF episodes were younger (67 ± 12 years vs. 71 ± 11 years old, p < .001) and had fewer cardiovascular co-morbidities than patients with asymptomatic AF exclusively. Symptomatic episodes were longer (5.5 [2.4, 14.4] h vs. 3.7 [1.7, 11] h, p < .001), had higher mean HR (103 ± 22 bpm vs. 88 ± 22 bpm, p < .001) and higher AF evidence scores (98 ± 27 vs. 82 ± 24, p < .001). These features were independently associated with symptomatic episodes on multivariable regression analysis and per-subject analysis in patients who had both symptomatic and asymptomatic episodes. DISCUSSION: Episode-level characteristics differed between symptomatic AF episodes versus asymptomatic episodes in patients with ICMs. Symptomatic patients also had less comorbidities. These parameters may be useful in understanding variable symptomatic manifestation and remote stratification of AF episodes.

Associations Between Changes in Maximum Daily Atrial Fibrillation Duration, Ischemic Stroke, and Mortality.

BACKGROUND: Atrial fibrillation (AF) outcomes are strongly associated with continuous measures of AF burden. OBJECTIVES: This study sought to assess the association between changes in maximum daily AF duration (MDAFD) and stroke or mortality in patients with cardiac implantable electronic devices (CIEDs). METHODS: The Optum deidentified electronic health record data set (2007-2021) was linked with the Medtronic CareLink heart rhythm database. Patients with CIEDs and health care activity recorded in the electronic health record were included, excluding those with oral anticoagulation prescription. MDAFD was assessed 30 days post implant (baseline period) and 30 days before censoring or an event. HRs for the primary analysis were adjusted for components of CHA2DS2-VASc, baseline MDAFD category, and chronic kidney disease. RESULTS: Of 26,400 patients (age 68 ± 13 years; follow-up 2.6 ± 1.6 years) analyzed, 2,544 (9.6%) had AF during baseline. Increased (vs stable or decreased) MDAFD category in follow-up was associated with a higher adjusted rate of stroke and mortality (HR: 1.80; 95% CI: 1.61-2.01). There was no association between decreased MDAFD in follow-up and the combined endpoint (HR: 0.82; 95% CI: 0.68-1.00). Subgroup analysis by baseline MDAFD category demonstrated that increased MDAFD in follow-up was associated with a greater risk of stroke or mortality among patients with no AF at baseline, and decreased MDAFD in follow-up was associated with a lower risk of stroke or mortality among patients with baseline MDAFD of 1 to <5.5 hours and 5.5 to <23.5 hours. CONCLUSIONS: In CIED patients not on oral anticoagulation, increased MDAFD in follow-up was associated with a higher rate of stroke and mortality. These results suggest that AF burden, and associated risk, s not stable over time.

Dynamic risk stratification of worsening heart failure using a deep learning-enabled implanted ambulatory single-lead electrocardiogram.

Aims: Implantable loop recorders (ILRs) provide continuous single-lead ambulatory electrocardiogram (aECG) monitoring. Whether these aECGs could be used to identify worsening heart failure (HF) is unknown. Methods and results: We linked ILR aECG from Medtronic device database to the left ventricular ejection fraction (LVEF) measurements in Optum® de-identified electronic health record dataset. We trained an artificial intelligence (AI) algorithm [aECG-convolutional neural network (CNN)] on a dataset of 35 741 aECGs from 2247 patients to identify LVEF ≤ 40% and assessed its performance using the area under the receiver operating characteristic curve. Ambulatory electrocardiogram-CNN was then used to identify patients with increasing risk of HF hospitalization in a real-world cohort of 909 patients with prior HF diagnosis. This dataset provided 12 467 follow-up monthly evaluations, with 201 HF hospitalizations. For every month, time-series features from these predictions were used to categorize patients into high- and low-risk groups and predict HF hospitalization in the next month. The risk of HF hospitalization in the next 30 days was significantly higher in the cohort that aECG-CNN identified as high risk [hazard ratio (HR) 1.89; 95% confidence interval (CI) 1.28-2.79; P = 0.001] compared with low risk, even after adjusting patient demographics (HR 1.88; 95% CI 1.27-2.79 P = 0.002). Conclusion: An AI algorithm trained to detect LVEF ≤40% using ILR aECGs can also readily identify patients at increased risk of HF hospitalizations by monitoring changes in the probability of HF over 30 days.

Ineffective cardiac resynchronization pacing is associated with poor outcomes in a nationwide cohort analysis.

BACKGROUND: Delivery of cardiac resynchronization therapy (CRT) requires left ventricular myocardial capture to achieve clinical benefits. OBJECTIVE: We sought to determine whether ineffective pacing affects survival. METHODS: Ineffective ventricular pacing (VP) was defined as the difference between the percentage of delivered CRT (%VP) and the percentage of EffectivCRT in CRT devices. Using the Optum de-identified electronic health record data set and Medtronic CareLink data warehouse, we identified patients implanted with applicable devices with at least 30 days of follow-up. Kaplan-Meier and Cox proportional hazards models assessed the effect of %VP and % ineffective VP on survival. RESULTS: Among 7987 patients with 2.1 ± 1.0 years of follow-up, increasing ineffective VP was associated with decreasing survival: the highest observed survival was in the quartile with <0.08% ineffective VP and the lowest survival was in the quartile with >1.47% ineffective VP (85.1% vs 75.7% at 3 years; P < .001). As expected, patients with more than the median %VP of 97.7% had better survival than did patients with <97.7% VP (84.2% vs 77.8%; P < .001). However, patients who had >97.7% VP but >2% ineffective VP had similar survival to patients with <97.7% VP but ≤2% ineffective VP (81.6% vs 79.4%; P = .54). A multivariable Cox proportional hazards model demonstrated that <97.7% VP (adjusted hazard ratio 1.29; 95% confidence interval 1.14-1.46; P < .001) and >2% ineffective VP (hazard ratio 1.35; 95% confidence interval 1.18-1.54; P < .001) were both significantly associated with decreased survival. CONCLUSION: Ineffective VP is associated with decreased survival. In addition to maximizing the percentage of delivered CRT pacing, every effort should be made to minimize ineffective VP.

Temporal Association Between Atrial Fibrillation Burden in Cardiac Implantable Electronic Devices and the Risk of Heart Failure Hospitalization.

BACKGROUND: Atrial fibrillation (AF) events in cardiac implantable electronic devices (CIEDs) are temporally associated with stroke risk. This study explores temporal differences in AF burden associated with HF hospitalization risk in patients with CIEDs. METHODS: Patients with HF events from the Optum de-identified Electronic Health Records from 2007 to 2021 and 120 days of preceding CIED-derived rhythm data from a linked manufacturer's data warehouse were included. AF burden ≥5.5 h/d was defined as an AF event. The AF event burden in the case period (days 1-30 immediately before the HF event) was considered temporally associated with the HF event and compared with the AF event burden in a temporally dissociated control period (days 91-120 before the HF event). The odds ratio for temporally associated HF events and the odds ratio associated with poorly rate-controlled AF (>110 bpm) were calculated. RESULTS: In total, 7257 HF events with prerequisite CIED data were included; 957 (13.2%) patients had AF events recorded only in either their case (763 [10.5%]) or control (194 [2.7%]) periods, but not both. The odds ratio for a temporally associated HF event was 3.93 (95% CI, 3.36-4.60). This was greater for an HF event with a longer stay of >3 days (odds ratio, 4.51 [95% CI, 3.57-5.68]). In patients with AF during both the control and case periods, poor AF rate control during the case period also increased HF event risk (1.78 [95% CI, 1.22-2.61]). In all, 222 of 4759 (5%) patients without AF events before their HF event had an AF event in the 10 days following. CONCLUSIONS: In a large real-world population of patients with CIED devices, AF burden was associated with HF hospitalization risk in the subsequent 30 days. The risk is increased with AF and an uncontrolled ventricular rate. Our findings support AF monitoring in CIED algorithms to prevent HF admissions.

Ambulatory Risk Stratification for Worsening Heart Failure in Patients with Reduced and Preserved Ejection Fraction Using Diagnostic Parameters Available in Implantable Cardiac Monitors.

BACKGROUND: Ambulatory risk stratification for worsening heart failure (HF) using diagnostics measured by insertable cardiac monitors (ICM) may depend on the left ventricular ejection fraction (LVEF). We evaluated risk stratification performance in patients with reduced versus preserved LVEF. METHODS: ICM patients with a history of HF events (HFEs) were included from the Optum® de-identified Electronic Health Record dataset merged with ICM device-collected data during 2007-2021. ICM measures nighttime heart rate (NHR), heart rate variability (HRV), atrial fibrillation (AF) burden, rate during AF, and activity duration (ACT) daily. Each diagnostic was categorized into high, medium, or low risk using previously defined features. HFEs were HF-related inpatient, observation unit, or emergency department stays with IV diuresis administration. Patients were divided into two cohorts: LVEF ≤ 40% and LVEF > 40%. A marginal Cox proportional hazards model compared HFEs for different risk groups. RESULTS: A total of 1020 ICM patients with 18,383 follow-up months and 301 months with HFEs (1.6%) were included. Monthly evaluations with a high risk were 2.3, 4.2, 5.0, and 4.5 times (p < 0.001 for all) more likely to have HFEs in the next 30 days compared to those with a low risk for AF, ACT, NHR, and HRV, respectively. HFE rates were higher for patients with LVEF > 40% compared to LVEF ≤ 40% (2.0% vs. 1.3%), and the relative risk between high-risk and low-risk for each diagnostic parameter was higher for patients with LVEF ≤ 40%. CONCLUSIONS: Diagnostics measured by ICM identified patients at risk for impending HFEs. Patients with preserved LVEF showed a higher absolute risk, and the relative risk between risk groups was higher in patients with reduced LVEF.

A Novel Heart Failure Diagnostic Risk Score Using a Minimally Invasive Subcutaneous Insertable Cardiac Monitor.

BACKGROUND: The authors tested the hypothesis that physiological information from sensors within a minimally invasive, subcutaneous, insertable cardiac monitor (ICM) could be used to develop an ambulatory heart failure risk score (HFRS) to accurately identify heart failure (HF) patients, across the ejection fraction spectrum, at high risk of an impending worsening heart failure event (HFE). OBJECTIVES: The purpose of this study was to examine performance of ICM-based, multiparameter, dynamic HFRS to predict HFEs in patients with NYHA functional class II/III HF. METHODS: In 2 observational cohorts, HF patients were implanted with an ICM; subcutaneous impedance, respiratory rate, heart rate and variability, atrial fibrillation burden, ventricular rate during atrial fibrillation, and activity duration were combined into an HFRS to identify the probability of HFE within 30 days. Patients and providers were blinded to the data. HFRS sensitivity and unexplained detection rate were defined in 2 independent patient population data sets. HFEs were defined as hospitalization, observation unit, or emergency department visit with a primary diagnosis of HF, and intravenous diuretic treatment. RESULTS: First data set (development): 42 patients had 19 HFE; second data set (validation): 94 patients had 19 HFE (mean age 66 ± 11 years, 63% men, 50% with LVEF ≥40%, 80% NYHA functional class III). Using a high-risk threshold = 7.5%, development and validation data sets: sensitivity was 73.7% and 68.4%; unexplained detection rate of 1.4 and 1.5 per patient-year; median 47 and 64 days early warning before HFE. CONCLUSIONS: ICM-HFRS provides a multiparameter, integrated diagnostic method with the ability to identify when HF patients are at increased risk of heart failure events. (Reveal LINQ Evaluation of Fluid [REEF]; NCT02275923, Reveal LINQ Heart Failure [LINQ HF]; NCT02758301, Algorithm Using LINQ Sensors for Evaluation and Treatment of Heart Failure [ALLEVIATE-HF]; NCT04452149).

Prolonged PR interval and incidence of atrial fibrillation, heart failure admissions, and mortality in patients with implanted cardiac devices: A real-world survey.

Background: Prolongation of the PR interval has long been considered a benign condition, particularly in the setting of nonstructural heart disease. Objective: The purpose of this study was to investigate the effect of PR interval on various well-adjudicated cardiovascular outcomes using a large real-world population data of patients with implanted dual-chamber permanent pacemakers or implantable cardioverter-defibrillators. Methods: PR intervals were measured during remote transmissions in patients with implanted permanent pacemakers or implantable cardioverter-defibrillators. Study endpoints (time to the first occurrence of AF, heart failure hospitalization [HFH], or death) were obtained between January 2007 and June 2019 from the deidentified Optum de-identified Electronic Health Record dataset. Results: A total of 25,752 patients (age 69.3 ± 13.9 years; 58% male) were evaluated. The average intrinsic PR interval was 185 ± 55 ms. In the subset of 16,730 patients with available long-term device diagnostic data, a total of 2555 (15.3%) individuals developed AF during 2.59 ± 2.18 years of follow-up. The incidence of AF was significantly higher (up to 30%) in patients with a longer PR interval (ie, PR interval ≥270 ms; P < .05). Time-to-event survival analysis and multivariable analysis showed that PR interval ≥190 ms was significantly associated with higher incidence of AF, HFH, or HFH or death when compared with shorter PR intervals (P < .05 for all 3 parameters). Conclusion: In a large real-world population of patients with implanted devices, PR interval prolongation was significantly associated with increased incidence of AF, HFH, or death.

Lower heart rates and beta-blockers are associated with new-onset atrial fibrillation.

Background: Lower heart rates (HRs) prolong diastole, which increases filling pressures and wall stress. As a result, lower HRs may be associated with higher brain natriuretic peptide (BNP) levels and incident atrial fibrillation (AF). Beta-blockers may increase the risk for AF due to suppression of resting HRs. Objective: Examine the relationships of HR, BNP, beta-blockers and new-onset AF in the REVEAL-AF and SPRINT cohort of subjects at risk for developing AF. Methods: In REVEAL-AF, 383 subjects without a history of AF and a mean CHA2DS2VASC score of 4.4 ± 1.3 received an insertable cardiac monitor and were followed up to 30 months. In SPRINT, 7595 patients without prior history of AF and a mean CHA2DS2VASC score of 2.3 ± 1.2 were followed up to 60 months. Results: The median daytime HR in the REVEAL-AF cohort was 75bpm [IQR 68-83]. Subjects with below-median HRs had 2.4-fold higher BNP levels compared to subjects with above-median HRs (median BNP [IQR]: 62 pg/dl [37-112] vs. 26 pg/dl [13-53], p < 0.001). HRs <75bpm were associated with a higher incidence of AF: 37% vs. 27%, p < 0.05. This was validated in the SPRINT cohort after adjusting for AF risk factors. Both a HR < 75bpm and beta-blocker use were associated with a higher rate of AF: 1.9 vs 0.7% (p < 0.001) and 2.5% vs. 0.6% (p < 0.001), respectively. The hazard ratio for patients on beta-blockers to develop AF was 3.72 [CI 2.32, 5.96], p < 0.001. Conclusions: Lower HRs are associated with higher BNP levels and incident AF, mimicking the hemodynamic effects of diastolic dysfunction. Suppression of resting HR by beta-blockers could explain their association with incident AF.

Temporal Characteristics of Device-Based Individual and Integrated Risk Metrics in Patients With Chronic Heart Failure.

BACKGROUND: Temporal characteristics of a multimetric risk score and its individual parameters before, during, and after a heart failure (HF) event have not been defined. OBJECTIVES: A large real-world patient cohort with implantable cardioverter-defibrillators and cardiac resynchronization therapy (CRT) defibrillators was used to define these temporal characteristics. METHODS: Deidentified health records were linked to manufacturer's device database in 17,886 patients. Multimetric risk score combined daily measures of impedance, heart rate, activity, heart rate variability, and atrial fibrillation (AF) burden, AF ventricular rate, CRT pacing, and ventricular tachycardia episodes and shocks. HF event was defined as an inpatient, emergency department, or observation unit stay with primary diagnosis of HF and intravenous diuretic agents administration. Changes in risk parameters during 60 days before, during, and after an HF event were compared in patients with no HF readmissions vs patients with HF readmission. RESULTS: A total of 1,174 patients had HF events with no HF readmission, and 282 patients had HF events with HF readmission. Diagnostic risk score was higher on all 60 days before and after a HF event in patients with HF readmission compared with patients with no readmission (P < 0.001). Change in risk score from admission to discharge was similar in patients with and without HF readmission, but the risk score fell more significantly 7 after discharge and 30 days after admission in patients without HF readmission (P < 0.001). CONCLUSIONS: Temporal characteristics of risk metrics were significantly different in patients with no HF readmissions vs patients with HF readmission; patients without HF recurrence had larger recovery of risk metrics values toward normal.

An ensemble of features based deep learning neural network for reduction of inappropriate atrial fibrillation detection in implantable cardiac monitors.

Background: Multiple studies have reported on classification of raw electrocardiograms (ECGs) using convolutional neural networks (CNNs). Objective: We investigated an application-specific CNN using a custom ensemble of features designed based on characteristics of the ECG during atrial fibrillation (AF) to reduce inappropriate AF detections in implantable cardiac monitors (ICMs). Methods: An ensemble of features was developed and combined to form an input signal for the CNN. The features were based on the morphological characteristics of AF, incoherence of RR intervals, and the fact that AF begets more AF. A custom CNN model and the RESNET18 model were trained using ICM-detected AF episodes that were adjudicated to be true AF or false detections. The trained models were evaluated using a test dataset from independent patients. Results: The training and validation datasets consisted of 31,757 AF episodes (2516 patients) and 28,506 false episodes (2126 patients). The validation set (20% randomly chosen episodes of each type) had an area under the curve of 0.996 for custom CNN (0.993 for RESNET18). Thresholds were chosen to obtain a relative sensitivity and specificity of 99.2% and 92.8%, respectively (99.2% and 87.9% for RESNET18, respectively). The performance in the independent test set (4546 AF episodes from 418 patients; 5384 false episodes from 605 patients) showed an area under the curve of 0.993 (0.991 for RESNET18) and relative sensitivity and specificity of 98.7% and 91.4%, respectively, at chosen thresholds (98.9% and 88.2% for RESNET18, respectively). Conclusion: An ensemble of features-based CNNs was developed that reduced inappropriate AF detection in ICMs by over 90% while preserving sensitivity.

Ambulatory activity in stroke survivors associated with functional outcome and quality of life: An observational cohort study.

BACKGROUND: Physical activity is beneficial in stroke prevention and recovery. Understanding activity dynamics and its effect on outcome after stroke is important to improve recommendations and develop interventions. OBJECTIVES: We examined serial changes in daily ambulatory activity (AA) averaged over 1 week in people with subacute to chronic stroke and its association with functional outcome (modified Rankin scale [mRS]) and quality of life (EQ-5D-3L). METHODS: This observational study examined AA in stroke survivors with no to moderate disability (US National Institute of Stroke Scale [NIHSS] score) who were mostly community dwelling and had cryptogenic stroke based on data from the Continuous Cardiac Monitoring to Assess Atrial Fibrillation After Cryptogenic Stroke study. The participants underwent long-term AA monitoring by accelerometric activity data obtained from an insertable cardiac monitor without receiving any specific encouragement regarding physical activity. We analysed AA changes and assessed the association between baseline AA and mRS/EQ-5D-3L scores. A small group of participants had follow-up data for 2 years, which allowed for analysing long-term serial changes. RESULTS: We included 186 participants (mean [SD] age 61.3 [11.2] years, 67% male, mean 39 [28] days after stroke). AA increased during the subacute phase in individuals with mild (NIHSS score 1-4, P<0.001) and moderate (NIHSS score 5-10, P=0.013) disability but not in the non-impaired group. Baseline AA was inversely associated with NIHSS score (P<0.001) and was associated with mRS score (P=0.001) and weakly correlated with EQ-5D-3L score at 6 months (P=0.032, r=0.22). For the 45 participants with follow-up data (mean age 64.5 [9.7] years, 80% male, mean 34 [21] days after stroke), AA remained stable. CONCLUSION: AA increased in stroke survivors with impairments but remained stable in those whose symptoms had resolved. AA during the early subacute period was associated with mRS and EQ-5D-3L scores at 6 months. Insertable cardiac monitoring offers a feasible method for monitoring activity over prolonged periods in people after stroke. Its increased use may offer an opportunity to overcome the limited reliability and validity of many existing measures. TRIAL REGISTRATION: ClinicalTrials.gov (NCT00924638).

Trends in implantable cardioverter-defibrillator programming practices and its impact on therapies: Insights from a North American Remote Monitoring Registry 2007-2018.

BACKGROUND: Recent evidence has revealed the utility of prolonged arrhythmia detection duration and increased rate cutoff to reduce implantable cardioverter-defibrillator (ICD) therapies. Data on real-world trends in ICD programming and its impact on outcomes are limited. OBJECTIVE: The purpose of this study was to evaluate trends in ICD programming and its impact on ICD therapy using a large remote monitoring database. METHODS: A retrospective analysis of patients with ICD implanted from 2007 to 2018 was conducted using the de-identified Medtronic CareLink database. Data on ICD programming (number of intervals to detection [NID] and therapy rate cutoff) and delivered ICD therapies were collected. RESULTS: Among 210,810 patients, the proportion programmed to a rate cutoff of ≥188 beats/min increased from 41% to 49% and an NID of ≥30/40 increased from 17% to 67% before May 2013 vs after February 2016. Programming to a rate cutoff of ≥188 beats/min, a ventricular fibrillation (VF) NID of ≥30/40, or a combined rate cutoff of ≥188 beats/min and VF NID of ≥30/40 were associated with reductions in ICD therapy. The largest reductions in ICD therapy occurred when the combination of rate cutoff ≥ 188 beats/min and VF NID ≥ 30/40 was programmed (antitachycardia pacing: hazard ratio [HR] 0.35; 95% confidence interval [CI] 0.34-0.36; P < .001; shocks: HR 0.67; 95% CI 0.65-0.69; P < .001; and antitachycardia pacing/shocks: HR 0.43; 95% CI 0.42-0.44; P < .001). CONCLUSION: Despite evidence supporting the use of prolonged detection duration and high rate cutoff, implementation of shock reduction programming strategies in real-world clinical practice has been modest. The use of evidence-based ICD programming is associated with reduced ICD shocks over long-term follow-up.

Temporal Association Between Episodes of Atrial Fibrillation and Risk of Ischemic Stroke.

Importance: Understanding the temporal association between atrial fibrillation (AF) and ischemic stroke informs our understanding of the AF-stroke mechanism and treatment of paroxysmal AF. Objective: To define the temporal association between episodes of AF and stroke in patients with cardiac implantable electronic devices (CIEDs). Design, Setting, and Participants: In this case-crossover study, data from a large national electronic health record database were linked with a single-vendor database of heart rhythm records of patients with CIEDs capable of continuous heart rhythm monitoring. Patients with CIEDs who sustained an ischemic stroke who also had 120 days of continuous remote rhythm monitoring prestroke were included. Data were collected from January 2007 to March 2017, and data were analyzed from November 2019 to June 2020. Exposure: AF for 5.5 hours or more on any given day during days 1 to 30 vs days 91 to 120 prestroke. Main Outcomes and Measures: Odds ratio for stroke comparing AF during days 1 to 30 vs 91 to 120 prestroke. This analysis was planned prior to the study. Results: From 466 635 patients included in both the Optum electronic health record and CareLink databases, 891 patients with CIEDs and ischemic stroke with continuous monitoring in the 120 days prestroke were identified. Of 891 included patients, 575 (64.5%) were male, and the median (interquartile range) age was 76 (67-82) years. The vast majority of patients with stroke had either no AF meeting the threshold duration of 5.5 hours or more in both the case and control periods (682 of 891 [76.5%]) or AF of 5.5 hours or more in both periods (143 of 891 [16.0%]). For those not meeting the 5.5-hour AF threshold in either period, there was no or very little AF throughout the 120 days prestroke. A total of 66 patients had informative, discordant arrhythmic states, with 52 having AF of 5.5 hours or more in the case period vs 14 in the control period (odds ratio [OR], 3.71; 95% CI, 2.06-6.70). Stroke risk was increased most in days 1 to 5 following an AF episode (OR, 5.00; 95% CI, 2.62-9.55). AF greater than 23 hours on a given day was associated with the clearest increase in stroke risk (OR, 5.00; 95% CI, 2.08-12.01). Conclusions and Relevance: In this large cohort of patients with CIEDs and continuous rhythm monitoring prior to ischemic stroke, excess stroke risk above baseline was highest within 5 days of an episode of AF of 5.5 hours or more in duration and diminished rapidly thereafter. Our findings are consistent with the traditional view that AF is directly and transiently associated with ischemic stroke. These results provide support for trials of time-delimited anticoagulation for patients with infrequent multihour episodes of AF and rigorous, continuous rhythm monitoring.

Use of Oral Anticoagulation in a Real-World Population With Device Detected Atrial Fibrillation.

Background Guideline recommendations for oral anticoagulation (OAC) in patients with atrial fibrillation (AF) are based on CHA2DS2-VASc score alone. Patients with cardiac implantable electronic devices provide an opportunity to assess how the interaction between AF duration and CHA2DS2-VASc score influences OAC prescription rates. Methods and Results Data from the Optum de-identified Electronic Health Record data set were linked to the Medtronic CareLink database of cardiac implantable electronic devices. An index date was assigned as the later of 6 months after device implant or 1 year after Electronic Health Record data availability. Maximum daily AF duration (no AF, 6 minutes-23.5 hours, and >23.5 hours) was assessed for 6 months before index date. OAC prescription rates were computed as a function of both AF duration and CHA2DS2-VASc score. A total of 35 779 patients with CHA2DS2-VASc scores ≥1 were identified, including 27 198 not prescribed OAC. Overall OAC prescription rate among the 12 938 patients with device-detected AF >6 minutes was 36.7% and significantly higher in those with a maximum daily AF duration >23.5 hours (45.4%) compared with those with 6 minutes to 23.5 hours (28.7%). OAC prescription rates increased monotonically with both increasing AF duration and CHA2DS2-VASc score, reaching a maximum of 67.2% for patients with AF >23.5 hours and a CHA2DS2-VASc score ≥5. Conclusions Real-world prescription of OAC increased with both increasing duration of AF and CHA2DS2-VASc score. This highlights the need for further research into the role of AF duration, stroke risk, and the need for anticoagulation in patients with devices capable of long-term AF monitoring.

Prediction of worsening heart failure events and all-cause mortality using an individualized risk stratification strategy.

AIMS: This study aimed to examine the clinical utility of a multisensor, remote, ambulatory diagnostic risk score, TriageHF™, in a real-world, unselected, large patient sample to predict heart failure events (HFEs) and all-cause mortality. METHODS AND RESULTS: TriageHF risk score was calculated in patients in the Optum® database who had Medtronic implantable cardiac defibrillator device from 2007 to 2016. Patients were categorized into three risk groups based on probability for having an HFE within 6 months (low risk <5.4%, medium risk ≥5.4 < 20%, and high risk ≥20%). Data were analysed using three strategies: (i) scheduled monthly data download; (ii) alert-triggered data download; and (iii) daily data download. Study population consisted of 22 901 patients followed for 1.8 ± 1.3 years. Using monthly downloads, HFE risk over 30 days incrementally increased across risk categories (odds ratio: 2.8, 95% confidence interval: 2.5-3.2 for HFE, P < 0.001, low vs. medium risk, and odds ratio: 9.2, 95% confidence interval: 8.1-10.3, P < 0.001, medium vs. high risk). Findings were similar using the other two analytic strategies. Using a receiver operating characteristic curve analysis, sensitivity for predicting HFE over 30 days using high-risk score was 47% (alert triggered) and 51% (daily download) vs. 0.5 per patient year unexplained detection rate. TriageHF risk score also predicted all-cause mortality risk over 4 years. All-cause mortality risk was 14% in low risk, 20% in medium risk, and 38% in high risk. CONCLUSIONS: TriageHF risk score provides a multisensor remote, ambulatory diagnostic method that predicts both HFEs and all-cause mortality.

Prediction of heart failure hospitalizations based on the direct measurement of intrathoracic impedance.

AIMS: OptiVol fluid index was developed as a transthoracic impedance-based indicator of short-term risk for heart failure hospitalization (HFH). OptiVol is calculated as the accumulating difference between daily impedance (measured impedance) and long-term average impedance (reference impedance). Measured impedance alone was thought to have limited prognostic utility; however, measured impedance has the advantage of being simple, direct, and possibly additive to OptiVol fluid index in establishing long-term HFH risk. We tested the hypothesis that directly measured impedance has independent prognostic value in predicting long-term HFH risk and that changes in measured impedance result in a change in predicted long-term HFH risk. METHODS AND RESULTS: A retrospective analysis of 1719 patients studied in PARTNERS-HF, FAST, and RAFT studies was performed. Baseline measured impedance was determined using daily values averaged over 1 month, from Month 6 to 7 post implant; change in measured impedance was determined from values averaged over 1 month, from Month 7 to 8 post implant compared with baseline. The predictive value of baseline measured impedance for HFHs was assessed beginning 7 months post implant. The predictive value of a change in measured impedance for a change in HFHs was assessed beginning 8 months post implant. Baseline measured impedance successfully predicted HFHs. For example, 3 year HFH rate for low baseline impedance < 70 Ω was 23%; for high baseline impedance ≥ 70 Ω was 15% (P < 0.001). Changes in measured impedance resulted in changes in predicted HFHs. For example, when a baseline impedance of ≥70 fell during follow-up to <70 Ω, the subsequent HFHs were 15% compared with 4% in patients with measured impedance that remained >70 Ω (P = 0.004). In addition, when baseline measured impedance fell during follow-up by >1%, 2%, or 3%, subsequent HFHs increased to 13%, 17%, or 18%, respectively. Finally, the prognostic value of measured impedance was additive to the prognostic value of the OptiVol fluid index. CONCLUSIONS: Direct measurements of intrathoracic impedance using an implanted device can be used to stratify patients at varying risk of long-term HFH. These direct measurements of impedance have practical clinical appeal because they are simple, continuous, and ambulatory.

Characteristics of ventricular tachyarrhythmias and their susceptibility to antitachycardia pacing termination in patients with ischemic and nonischemic cardiomyopathy: A patient-level meta-analysis of three large clinical trials.

BACKGROUND: Implantable cardioverter defibrillators (ICDs) reduce all-cause mortality among cardiomyopathy patients. Whether or not antitachycardia pacing (ATP) is equally effective in ischemic (ICM) and nonischemic (NICM) cardiomyopathy patients remains poorly understood. We describe the distribution of monomorphic (MVT) and non-monomorphic (polymorphic ventricular tachycardia/ventricular fibrillation [PVT/VF]) ventricular tachyarrhythmias among ICM and NICM primary prevention patients. METHODS: This patient-level meta-analysis included primary prevention patients from the Shock-Less (n = 3519), PainFree SST (n = 1917), and PREPARE (n = 690) studies. Distribution of MVT and PVT/VF events were compared with χ2 tests. ATP success was estimated using a generalized estimating equation model to correct for multiple episodes for a patient between cohorts for slow (≥320 ms) and fast (240-310 ms) MVTs. RESULTS: Among 6126 patients, 714 (29% NICM, age 66 ± 13 years, female 18%, EF = 29 ± 12%) had a total of 4444 treated ventricular tachyarrhythmia episodes. The rate of individuals treated for MVT or PVT/VF was comparable between ICM (11.9%) and NICM (11.2%) over 21 ± 10 months. In addition, the distribution of MVT (76% ICM vs. 71% NICM) and PVT/VF (15% ICM vs. 20% NICM) was not significantly different (p = .28). Among MVT episodes, the average tachycardia cycle lengths (332 ± 58 ms ICM vs. 313 ± 40 ms NICM; p = .27) were similar, as was the likelihood of ATP-associated termination (74.6% ICM vs. 76.4% NICM; p = .58). Overall, ATP success was higher for slow (≥320 ms) MVT versus faster (240-310 ms) episodes (84.1% vs. 69%; p < .001). CONCLUSION: In a large cohort of primary prevention ICD patients, ICM and NICM patients have similar rates and proportions of MVT and PVT/VF episodes. ATP-associated termination of MVT was comparable between the two groups.

Evaluation of an Integrated Device Diagnostics Algorithm to Risk Stratify Heart Failure Patients　- Results From the SCAN-HF Study.

BACKGROUND: Integrated device diagnostics, Triage-HF, is useful in risk stratifying patients with heart failure (HF), but its performance for Japanese patients remains unknown. This is a prospective study of Japanese patients treated with a cardiac resynchronization therapy defibrillator (CRT-D), with a Medtronic OptiVol 2.0 feature.Methods and Results:A total of 320 CRT-D patients were enrolled from 2013 to 2017. All received HF treatment in the prior 12 months. Following enrollment, they were followed every 6 months for 48 months (mean, 22 months). Triage-HF-stratified patients at low, medium and high risk statuses at every 30-day period, and HF-related hospitalization occurring for the subsequent 30 days, were evaluated and repeated. The primary endpoint was to assess Triage-HF performance in predicting HF-related hospitalization risk. All device data were available for 279 of 320 patients (NYHA class II or III in 93%; mean left ventricular ejection fraction, 31%). During a total of 5,977 patient-month follow-ups, 89 HF-related hospitalization occurred in 72 patients. The unadjusted event numbers for Low, Medium and High statuses were 19 (0.7%), 42 (1.6%) and 28 (4.1%), respectively. Relative risk of Medium to Low status was 2.18 (95% CI 1.23-3.85) and 5.78 (95% CI 3.34-10.01) for High to Low status. Common contributing factors among the diagnostics included low activity, OptiVol threshold crossing, and elevated night heart rate. CONCLUSIONS: Triage-HF effectively stratified Japanese patients at risk of HF-related hospitalization.

Premature ventricular contraction detection for long-term monitoring in an implantable cardiac monitor.

BACKGROUND: Premature ventricular complexes (PVCs) are an important therapeutic target in symptomatic patients and in the setting of PVC-induced cardiomyopathy; however, measuring burden and therapeutic response is challenging. We developed and validated an algorithm for continuous long-term monitoring of PVC burden in an insertable cardiac monitor (ICM). METHODS: A high-specificity PVC detection algorithm was developed using real-world ICM data and validated using simultaneous Holter data and real-world ICM data. The PVC algorithm uses long-short-long RR interval sequence and morphology characteristics for three consecutive beats to detect the occurrence of single PVC beats. Data are expressed as gross incidence, patient average, and generalized estimating equation estimates, which were used to determine sensitivity, specificity, positive and negative predictive value (PPV, NPV). RESULTS: The PVC detection algorithm was developed on eighty-seven 2-min EGM strips recorded by an ICM to obtain a sensitivity and specificity of 75.9% and 98.8%. The ICM validation data cohort consisted of 787 ICM recorded ECG strips 7-16 min in duration from 134 patients, in which the algorithm detected PVC beats with a sensitivity, specificity, PPV, and NPV of 75.2%, 99.6%, 75.9%, and 99.5%, respectively. In the Holter validation dataset with continuous 2-h snippets from 20 patients, the algorithm sensitivity, specificity, PPV, and NPV were 74.4%, 99.6%, 68.8%, and 99.7%, respectively, for detecting PVC beats. CONCLUSIONS: The PVC detection algorithm was able to achieve a high specificity with only 0.4% of the normal events being incorrectly identified as PVCs, while detecting around three of four PVCs on a continuous long-term basis in ICMs.