Clinical discussions in antithrombotic therapy management in patients with atrial fibrillation: a delphi consensus panel

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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

Remote monitoring for implantable defibrillators: A nationwide survey in italy

Background: Remote monitoring (RM) permits home interrogation of implantable cardioverter defibrillator (ICD) and provides an alternative option to frequent in-person visits. Objective: The Italia-RM survey aimed to investigate the current practice of ICD follow-up in Italy and to evaluate the adoption and routine use of RM. Methods: An ad hoc questionnaire on RM adoption and resource use during in-clinic and remote follow-up sessions was completed in 206 Italian implanting centers. Results: The frequency of routine in-clinic ICD visits was 2 per year in 158/206 (76.7%) centers, 3 per year in 37/206 (18.0%) centers, and 4 per year in 10/206 (4.9%) centers. Follow-up examinations were performed by a cardiologist in 203/206 (98.5%) centers, and by more than one health care worker in 184/206 (89.3%) centers. There were 137/206 (66.5%) responding centers that had already adopted an RM system, the proportion of ICD patients remotely monitored being 15% for single- and dual-chamber ICD and 20% for cardiac resynchronization therapy ICD. Remote ICD interrogations were scheduled every 3 months, and were performed by a cardiologist in 124/137 (90.5%) centers. After the adoption of RM, the mean time between in-clinic visits increased from 5 (SD 1) to 8 (SD 3) months (P<.001). Conclusions: In current clinical practice, in-clinic ICD follow-up visits consume a large amount of health care resources. The results of this survey show that RM has only partially been adopted in Italy and, although many centers have begun to implement RM in their clinical practice, the majority of their patients continue to be routinely followed-up by means of in-clinic visits

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

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 &lt;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 &lt;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 &lt;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 &lt; 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 &lt;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 &lt; 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 (&gt; 16), and the ICD-measured Respiratory Disturbance Index (RDI) was computed to identify severe SA. The endpoints were as follows: daily AHRE burden of &gt;= 5 min, &gt;= 6 h, and &gt;= 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 &gt;= 30 episodes/h (severe SA) during 58% of the observation period. An AHRE burden of &gt;= 5 min/day was documented in 139 (34%) patients, &gt;= 6 h/day in 89 (22%) patients, and &gt;= 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 &gt;= 5 min/day to 3.43 for &gt;= 23 h/day (P &lt; 0.01). An RDI &gt;= 30 episodes/h was associated only with AHRE burden &gt;= 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 &gt;= 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 &gt;= 5 min/day to 22 events/100 patient-years for AHRE burden &gt;= 23 h/day).Conclusions In HF patients, the occurrence of AHRE is independently associated with the ICD-measured IN-alert HF state and RDI &gt;= 30 episodes/h. The coexistence of these two conditions occurs rarely but is associated with a very high rate of AHRE occurrence

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