Implantable defibrillator-detected heart failure status predicts ventricular tachyarrhythmias.

INTRODUCTION: The prediction of ventricular tachyarrhythmias among patients with implantable cardioverter defibrillators is difficult with available clinical tools. We sought to assess whether in patients with heart failure (HF) and reduced ejection fraction with defibrillators, physiological sensor-based HF status, as summarized by the HeartLogic index, could predict appropriate device therapies. METHODS: Five hundred and sixty-eight consecutive HF patients with defibrillators (n = 158, 28%) or cardiac resynchronization therapy-defibrillators (n = 410, 72%) were included in this prospective observational multicenter analysis. The association of both HeartLogic index and its physiological components with defibrillator shocks and overall appropriate therapies was assessed in regression and time-dependent Cox models. RESULTS: Over a follow-up of 25 (15-35) months, 122 (21%) patients received an appropriate device therapy (shock, n = 74, 13%), while the HeartLogic index crossed the threshold value (alert, HeartLogic ≥ 16) 1200 times (0.71 alerts/patient-year) in 370 (65%) subjects. The occurrence of ≥1 HeartLogic alert was significantly associated with both appropriate shocks (Hazard ratios [HR]: 2.44, 95% confidence interval [CI]: 1.49-3.97, p = .003), and any appropriate defibrillator therapies. In multivariable time-dependent Cox models, weekly IN-alert state was the strongest predictor of appropriate defibrillator shocks (HR: 2.94, 95% CI: 1.73-5.01, p < .001) and overall therapies. Compared with stable patients, patients with appropriate shocks had significantly higher values of HeartLogic index, third heart sound amplitude, and resting heart rate 30-60 days before device therapy. CONCLUSION: The HeartLogic index is an independent dynamic predictor of appropriate defibrillator therapies. The combined index and its individual physiological components change before the arrhythmic event occurs.

Performance of a multi-sensor implantable defibrillator algorithm for heart failure monitoring in the presence of atrial fibrillation.

AIMS: The HeartLogic Index combines data from multiple implantable cardioverter defibrillators (ICDs) sensors and has been shown to accurately stratify patients at risk of heart failure (HF) events. We evaluated and compared the performance of this algorithm during sinus rhythm and during long-lasting atrial fibrillation (AF). METHODS AND RESULTS: HeartLogic was activated in 568 ICD patients from 26 centres. We found periods of ≥30 consecutive days with an atrial high-rate episode (AHRE) burden <1 h/day and periods with an AHRE burden ≥20 h/day. We then identified patients who met both criteria during the follow-up (AHRE group, n = 53), to allow pairwise comparison of periods. For control purposes, we identified patients with an AHRE burden <1 h throughout their follow-up and implemented 2:1 propensity score matching vs. the AHRE group (matched non-AHRE group, n = 106). In the AHRE group, the rate of alerts was 1.2 [95% confidence interval (CI): 1.0-1.5]/patient-year during periods with an AHRE burden <1 h/day and 2.0 (95% CI: 1.5-2.6)/patient-year during periods with an AHRE-burden ≥20 h/day (P = 0.004). The rate of HF hospitalizations was 0.34 (95% CI: 0.15-0.69)/patient-year during IN-alert periods and 0.06 (95% CI: 0.02-0.14)/patient-year during OUT-of-alert periods (P < 0.001). The IN/OUT-of-alert state incidence rate ratio of HF hospitalizations was 8.59 (95% CI: 1.67-55.31) during periods with an AHRE burden <1 h/day and 2.70 (95% CI: 1.01-28.33) during periods with an AHRE burden ≥20 h/day. In the matched non-AHRE group, the rate of HF hospitalizations was 0.29 (95% CI: 0.12-0.60)/patient-year during IN-alert periods and 0.04 (95% CI: 0.02-0.08)/patient-year during OUT-of-alert periods (P < 0.001). The incidence rate ratio was 7.11 (95% CI: 2.19-22.44). CONCLUSION: Patients received more alerts during periods of AF. The ability of the algorithm to identify increased risk of HF events was confirmed during AF, despite a lower IN/OUT-of-alert incidence rate ratio in comparison with non-AF periods and non-AF patients. CLINICAL TRIAL REGISTRATION: http://clinicaltrials.gov/Identifier: NCT02275637.

Combination of an implantable defibrillator multi-sensor heart failure index and an apnea index for the prediction of atrial high-rate events.

AIMS: Patients with atrial fibrillation frequently experience sleep disorder breathing, and both conditions are highly prevalent in presence of heart failure (HF). We explored the association between the combination of an HF and a sleep apnoea (SA) index and the incidence of atrial high-rate events (AHRE) in patients with implantable defibrillators (ICDs). METHODS AND RESULTS: Data were prospectively collected from 411 consecutive HF patients with ICD. The IN-alert HF state was measured by the multi-sensor HeartLogic Index (>16), and the ICD-measured Respiratory Disturbance Index (RDI) was computed to identify severe SA. The endpoints were as follows: daily AHRE burden of ≥5 min, ≥6 h, and ≥23 h. During a median follow-up of 26 months, the time IN-alert HF state was 13% of the total observation period. The RDI value was ≥30 episodes/h (severe SA) during 58% of the observation period. An AHRE burden of ≥5 min/day was documented in 139 (34%) patients, ≥6 h/day in 89 (22%) patients, and ≥23 h/day in 68 (17%) patients. The IN-alert HF state was independently associated with AHRE regardless of the daily burden threshold: hazard ratios from 2.17 for ≥5 min/day to 3.43 for ≥23 h/day (P < 0.01). An RDI ≥ 30 episodes/h was associated only with AHRE burden ≥5 min/day [hazard ratio 1.55 (95% confidence interval: 1.11-2.16), P = 0.001]. The combination of IN-alert HF state and RDI ≥ 30 episodes/h accounted for only 6% of the follow-up period and was associated with high rates of AHRE occurrence (from 28 events/100 patient-years for AHRE burden ≥5 min/day to 22 events/100 patient-years for AHRE burden ≥23 h/day). CONCLUSIONS: In HF patients, the occurrence of AHRE is independently associated with the ICD-measured IN-alert HF state and RDI ≥ 30 episodes/h. The coexistence of these two conditions occurs rarely but is associated with a very high rate of AHRE occurrence. CLINICAL TRIAL REGISTRATION: URL: http://clinicaltrials.gov/Identifier: NCT02275637.

Patient acceptance of subcutaneous versus transvenous defibrillator systems: A multi-center experience.

BACKGROUND: The subcutaneous implantable cardioverter-defibrillator (S-ICD) is an effective alternative to the transvenous ICD. No study has yet compared S-ICD and transvenous ICD by assessing patient acceptance as a patient-centered outcome. OBJECTIVE: To evaluate the patient acceptance of the S-ICD and to investigate its association with clinical and implantation variables. In patients with symptomatic heart failure and reduced ejection fraction (HFrEF), the acceptance of the S-ICD was compared with a control group of patients who received a transvenous ICD. METHODS: Patient acceptance was calculated with the Florida Patient Acceptance Survey (FPAS) which measures four factors: return to function (RTF), device-related distress (DRD), positive appraisal (PA), and body image concerns (BIC). The survey was administered 12 months after implantation. RESULTS: 176 patients underwent S-ICD implantation. The total FPAS and the single factors did not differ according to gender, body habitus, or generator positioning. Patients with HFrEF had lower FPAS and RTF. Younger patients showed better RTF (75 [56-94] vs. 56 [50-81], p = .029). Patients who experienced device complications or device therapies showed higher DRD (40 [35-60] vs. 25 [10-50], p = .019). Patients with HFrEF receiving the S-ICD had comparable FPAS, RTF, DRD, and BIC to HFrEF patients implanted with the transvenous ICD while exhibited significantly better PA (88 [75-100] vs. 81 [63-94], p = .02). CONCLUSIONS: Our analysis revealed positive patient acceptance of the S-ICD, even in groups at risk of more distress such as women or patients with thinner body habitus, and regardless of the generator positioning. Among patients receiving ICDs for HFrEF, S-ICD was associated with better PA versus transvenous ICD.

Stricter criteria for left bundle branch block diagnosis do not improve response to CRT.

BACKGROUND: Cardiac resynchronization therapy (CRT) has proved to be effective in patients with heart failure and left bundle branch block (LBBB). Recently, new electrocardiography criteria have been proposed for the diagnosis of LBBB. These criteria are stricter than the current American Heart Association (AHA) criteria. We assessed the rate of echocardiographic response to CRT in patients with traditional LBBB versus patients who met the new criteria (strict LBBB). METHODS: Consecutive patients undergoing CRT were enrolled in the CRT MORE registry. Patients with no-LBBB QRS morphology according to AHA criteria, atrial fibrillation, right bundle branch block, and right ventricular pacing were excluded. Strict LBBB was defined as: QRS ≥ 140 ms for men and ≥130 ms for women, QS or rS in V1-V2, mid-QRS notching or slurring in ≥2 contiguous leads. Patients showing a relative decrease of ≥15% in left ventricular end-systolic volume (LVESV) at 12 months were defined as responders. RESULTS: Among 335 patients with LBBB, 131 (39%) had strict LBBB. Patients with and without strict LBBB showed comparable baseline characteristics, except for QRS duration (166 ± 20 ms vs 152 ± 25 ms, P < 0.001). On 12-month evaluation, 205 patients (61%) were responders; 85 of 131 (65%) had strict LBBB and 120 of 204 (59%) had traditional LBBB (P = 0.267). On multivariate analysis, a history of atrial fibrillation, larger LVESV, and the presence of mid-QRS notching in ≥1 lead (odds ratio 2.099; 95% confidence interval 1.061-4.152, P = 0.033) were independently associated with echocardiographic response. CONCLUSION: Stricter definition of LBBB did not improve response to CRT in comparison to the current AHA definition.

Association between amount of biventricular pacing and heart failure status measured by a multisensor implantable defibrillator algorithm.

Background: Achieving a high biventricular pacing percentage (BiV%) is crucial for optimizing outcomes in cardiac resynchronization therapy (CRT). The HeartLogic index, a multiparametric heart failure (HF) risk score, incorporates implantable cardioverter-defibrillator (ICD)-measured variables and has demonstrated its predictive ability for impending HF decompensation. Objective: This study aimed to investigate the relationship between daily BiV% in CRT ICD patients and their HF status, assessed using the HeartLogic algorithm. Methods: The HeartLogic algorithm was activated in 306 patients across 26 centers, with a median follow-up of 26 months (25th-75th percentile: 15-37). Results: During the follow-up period, 619 HeartLogic alerts were recorded in 186 patients. Overall, daily values associated with the best clinical status (highest first heart sound, intrathoracic impedance, patient activity; lowest combined index, third heart sound, respiration rate, night heart rate) were associated with a BiV% exceeding 99%. We identified 455 instances of BiV% dropping below 98% after consistent pacing periods. Longer episodes of reduced BiV% (hazard ratio: 2.68; 95% CI: 1.02-9.72; P = .045) and lower BiV% (hazard ratio: 3.97; 95% CI: 1.74-9.06; P=.001) were linked to a higher risk of HeartLogic alerts. BiV% drops exceeding 7 days predicted alerts with 90% sensitivity (95% CI [74%-98%]) and 55% specificity (95% CI [51%-60%]), while BiV% ≤96% predicted alerts with 74% sensitivity (95% CI [55%-88%]) and 81% specificity (95% CI [77%-85%]). Conclusion: A clear correlation was observed between reduced daily BiV% and worsening clinical conditions, as indicated by the HeartLogic index. Importantly, even minor reductions in pacing percentage and duration were associated with an increased risk of HF alerts.

Performance of a multisensor implantable defibrillator algorithm for heart failure monitoring related to co-morbidities.

AIMS: The HeartLogic algorithm combines multiple implantable defibrillator (ICD) sensor data and has proved to be a sensitive and timely predictor of impending heart failure (HF) decompensation in cardiac resynchronization therapy (CRT-D) patients. We evaluated the performance of this algorithm in non-CRT ICD patients and in the presence of co-morbidities. METHODS AND RESULTS: The HeartLogic feature was activated in 568 ICD patients (410 with CRT-D) from 26 centres. The median follow-up was 26 months [25th-75th percentile: 16-37]. During follow-up, 97 hospitalizations were reported (53 cardiovascular) and 55 patients died. We recorded 1200 HeartLogic alerts in 370 patients. Overall, the time IN the alert state was 13% of the total observation period. The rate of cardiovascular hospitalizations or death was 0.48/patient-year (95% CI: 0.37-0.60) with the HeartLogic IN the alert state and 0.04/patient-year (95% CI: 0.03-0.05) OUT of the alert state, with an incidence rate ratio of 13.35 (95% CI: 8.83-20.51, P < 0.001). Among patient characteristics, atrial fibrillation (AF) on implantation (HR: 1.62, 95% CI: 1.27-2.07, P < 0.001) and chronic kidney disease (CKD) (HR: 1.53, 95% CI: 1.21-1.93, P < 0.001) independently predicted alerts. HeartLogic alerts were not associated with CRT-D versus ICD implantation (HR: 1.03, 95% CI: 0.82-1.30, P = 0.775). Comparisons of the clinical event rates in the IN alert state with those in the OUT of alert state yielded incidence rate ratios ranging from 9.72 to 14.54 (all P < 0.001) in all groups of patients stratified by: CRT-D/ICD, AF/non-AF, and CKD/non-CKD. After multivariate correction, the occurrence of alerts was associated with cardiovascular hospitalization or death (HR: 1.92, 95% CI: 1.05-3.51, P = 0.036). CONCLUSIONS: The burden of HeartLogic alerts was similar between CRT-D and ICD patients, while patients with AF and CKD seemed more exposed to alerts. Nonetheless, the ability of the HeartLogic algorithm to identify periods of significantly increased risk of clinical events was confirmed, regardless of the type of device and the presence of AF or CKD.

Predicting all-cause mortality by means of a multisensor implantable defibrillator algorithm for heart failure monitoring.

BACKGROUND: The HeartLogic algorithm (Boston Scientific) has proved to be a sensitive and timely predictor of impending heart failure (HF) decompensation. OBJECTIVE: The purpose of this study was to determine whether remotely monitored data from this algorithm could be used to identify patients at high risk for mortality. METHODS: The algorithm combines implantable cardioverter-defibrillator (ICD)-measured accelerometer-based heart sounds, intrathoracic impedance, respiration rate, ratio of respiration rate to tidal volume, night heart rate, and patient activity into a single index. An alert is issued when the index crosses a programmable threshold. The feature was activated in 568 ICD patients from 26 centers. RESULTS: During median follow-up of 26 months [25th-75th percentile 16-37], 1200 alerts were recorded in 370 patients (65%). Overall, the time IN-alert state was 13% of the total observation period (151/1159 years) and 20% of the follow-up period of the 370 patients with alerts. During follow-up, 55 patients died (46 in the group with alerts). The rate of death was 0.25 per patient-year (95% confidence interval [CI] 0.17-0.34) IN-alert state and 0.02 per patient-year (95% CI 0.01-0.03) OUT of the alert state, with an incidence rate ratio of 13.72 (95% CI 7.62-25.60; P <.001). After multivariate correction for baseline confounders (age, ischemic cardiomyopathy, kidney disease, atrial fibrillation), the IN-alert state remained significantly associated with the occurrence of death (hazard ratio 9.18; 95% CI 5.27-15.99; P <.001). CONCLUSION: The HeartLogic algorithm provides an index that can be used to identify patients at higher risk for all-cause mortality. The index state identifies periods of significantly increased risk of death.

The challenging management of cardiac involvement in systemic sarcoidosis.

A 34 year-old young man came to our attention after an occasional finding of complete AV block. We made the diagnosis of systemic sarcoidosis with cardiac involvement through an FDG-PET even with a normal CMR. We started corticosteroid therapy and we decided to follow-up the patient through an implantable loop recorder (ILR). Beyond an initial regression of the AV block, after 8 months the ILR revealed AV block and pauses more than 3 s during the day; a new FDG-PET evidenced FDG uptake in new areas of left ventricle. Hence we started infliximab and implanted a dual chamber ICD.

Implantable defibrillator-detected heart failure status predicts atrial fibrillation occurrence.

BACKGROUND: In heart failure (HF) patients, atrial fibrillation (AF) is associated with a worse prognosis. Implantable cardioverter-defibrillator (ICD) diagnostics allow continuous monitoring of AF and are equipped with algorithms for HF monitoring. OBJECTIVE: We evaluated the association between the values of the multisensor HF HeartLogic index and the incidence of AF, and assessed the performance of the index in detecting follow-up periods of significantly increased AF risk. METHODS: The HeartLogic feature was activated in 568 ICD patients. Median follow-up was 25 months [25th-75th percentile (15-35)]. The HeartLogic algorithm calculates a daily HF index and identifies periods of IN-alert state on the basis of a configurable threshold. The endpoints were daily AF burden ≥5 minutes, ≥6 hours, and ≥23 hours. RESULTS: The HeartLogic index crossed the threshold value 1200 times. AF burden ≥5 minutes/day was documented in 183 patients (32%), ≥6 hours/day in 118 patients (21%), and ≥23 hours/day in 89 patients (16%). The weekly time of IN-alert state was independently associated with AF burden ≥5 minutes/day (hazard ratio [HR] 1.95; 95% confidence interval [CI] 1.22-3.13; P = .005), ≥6 hours/day (HR 2.66; 95% CI 1.60-4.44; P <.001), and ≥23 hours/day (HR 3.32; 95% CI 1.83-6.02; P <.001), after correction for baseline confounders. Comparison of the episode rates in the IN-alert state with those in the OUT-of-alert state yielded HR ranging from 1.57 to 3.11 for AF burden from ≥5 minutes to ≥23 hours. CONCLUSIONS: The HeartLogic alert state was independently associated with AF occurrence. The intervals of time defined by the algorithm as periods of increased risk of HF allow risk stratification of AF according to various thresholds of daily burden.