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Predicting Survival in Heart Failure Case and Control Subjects by Use of Fully Automated Methods for Deriving Nonlinear and Conventional Indices of Heart Rate Dynamics
Abstract
Background Despite much recent interest in quantification of heart rate variability (HRV), the prognostic value of conventional measures of HRV and of newer indices based on nonlinear dynamics is not universally accepted. Methods and Results We have designed algorithms for analyzing ambulatory ECG recordings and measuring HRV without human intervention, using robust methods for obtaining time-domain measures (mean and SD of heart rate), frequency-domain measures (power in the bands of 0.001 to 0.01 Hz [VLF], 0.01 to 0.15 Hz [LF], and 0.15 to 0.5 Hz [HF] and total spectral power [TP] over all three of these bands), and measures based on nonlinear dynamics (approximate entropy [ApEn], a measure of complexity, and detrended fluctuation analysis [DFA], a measure of long-term correlations). The study population consisted of chronic congestive heart failure (CHF) case patients and sex- and age-matched control subjects in the Framingham Heart Study. After exclusion of technically inadequate studies and those with atrial fibrillation, we used these algorithms to study HRV in 2-hour ambulatory ECG recordings of 69 participants (mean age, 71.7±8.1 years). By use of separate Cox proportional-hazards models, the conventional measures SD ( P <.01), LF ( P <.01), VLF ( P <.05), and TP ( P <.01) and the nonlinear measure DFA ( P <.05) were predictors of survival over a mean follow-up period of 1.9 years; other measures, including ApEn ( P >.3), were not. In multivariable models, DFA was of borderline predictive significance ( P =.06) after adjustment for the diagnosis of CHF and SD. Conclusions These results demonstrate that HRV analysis of ambulatory ECG recordings based on fully automated methods can have prognostic value in a population-based study and that nonlinear HRV indices may contribute prognostic value to complement traditional HRV measures.
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“A study using a forced desynchrony discovered that these temporal correlations have a circadian rhythm (independent from scheduled behaviors, activity, and mean HR) with signs of breaking down towards patterns seen in congestive heart failure during the vulnerable morning period (108).”
From Role of the circadian system in cardiovascular disease (2018) · cites this paper as [108]
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Metadata
- Authors
- Ho, K. K. L., Moody, G. B., Peng, C.-K., Mietus, J. E., Larson, M. G., Levy, D., & Goldberger, A. L.
- Affiliations
- Beth Israel Deaconess Medical Center (US)
- Venue
- Circulation
- Published
- 1997-08-05
- Volume
- 96
- Issue
- 3
- Pages
- 842-848
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- OpenAlex
- W2006524496
- Cited by
- 489
- References
- 26
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 3 · 2023: 9 · 2022: 6 · 2021: 12 · 2020: 24 · 2019: 19 · 2018: 17 · 2017: 17 · 2016: 18 · 2015: 18 · 2014: 13 · 2013: 21 · 2012: 26
- FWCI
- 9.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Circulation (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r29mh054081-03, n01hc038038-022)
- National Heart, Lung, and Blood Institute (N01-HC-38038)
- National Institute of Mental Health (MH-54081)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac electrophysiology and arrhythmias
- Keywords
- heart rate variability, congestive heart failure, survival prediction, prognostic factors, nonlinear HRV indices, detrended fluctuation analysis, approximate entropy, autonomic nervous system, Holter monitoring, frequency-domain HRV measures
- MeSH terms
- Aged, Aged, 80 and over, Algorithms, Automation, Feasibility Studies, Female, Forecasting, Heart Failure, Heart Rate, Humans, Male, Middle Aged, Models, Cardiovascular, Reference Values, Electrocardiography, Ambulatory, Survival Analysis, Nonlinear Dynamics, Entropy
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