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 moni-toring. OBJECTIVE We evaluated the association between the values of the multisensor HF HeartLogic index and the incidence of AF, and as-sessed the performance of the index in detecting follow-up periods of significantly increased AF risk. METHODS The HeartLogic feature was activated in 568 ICD pa-tients. 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 5 .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 asso-ciated with AF occurrence. The intervals of time defined by the algo-rithm as periods of increased risk of HF allow risk stratification of AF according to various thresholds of daily burden

Electrocardiographic predictors of left ventricular scar in athletes with right-ventricular-bundle-branch-block premature ventricular beats

Aims: Right bundle branch block (RBBB) morphology non-sustained ventricular arrhythmias (VAs) have been associated with the presence of non-ischemic left ventricular scar (NLVS) in athletes. Aim of this cross-sectional study was to identify clinical and ECG predictors of the presence of NLVS in athletes with RBBB VAs. Methods: Sixty-four athletes (median age 39(24-53) years, 79% males) with non-sustained RBBB VAs underwent cardiac magnetic resonance(CMR) with late gadolinium enhancement in order to exclude the presence of a concealed structural heart disease. Results: Thirty-six athletes (56%) showed NLVS at CMR and were assigned to NLVS positive group, whereas 28 athletes (44%) to NLVS negative group. Family history of cardiomyopathy and 7 different ECG variables were statistically more prevalent in NLVS positive group. At univariate analysis, 7 ECG variables (low QRS voltages in limb leads, negative T-waves in inferior leads, negative T-waves in limb leads I-aVL, negative T waves in precordial leads V4-V6, presence of left posterior fascicular block, presence of pathologic Q waves, poor R-wave progression in right precordial leads) proved to be statistically associated with the finding of NLVS; these were grouped together in a score. A score>2 was proved to be the optimal cut-off point, identifying NLVS athletes in 92% of cases and showing the best accuracy (86% sensitivity and 100% specificity, respectively). However, a cut-off >1 correctly identified all patients with NLVS (absence of false negatives). Conclusions: In athletes with RBBB morphology non-sustained VAs, specific ECG abnormalities at 12-lead ECG can help in detecting subjects with NLVS at CMR

D-MP02-03 Prospective evaluation of The Multisensor ICD Algorithm for Heart Failure Monitoring

Background: The HeartLogic algorithm measures data from multiple implantable cardioverter-defibrillator-based sensors and combines them into a single index. The associated alert has proved to be a sensitive and timely predictor of impending heart failure (HF) decompensation. Objective: To describe a multicenter experience of remote HF management by means of HeartLogic and appraise the value of an alert-based follow-up strategy. Methods: HeartLogic was activated in 104 patients. All patients were followed up according to a standardized protocol that included remote data reviews and patient phone contacts every month and at the time of HeartLogic alerts. In-office examinations were performed every 6 months or when deemed necessary. Results: During a median follow-up of 13 [10-16] months, the overall number of HF hospitalizations was 16 (rate 0.15 hospitalizations/patient-year) and 100 HeartLogic alerts were reported in 53 patients. Sixty alerts were judged clinically meaningful, and were associated with multiple HF-related conditions. In 48 of the 60 alerts, the clinician was not previously aware of the condition. Of these 48 alerts, 43 triggered clinical actions. The rate of alerts judged non-clinically meaningful was 0.37/patient-year, and the rate of hospitalizations not associated with an alert was 0.05/patient-year. Centers performed remote follow-up assessments of 1113 scheduled monthly transmissions (10.3/patient-year) and 100 alerts (0.93/patientyear). Monthly remote data review allowed to detect 11 (1%) HF events requiring clinical actions (versus 43% actionable alerts, p<0.001). Conclusion: HeartLogic allowed relevant HF-related clinical conditions to be identified remotely and enabled effective clinical actions to be taken; the rates of unexplained alerts and undetected HF events were low. An alert-based management strategy seemed more efficient than a scheduled monthly remote follow-up scheme

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

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 resynchroniza tion therapy (CRT). The HeartLogic index, a multiparametric heart failure (HF) risk score, incorporates implantable cardioverter-defi brillator (ICD)-measured variables and has demonstrated its predic tive ability for impending HF decompensation. OBJECTIVE This study aimed to investigate the relationship be tween 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 imped ance, 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 5 .045) and lower BiV% (hazard ratio: 3.97; 95% CI: 1.74–9.06; P5.001) 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