Association between implantable defibrillator-detected sleep apnea and atrial fibrillation: The DASAP-HF study.

INTRODUCTION: The Respiratory Disturbance Index (RDI) computed by an implantable cardioverter defibrillator (ICD) algorithm accurately identifies severe sleep apnea (SA). In the present analysis, we tested the hypothesis that RDI could also predict atrial fibrillation (AF) burden. METHODS: Patients with ejection fraction ≤35% implanted with an ICD were enrolled and followed up for 24 months. One month after implantation, patients underwent a polysomnographic study. The weekly mean RDI value was considered, as calculated during the entire follow-up period and over a 1-week period preceding the sleep study. The endpoints were as follows: daily AF burden of ≥5 min, ≥6 h, ≥23 h. RESULTS: Here, 164 patients had usable RDI values during the entire follow-up period. Severe SA (RDI ≥ 30 episodes/h) was diagnosed in 92 (56%) patients at the time of the sleep study. During follow-up, AF burden ≥ 5 min/day was documented in 70 (43%), ≥6 h/day in 48 (29%), and ≥23 h/day in 33 (20%) patients. Device-detected RDI ≥ 30 episodes/h at the time of the polygraphy, as well as the polygraphy-measured apnea hypopnea index ≥ 30 episodes/h, were not associated with the occurrence of the endpoints, using a Cox regression model. However, using a time-dependent model, continuously measured weekly mean RDI ≥ 30 episodes/h was independently associated with AF burden ≥ 5 min/day (hazard ratio [HR]: 2.13, 95% confidence interval [CI]: 1.24-3.65, p = .006), ≥6 h/day (HR: 2.75, 95% CI: 1.37-5.49, p = .004), and ≥23 h/day (HR: 2.26, 95% CI: 1.05-4.86, p = .037). CONCLUSIONS: In heart failure patients, ICD-diagnosed severe SA on follow-up data review identifies patients who are from two- to three-fold more likely to experience an AF episode, according to various thresholds of daily AF burden.

The Italian subcutaneous implantable cardioverter-defibrillator survey: S-ICD, why not?

AIMS: A recommendation for a subcutaneous-implantable cardioverter-defibrillator (S-ICD) has been added to recent European Society of Cardiology Guidelines. However, the S-ICD is not ideally suitable for patients who need pacing. The aim of this survey was to analyse the current practice of ICD implantation and to evaluate the actual suitability of S-ICD. METHODS AND RESULTS: The survey 'S-ICD Why Not?' was an independent initiative taken by the Italian Heart Rhythm Society (AIAC). Clinical characteristics, selection criteria, and factors guiding the choice of ICD type were collected in consecutive patients who underwent ICD implantation in 33 Italian centres from September to December 2015. A cardiac resynchronization therapy (CRT) device was implanted in 39% (369 of 947) of patients undergoing de novo ICD implantation. An S-ICD was implanted in 12% of patients with no CRT indication (62 of 510 with available data). S-ICD patients were younger than patients who received transvenous ICD, more often had channelopathies, and more frequently received their device for secondary prevention of sudden death. More frequently, the clinical reason for preferring a transvenous ICD over an S-ICD was the need for pacing (45%) or for antitachycardia pacing (36%). Nonetheless, only 7% of patients fulfilled conditions for recommending permanent pacing, and 4% of patients had a history of monomorphic ventricular tachycardia that might have been treatable with antitachycardia pacing. CONCLUSION: The vast majority of patients needing ICD therapy are suitable candidates for S-ICD implantation. Nevertheless, it currently seems to be preferentially adopted for secondary prevention of sudden death in young patients with channelopathies.

Implantable Cardioverter Defibrillator Multisensor Monitoring during Home Confinement Caused by the COVID-19 Pandemic.

AIMS: The utilization of remote monitoring platforms was recommended amidst the COVID-19 pandemic. The HeartLogic index combines multiple implantable cardioverter defibrillator (ICD) sensors and has proved to be a predictor of impending heart failure (HF) decompensation. We examined how multiple ICD sensors behave in the periods of anticipated restrictions pertaining to physical activity. METHODS: The HeartLogic feature was active in 349 ICD and cardiac resynchronization therapy ICD patients at 20 Italian centers. The period from 1 January to 19 July 2020, was divided into three phases: pre-lockdown (weeks 1-11), lockdown (weeks 12-20), post-lockdown (weeks 21-29). RESULTS: Immediately after the implementation of stay-at-home orders (week 12), we observed a significant drop in median activity level whereas there was no difference in the other contributing parameters. The median composite HeartLogic index increased at the end of the Lockdown. The weekly rate of alerts was significantly higher during the lockdown (1.56 alerts/week/100 pts, 95%CI: 1.15-2.06; IRR = 1.71, p = 0.014) and post-lockdown (1.37 alerts/week/100 pts, 95%CI: 0.99-1.84; IRR = 1.50, p = 0.072) than that reported in pre-lockdown (0.91 alerts/week/100 pts, 95%CI: 0.64-1.27). However, the median duration of alert state and the maximum index value did not change among phases, as well as the proportion of alerts followed by clinical actions at the centers and the proportion of alerts fully managed remotely. CONCLUSIONS: During the lockdown, the system detected a significant drop in the median activity level and generated a higher rate of alerts suggestive of worsening of the HF status.

Association Between Device-Detected Sleep-Disordered Breathing and Implantable Defibrillator Therapy in Patients With Heart Failure.

BACKGROUND: Sleep-disordered breathing is highly prevalent in heart failure (HF) and has been suggested as a risk factor for malignant ventricular arrhythmias. The Respiratory Disturbance Index (RDI) computed by an implantable cardioverter-defibrillator (ICD) algorithm accurately identifies severe sleep apnea. OBJECTIVES: In the present analysis, the authors evaluated the association between ICD-detected sleep apnea and the incidence of appropriate ICD therapies in patients with HF. METHODS: We enrolled 411 HF patients who had received an ICD endowed with an algorithm that calculates the RDI each night. In this analysis, the weekly mean RDI value was considered. The endpoint was the first appropriate ICD shock. RESULTS: The median follow-up was 26 months (25th to 75th percentile: 16-35 months). During follow-up, 1 or more ICD shocks were documented in 58 (14%) patients. Patients with shocks were younger (age 66 ± 13 years vs 70 ± 10 years; P = 0.038), and had more frequently undergone implantation for secondary prevention (21% vs 10%; P = 0.026). The maximum RDI value calculated during the entire follow-up period did not differ between patients with and without shocks (55 ± 15 episodes/h vs 54 ± 14 episodes/h; P = 0.539). However, the ICD-detected RDI showed considerable variability during follow-up. The overall median of the weekly RDI was 33 episodes/h (25th to 75th percentile: 24-45 episodes/h). A time-dependent Cox regression model revealed that a continuously measured weekly mean RDI of ≥45 episodes/h was independently associated with shock occurrence (HR: 4.63; 95% CI: 2.54-8.43; P < 0.001), after correction for baseline confounders (age, secondary prevention). CONCLUSIONS: In HF patients, appropriate ICD shocks were more likely to be delivered during periods when patients exhibited more sleep-disordered breathing. (Arrhythmias Detection in a Real World Population [RHYTHM DETECT]; NCT02275637).

Multiparametric Implantable Cardioverter-Defibrillator Algorithm for Heart Failure Risk Stratification and Management: An Analysis in Clinical Practice.

BACKGROUND: The HeartLogic algorithm combines multiple implantable cardioverter-defibrillator sensors to identify patients at risk of heart failure (HF) events. We sought to evaluate the risk stratification ability of this algorithm in clinical practice. We also analyzed the alert management strategies adopted in the study group and their association with the occurrence of HF events. METHODS: The HeartLogic feature was activated in 366 implantable cardioverter-defibrillator and cardiac resynchronization therapy implantable cardioverter-defibrillator patients at 22 centers. The median follow-up was 11 months [25th-75th percentile: 6-16]. The HeartLogic algorithm calculates a daily HF index and identifies periods IN alert state on the basis of a configurable threshold. RESULTS: The HeartLogic index crossed the threshold value 273 times (0.76 alerts/patient-year) in 150 patients. The time IN alert state was 11% of the total observation period. Patients experienced 36 HF hospitalizations, and 8 patients died of HF during the observation period. Thirty-five events were associated with the IN alert state (0.92 events/patient-year versus 0.03 events/patient-year in the OUT of alert state). The hazard ratio in the IN/OUT of alert state comparison was (hazard ratio, 24.53 [95% CI, 8.55-70.38], P<0.001), after adjustment for baseline clinical confounders. Alerts followed by clinical actions were associated with less HF events (hazard ratio, 0.37 [95% CI, 0.14-0.99], P=0.047). No differences in event rates were observed between in-office and remote alert management. CONCLUSIONS: This multiparametric algorithm identifies patients during periods of significantly increased risk of HF events. The rate of HF events seemed lower when clinical actions were undertaken in response to alerts. Extra in-office visits did not seem to be required to effectively manage HeartLogic alerts. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02275637.

Prognostic value of implantable defibrillator-computed respiratory disturbance index: The DASAP-HF study.

BACKGROUND: Sleep apnea, as measured by polysomnography, is associated with adverse outcomes in heart failure. The DASAP-HF (Diagnosis and Treatment of Sleep Apnea in Patient With Heart Failure) study previously demonstrated that the respiratory disturbance index (RDI) computed by the ApneaScan algorithm (Boston Scientific) accurately identifies severe sleep apnea in implantable cardioverter-defibrillator (ICD) patients. OBJECTIVE: The purpose of the long-term study phase was to assess the incidence of clinical events after 24 months and investigate the association with RDI values. METHODS: Patients with left ventricular ejection fraction ≤35% implanted with an ICD were enrolled and followed-up for 24 months. The RDI calculated at 1 month after implantation was used to stratify patients (below or above 30 episodes/h). The endpoints were all-cause death and a combination of all-cause death or cardiovascular hospitalization. RESULTS: Of the 265 enrolled patients, 224 had usable RDI values. Severe sleep apnea (RDI ≥30 episodes/h) was diagnosed in 115 patients (51%). These patients were more frequently male (84% vs 72%; P = .030) and had higher creatinine levels. During median follow-up of 25 months, 19 patients (8%) died. Cardiovascular hospitalizations were reported in 19 patients (8%). The risk of all-cause death was higher in patients with RDI ≥30 episodes/h (hazard ratio [HR] 3.33; 95% confidence interval [CI] 1.35-8.21; P = .023), as well as the risk of all-cause death or cardiovascular hospitalization (HR 1.94; 95% CI 1.01-3.76; P = .048). At multivariate analysis, independent predictors of death were RDI ≥30 episodes/h (HR 4.02; 95% CI 1.16-13.97; P = .029) and creatinine levels (HR 2.36; 95% CI 1.26-4.42; P = .008). CONCLUSION: In heart failure patients implanted with an ICD, higher RDI values are associated with death and cardiovascular hospitalizations. Device-detected severe sleep apnea independently predicts death.

Incidence, predictors, and impact on outcome of increased left ventricular latency in patients undergoing cardiac resynchronization therapy.

PURPOSE: Latency during left ventricle (LV) pacing has been suggested as a potential cause of ineffectual biventricular pacing. We assessed the incidence, predictors, and impact on outcome of increased LV latency in 274 patients undergoing cardiac resynchronization therapy (CRT). METHODS: On implantation, the latency interval was defined as the shortest stimulus-to-QRS onset interval in any lead of the 12-lead ECG. A stimulus-to-QRS onset interval ≥ 40 ms was used to define the presence of increased LV latency. RESULTS: Increased LV latency was observed in 55 patients (20%). On multivariate analysis, only ischemic etiology proved to be a predictor of increased LV latency. On 12-month echocardiographic evaluation, 68% patients showed a ≥ 15% decrease in LV end systolic volume (74% patients with increased LV latency, 67% patients without increased LV latency (p = 0.58). The presence of increased LV latency was not associated with a different clinical response to CRT. CONCLUSIONS: Increased LV latency occurred in almost 20% of patients undergoing CRT and was more frequent in patients with ischemic heart disease. The presence of increased LV latency does not seem to have an impact on echocardiographic or clinical response to CRT.

Implantable cardioverter-defibrillator-computed respiratory disturbance index accurately identifies severe sleep apnea: The DASAP-HF study.

BACKGROUND: Sleep apnea (SA) is a relevant issue in the management of patients with heart failure for risk stratification and for implementing treatment strategies. OBJECTIVE: The purpose of this study was to evaluate in patients with implantable cardioverter-defibrillators (ICDs) the performance of the respiratory disturbance index (RDI) computed by the ApneaScan algorithm (Boston Scientific Inc., Natick, MA) as a discriminator of severe SA. METHODS: ICD-indicated patients with left ventricular ejection fraction ≤35% were enrolled. One month after implantation, patients underwent a polysomnographic study. We evaluated the accuracy of the RDI for the prediction of severe SA (apnea-hypopnea index [AHI] ≥30 episodes/h) and the agreement between RDI and AHI during the sleep study night. RESULTS: Two hundred sixty-five patients were enrolled to obtain the required sample of 173 patients with AHI and RDI data for analysis. The mean AHI was 21 ± 15 episodes/h and severe SA was diagnosed in 38 patients (22%), while the mean RDI was 33 ± 13 episodes/h. On the basis of the receiver operating characteristic curve analysis of RDI values, the area under the curve was 0.77 (95% confidence interval [CI] 0.70-0.83; P < .001). At an RDI value of 31 episodes/h, severe SA was detected with 87% (95% CI 72%-96%) sensitivity and 56% (95% CI 48%-66%) specificity. RDI closely correlated with AHI recorded during the same night (r = 0.74; 95% CI 0.57-0.84; P < .001), and the Bland-Altman agreement analysis revealed a bias of 11 episodes/h, with limits of agreement being -10 to 32 episodes/h. CONCLUSION: The RDI accurately identified severe SA and demonstrated good agreement with AHI. Therefore, it may serve as an efficient tool for screening patients at risk of SA.