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Published on: February 28, 2012
Implantable defibrillator-detected heart failure status predicts atrial fibrillation occurrence
Matteo Bertini1, Francesco Vitali1, Luca Santini2
1Cardiology Unit, Sant'Anna University Hospital, University of Ferrara, Ferrara, Italy.
Insights
The HeartLogic index in implantable cardioverter-defibrillators (ICDs) can predict atrial fibrillation (AF) risk in heart failure patients. Alert states from the device independently indicate increased AF occurrence, aiding risk stratification.
Area of Science:
- Cardiology
- Biomedical Engineering
- Medical Device Technology
Background:
- Atrial fibrillation (AF) worsens prognosis in heart failure (HF) patients.
- Implantable cardioverter-defibrillators (ICDs) offer continuous AF monitoring and HF algorithms.
Purpose of the Study:
- Evaluate the association between the HeartLogic multisensor HF index and AF incidence.
- Assess the HeartLogic index's performance in detecting heightened AF risk periods.
Main Methods:
- The HeartLogic feature was activated in 568 ICD patients with a median follow-up of 25 months.
- The algorithm identifies daily HF index and IN-alert states based on a configurable threshold.
- Endpoints included daily AF burden of ≥5 minutes, ≥6 hours, and ≥23 hours.
Main Results:
- The HeartLogic index threshold was crossed 1200 times.
- Weekly IN-alert state was independently associated with AF burden (HRs ranging from 1.95 to 3.32, P < .005).
- Alert states showed higher AF episode rates (HRs 1.57-3.11) compared to out-of-alert states.
Conclusions:
- The HeartLogic alert state is independently associated with AF occurrence in HF patients.
- The algorithm's risk intervals aid in stratifying AF risk based on daily burden thresholds.
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 monitoring.
Objective:
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. 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 = .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 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.
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