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

Factors affecting signal quality in implantable cardiac monitors with long sensing vector

Purpose: Electrical artefacts are frequent in implantable cardiac monitors (ICMs). We analyzed the subcutaneous electrogram (sECG) provided by an ICM with a long sensing vector and factors potentially affecting its quality. Methods: Consecutive ICM recipients underwent a follow-up where demographics, body mass index (BMI), implant location, and surface ECG were collected. The sECG was then analyzed in terms of R-wave amplitude and P-wave visibility. Results: A total of 84 patients (43% female, median age 68 [58-76] years) were enrolled at 3 sites. ICMs were positioned with intermediate inclination (n\ua0=\ua044, 52%), parallel (n\ua0=\ua035, 43%), or perpendicular (n\ua0=\ua05, 6%) to the sternum. The median R-wave amplitude was 1.10 (0.72-1.48) mV with P waves readily visible in 69.2% (95% confidence interval, CI: 57.8%-79.2%), partially visible in 23.1% [95% CI: 14.3%-34.0%], and never visible in 7.7% [95% CI: 2.9%-16.0%] of patients. Men had higher R-wave amplitudes compared to women (1.40 [0.96-1.80] mV vs 1.00 [0.60-1.20] mV, P\ua0=.001), while obese people tended to have lower values (0.80 [0.62-1.28] mV vs 1.10 [0.90-1.50] mV, P\ua0=.074). The P-wave visibility reached 86.2% [95% CI: 68.3%-96.1%] in patients with high-voltage P waves ( 650.2\ua0mV) at surface ECG. The sECG quality was not affected by implant site. Conclusion: In ordinary clinical practice, ICMs with long sensing vector provided median R-wave amplitude above 1\ua0mV and reliable P-wave visibility of nearly 70%, regardless of the position of the device. Women and obese patients showed lower but still very good signal quality

Association between atrial fibrillation and cardiac implantable defibrillator detected heart failure status

Background: In heart failure (HF) patients, atrial fibrillation (AF) is a common comorbidity and is associated with a worse prognosis. Implantable defibrillator (ICD) diagnostics allow continuous monitoring of atrial high-rate events (AHRE), as a surrogate of AF, and are equipped with algorithms for HF monitoring. 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. The median follow-up was 25 months [25th–75th percentile: 15-35]. The HeartLogic algorithm calculates a daily HF index and identifies periods IN the alert state on the basis of a configurable threshold. The endpoints were: daily AF burden of ≥5 minutes, ≥6 hours and ≥23 hours. Results: TheHeartLogicindexcrossedthethresholdvalue1200times(0.71alerts/patient-year). The time INthe alert state was13%ofthe total observation period. During the observation period, an AF burden of≥5minutes/daywasdocumentedin183(32%)patients,≥6hours/dayin118 (21%) patients, and ≥23 hours/day in 89 (16%). On using a time-dependent Cox model, the weekly time IN the alert state was independently associated with an AF burden of ≥5 minutes/day (HR:1.95, 95%CI:1.22-3.13, p=0.005), ≥6 hours/day (HR:2.66, 95%CI:1.60-4.44, p<0.001), and ≥23 hours/day (HR:3.32, 95%CI:1.83-6.02, p<0.001), after correction for baseline confounders. Comparison of the episode rates in the IN-alert state with those in the OUT-of-alert state yielded HRs 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

Implantable defibrillator-detected heart failure status predicts ventricular tachyarrhythmias

Background: The occurrence of ventricular tachyarrhythmias is associ ated with increased mortality and hospitalizations for heart failure in im plantable cardioverter defibrillator (ICD) patients. Nonetheless, the tem poral relationship between heart failure worsening and ventricular tach yarrhythmias has been scarcely explored so far. Purpose: We hypothesized that in patients with heart failure and reduced ejection fraction with ICDs, physiological sensor-based heart failure status, as reflected in the HeartLogic index, would predict appropriate device ther apies for ventricular tachyarrhythmias (shocks and antitachycardia pacing). Methods and results: 568 patients implanted with ICDs (n=410, 72%) or cardiac resynchronization therapy-defibrillators (CRT-D, n=158, 28%) en dowed with the HeartLogic algorithm were included in this prospective observational multicenter analysis. Over a follow-up of 25 [25th-75th per centile: 15–35] months, 122 (21%) patients received an appropriate device therapy (shock, n=74, 13%), while the HeartLogic index crossed the thresh old value 1200 times (0.71 alerts/patient-year) in 370 subjects (65%). The occurrence of at least one HeartLogic alert was significantly associated with both appropriate shocks (HR: 2.44, 95% CI: 1.49–3.97, p=0.003) and any ICD therapies (HR: 1.95, 95% CI: 1.37–2.85, p=0.003). Using a time dependent Cox model, the weekly IN-alert state was the strongest predic tor of ICD shocks (HR: 2.94, 95% CI: 1.73–5.01, p<0.001), after correction for age, secondary prevention, and use of CRT. As compared to clinically stable subjects with no therapies, patients experiencing shocks had signif icantly higher baseline values of the HeartLogic index, third heart sound amplitude, and respiratory rate. Beginning about one month prior to the ar rhythmic event, we noticed further increase of the combined index and the third heart sound amplitude, a decrease of thoracic impedance, and higher resting heart rate (Figure 1). Conclusions: The HeartLogic index is an independent predictor of appro priate defibrillator therapies. The combined index and its individual physi ological components change well before the arrhythmic event, suggesting the existence of a window of opportunity to prevent shocks

Performance of a multisensor implantable defibrillator algorithm for HF monitoring in presence of comorbidities

Background: Cardiovascular and non-cardiovascular comorbidities are common in heart failure (HF) patients and impact disease severity and prognosis. Select modern implantable defibrillators (ICDs) are equipped with multisensor algorithms for HF monitoring. The HeartLogic index com bines multiple ICD-based sensor data (heart rate, heart sounds, thoracic impedance, respiration, activity), and the associated alert has proved to be a sensitive and timely predictor of impending HF decompensation in cardiac resynchronization therapy (CRT-D) patients The algorithm was de veloped using data from CRT-D patients; the performance in non-CRT ICD patients and the impact of selected comorbidities on performance requires further study. Methods: The HeartLogic feature was activated in 568 ICD patients (410 with CRT) from 26 centers. The median follow-up was 25 months [25th 75th percentile: 15–35]. Results: During follow-up, 97 hospitalizations were reported (53 cardio vascular) and 55 patients died. We recorded 1200 HeartLogic alerts (0.71 alerts/patient-year) in 370 patients. Overall, the time IN the alert state was 13%of the total observation period. The rate of cardiovascular hospitaliza tions or death was 0.48/patient-year (95% CI: 0.37–0.60) with the Heart Logic IN alert state and 0.04/patient-year (95% CI: 0.03–0.05) OUT of 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) at 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. Heart Logic alerts were not associated with CRT vs. non-CRT device implan tation (HR: 1.03, 95% CI: 0.82–1.30, p=0.775). The 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/non-CRT, AF/non-AF, CKD/non-CKD. Indeed, after multivariate correction for CKD and AF at implantation, the time IN the HeartLogic alert state >13% was associated with the occur rence of the combined endpoint of cardiovascular hospitalization or death (HR: 2.54, 95% CI: 1.61–4.01, p<0.001). Conclusions: The burden of HeartLogic alerts appears similar between CRT and non-CRT patients, while patients with AF and CKD seem more exposed to alerts. Nonetheless, the ability of the HeartLogic algorithm to identify patients during periods of significantly increased risk of clinical events is confirmed regardless of the type of device, the presence of AF, or CK

Performance of a multisensor implantable defibrillator algorithm for HF monitoring in presence of comorbidities

Background: Cardiovascular and non-cardiovascular comorbidities are common in heart failure (HF) patients and impact disease severity and prognosis. Select modern implantable defibrillators (ICDs) are equipped with multisensor algorithms for HF monitoring. The HeartLogic index com bines multiple ICD-based sensor data (heart rate, heart sounds, thoracic impedance, respiration, activity), and the associated alert has proved to be a sensitive and timely predictor of impending HF decompensation in cardiac resynchronization therapy (CRT-D) patients The algorithm was de veloped using data from CRT-D patients; the performance in non-CRT ICD patients and the impact of selected comorbidities on performance requires further study. Methods: The HeartLogic feature was activated in 568 ICD patients (410 with CRT) from 26 centers. The median follow-up was 25 months [25th 75th percentile: 15–35]. Results: During follow-up, 97 hospitalizations were reported (53 cardio vascular) and 55 patients died. We recorded 1200 HeartLogic alerts (0.71 alerts/patient-year) in 370 patients. Overall, the time IN the alert state was 13%of the total observation period. The rate of cardiovascular hospitaliza tions or death was 0.48/patient-year (95% CI: 0.37–0.60) with the Heart Logic IN alert state and 0.04/patient-year (95% CI: 0.03–0.05) OUT of 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) at 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. Heart Logic alerts were not associated with CRT vs. non-CRT device implan tation (HR: 1.03, 95% CI: 0.82–1.30, p=0.775). The 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/non-CRT, AF/non-AF, CKD/non-CKD. Indeed, after multivariate correction for CKD and AF at implantation, the time IN the HeartLogic alert state >13% was associated with the occur rence of the combined endpoint of cardiovascular hospitalization or death (HR: 2.54, 95% CI: 1.61–4.01, p<0.001). Conclusions: The burden of HeartLogic alerts appears similar between CRT and non-CRT patients, while patients with AF and CKD seem more exposed to alerts. Nonetheless, the ability of the HeartLogic algorithm to identify patients during periods of significantly increased risk of clinical events is confirmed regardless of the type of device, the presence of AF, or CKD

Prediction of all-cause mortality using a multisensor implantable defibrillator algorithm for HF monitoring

Background: 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. Purpose: We determined if remotely monitored data from this algorithm can be used to identify patients at high risk of mortality. Methods: The HeartLogic feature was activated in 568 ICD patients from 26 centers. Results: During a median follow-up of 26 months [25th–75th percentile: 16-37], 1200 HeartLogic alerts were recorded in 370 (65%) patients. Overall, the time IN the alert state was 13% of the total observation period (151 out of 1159 years) and 20% of the follow-up period of the 370 patients with alerts. During follow-up, 55 patients died (37 in the group with alerts). Experiencing any alert episode was associated with a substantially increased risk of death [hazard ratio (HR): 2.08, 95% confidence interval (CI): 1.16–3.73, P = 0.039]. Additionally, a time IN alert ≥20%wasassociated with death (HR: 4.07, 95%CI: 2.19-7.54, p<0.001, Figure), even after multivariate correction for age, atrial fibrillation on implantation, chronic kidney disease, ischemic cardiomyopathy (HR: 3.26, 95%CI:1.87-5.70, p<0.001). The rate of death was 0.25/patient-year (95%CI: 0.17-0.34) with the HeartLogic IN the alert state and 0.02/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<0.001). Conclusions: The HeartLogic algorithm provides an index that can be used to identify patients at higher risk of all-cause mortality. The index status identifies periods of significantly increased risk of deat