Cargando…
Comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death
OBJECTIVE: Comparative algorithmic evaluation of heartbeat series in low-to-high risk cardiac patients for the prospective prediction of risk of arrhythmic death (AD). BACKGROUND: Heartbeat variation reflects cardiac autonomic function and risk of AD. Indices based on linear stochastic models are in...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2009
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2731023/ https://www.ncbi.nlm.nih.gov/pubmed/19707283 |
_version_ | 1782170921615753216 |
---|---|
author | Skinner, James E Meyer, Michael Nester, Brian A Geary, Una Taggart, Pamela Mangione, Antoinette Ramalanjaona, George Terregino, Carol Dalsey, William C |
author_facet | Skinner, James E Meyer, Michael Nester, Brian A Geary, Una Taggart, Pamela Mangione, Antoinette Ramalanjaona, George Terregino, Carol Dalsey, William C |
author_sort | Skinner, James E |
collection | PubMed |
description | OBJECTIVE: Comparative algorithmic evaluation of heartbeat series in low-to-high risk cardiac patients for the prospective prediction of risk of arrhythmic death (AD). BACKGROUND: Heartbeat variation reflects cardiac autonomic function and risk of AD. Indices based on linear stochastic models are independent risk factors for AD in post-myocardial infarction (post-MI) cohorts. Indices based on nonlinear deterministic models have superior predictability in retrospective data. METHODS: Patients were enrolled (N = 397) in three emergency departments upon presenting with chest pain and were determined to be at low-to-high risk of acute MI (>7%). Brief ECGs were recorded (15 min) and R-R intervals assessed by three nonlinear algorithms (PD2i, DFA, and ApEn) and four conventional linear-stochastic measures (SDNN, MNN, 1/f-Slope, LF/HF). Out-of-hospital AD was determined by modified Hinkle–Thaler criteria. RESULTS: All-cause mortality at one-year follow-up was 10.3%, with 7.7% adjudicated to be AD. The sensitivity and relative risk for predicting AD was highest at all time-points for the nonlinear PD2i algorithm (p ≤0.001). The sensitivity at 30 days was 100%, specificity 58%, and relative risk >100 (p ≤0.001); sensitivity at 360 days was 95%, specificity 58%, and relative risk >11.4 (p ≤0.001). CONCLUSIONS: Heartbeat analysis by the time-dependent nonlinear PD2i algorithm is comparatively the superior test. |
format | Text |
id | pubmed-2731023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-27310232009-08-25 Comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death Skinner, James E Meyer, Michael Nester, Brian A Geary, Una Taggart, Pamela Mangione, Antoinette Ramalanjaona, George Terregino, Carol Dalsey, William C Ther Clin Risk Manag Original Research OBJECTIVE: Comparative algorithmic evaluation of heartbeat series in low-to-high risk cardiac patients for the prospective prediction of risk of arrhythmic death (AD). BACKGROUND: Heartbeat variation reflects cardiac autonomic function and risk of AD. Indices based on linear stochastic models are independent risk factors for AD in post-myocardial infarction (post-MI) cohorts. Indices based on nonlinear deterministic models have superior predictability in retrospective data. METHODS: Patients were enrolled (N = 397) in three emergency departments upon presenting with chest pain and were determined to be at low-to-high risk of acute MI (>7%). Brief ECGs were recorded (15 min) and R-R intervals assessed by three nonlinear algorithms (PD2i, DFA, and ApEn) and four conventional linear-stochastic measures (SDNN, MNN, 1/f-Slope, LF/HF). Out-of-hospital AD was determined by modified Hinkle–Thaler criteria. RESULTS: All-cause mortality at one-year follow-up was 10.3%, with 7.7% adjudicated to be AD. The sensitivity and relative risk for predicting AD was highest at all time-points for the nonlinear PD2i algorithm (p ≤0.001). The sensitivity at 30 days was 100%, specificity 58%, and relative risk >100 (p ≤0.001); sensitivity at 360 days was 95%, specificity 58%, and relative risk >11.4 (p ≤0.001). CONCLUSIONS: Heartbeat analysis by the time-dependent nonlinear PD2i algorithm is comparatively the superior test. Dove Medical Press 2009 2009-08-20 /pmc/articles/PMC2731023/ /pubmed/19707283 Text en © 2009 Skinner et al, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited. |
spellingShingle | Original Research Skinner, James E Meyer, Michael Nester, Brian A Geary, Una Taggart, Pamela Mangione, Antoinette Ramalanjaona, George Terregino, Carol Dalsey, William C Comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death |
title | Comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death |
title_full | Comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death |
title_fullStr | Comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death |
title_full_unstemmed | Comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death |
title_short | Comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ECGs to predict risk of arrhythmic death |
title_sort | comparison of linear–stochastic and nonlinear–deterministic algorithms in the analysis of 15-minute clinical ecgs to predict risk of arrhythmic death |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2731023/ https://www.ncbi.nlm.nih.gov/pubmed/19707283 |
work_keys_str_mv | AT skinnerjamese comparisonoflinearstochasticandnonlineardeterministicalgorithmsintheanalysisof15minuteclinicalecgstopredictriskofarrhythmicdeath AT meyermichael comparisonoflinearstochasticandnonlineardeterministicalgorithmsintheanalysisof15minuteclinicalecgstopredictriskofarrhythmicdeath AT nesterbriana comparisonoflinearstochasticandnonlineardeterministicalgorithmsintheanalysisof15minuteclinicalecgstopredictriskofarrhythmicdeath AT gearyuna comparisonoflinearstochasticandnonlineardeterministicalgorithmsintheanalysisof15minuteclinicalecgstopredictriskofarrhythmicdeath AT taggartpamela comparisonoflinearstochasticandnonlineardeterministicalgorithmsintheanalysisof15minuteclinicalecgstopredictriskofarrhythmicdeath AT mangioneantoinette comparisonoflinearstochasticandnonlineardeterministicalgorithmsintheanalysisof15minuteclinicalecgstopredictriskofarrhythmicdeath AT ramalanjaonageorge comparisonoflinearstochasticandnonlineardeterministicalgorithmsintheanalysisof15minuteclinicalecgstopredictriskofarrhythmicdeath AT terreginocarol comparisonoflinearstochasticandnonlineardeterministicalgorithmsintheanalysisof15minuteclinicalecgstopredictriskofarrhythmicdeath AT dalseywilliamc comparisonoflinearstochasticandnonlineardeterministicalgorithmsintheanalysisof15minuteclinicalecgstopredictriskofarrhythmicdeath |