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.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105876 | PMC |
http://dx.doi.org/10.1093/europace/euad052 | DOI Listing |
ESC Heart Fail
October 2024
Department of Cardiology, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan.
Aims: Hospitalizations are common in patients with heart failure and are associated with high mortality, readmission and economic burden. Detecting early signs of worsening heart failure may enable earlier intervention and reduce hospitalizations. The HeartLogic algorithm is designed to predict worsening heart failure using diagnostic data from multiple device sensors.
View Article and Find Full Text PDFAppl Clin Inform
August 2024
Information Services and Technology, Children's Healthcare of Atlanta, Atlanta, Georgia, United States.
Sci Rep
April 2024
Normandie Université, UNICAEN, INSERM, COMETE U1075, CYCERON, CHU Caen, 14000, Caen, France.
This research explores different methodologies to modulate the effects of drowsiness on functional connectivity (FC) during resting-state functional magnetic resonance imaging (RS-fMRI). The study utilized a cohort of students (MRi-Share) and classified individuals into drowsy, alert, and mixed/undetermined states based on observed respiratory oscillations. We analyzed the FC group difference between drowsy and alert individuals after five different processing methods: the reference method, two based on physiological and a global signal regression of the BOLD time series signal, and two based on Gaussian standardizations of the FC distribution.
View Article and Find Full Text PDFBrain Imaging Behav
June 2024
Department of Neurosurgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is highly transmissible and pathogenic. Patients with mild cases account for the majority of those infected with coronavirus disease 2019 (COVID-19). Although there is evidence that many patients with COVID-19 have varying degrees of attentional impairment, little is known about how SARS-COV-2 affects attentional function.
View Article and Find Full Text PDFEuropace
August 2023
Unità Operativa di Elettrofisiologia, Studio e Terapia delle Aritmie, Monaldi Hospital, Naples, Italy.
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.
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