Literature DB >> 15159047

Can cardiac vagal tone be estimated from the 10-second ECG?

Ruth M Hamilton1, Peter S McKechnie, Peter W Macfarlane.   

Abstract

BACKGROUND: Heart rate variability (HRV) recorded over 5 min or 24 h is used increasingly to measure autonomic function and as a prognostic indicator in cardiology. Measuring HRV during a standard 10-s ECG would save time and cut costs. The aim of this study, therefore, was to discover whether indices of HRV calculated over 10 s could predict cardiac vagal tone (CVT) recorded over a 5-min period by the NeuroScope, a new instrument that selectively measures vagal tone.
METHODS: A total of 50 subjects had ECGs taken at the beginning, middle and end of a 5-min measurement of CVT. Standard deviation of normal-to-normal RR interval (SDNN), root mean square of successive differences in RR intervals (rMSSD), and the average absolute difference (AAD) in RR intervals were calculated from RR intervals derived from the ECGs. Subjects were divided into a training set (n=40) and a test set (n=10).
RESULTS: Regression equations derived from the training set predicted 5-min mean CVT in the test set with r(2) of 95.8%, 92.9% and 87.9% for AAD, rMSSD and SDNN, respectively. Indices obtained from the third ECG in each set tended to give a closer relationship with CVT than those derived from the first and second ECGs: this could be because of the greater spread of the independent variables in the third set. An underlying linear physiological phenomenon could not be excluded, however, without continuing the measurements over a longer time.
CONCLUSIONS: These results demonstrate that AAD and rMSSD calculated from a 10-s ECG can accurately predict 5-min mean CVT as measured by the NeuroScope.

Mesh:

Year:  2004        PMID: 15159047     DOI: 10.1016/j.ijcard.2003.07.005

Source DB:  PubMed          Journal:  Int J Cardiol        ISSN: 0167-5273            Impact factor:   4.164


  24 in total

1.  Paper electrocardiograph strips may contain overlooked clinical information in screen-detected type 2 diabetes patients.

Authors:  Jesper Fleischer; Morten Charles; Lise Tarnow; Klaus Skovbo Jensen; Hans Nygaard; Annelli Sandbaek; Niels Ejskjaer
Journal:  J Diabetes Sci Technol       Date:  2012-01-01

2.  Design and evaluation of a handheld impedance plethysmograph for measuring heart rate variability.

Authors:  N K Kristiansen; J Fleischer; M S Jensen; K S Andersen; H Nygaard
Journal:  Med Biol Eng Comput       Date:  2005-07       Impact factor: 2.602

3.  Reliability and accuracy of heart rate variability metrics versus ECG segment duration.

Authors:  James McNames; Mateo Aboy
Journal:  Med Biol Eng Comput       Date:  2006-08-22       Impact factor: 2.602

4.  Novel measure of autonomic remodeling associated with sudden cardiac arrest in diabetes.

Authors:  Yang Yang; Aapo L Aro; Sandeep G Nair; Reshmy Jayaraman; Kyndaron Reinier; Carmen Rusinaru; Audrey Uy-Evanado; Hirad Yarmohammadi; Jonathan Jui; Sumeet S Chugh
Journal:  Heart Rhythm       Date:  2017-07-13       Impact factor: 6.343

5.  Using the multi-parameter variability of photoplethysmographic signals to evaluate short-term cardiovascular regulation.

Authors:  Xiang Chen; Ning Liu; Yuanyuan Huang; Feng Yun; Jue Wang; Jin Li
Journal:  J Clin Monit Comput       Date:  2014-11-19       Impact factor: 2.502

Review 6.  Heart rate variability indices for very short-term (30 beat) analysis. Part 1: survey and toolbox.

Authors:  Anne-Louise Smith; Harry Owen; Karen J Reynolds
Journal:  J Clin Monit Comput       Date:  2013-05-15       Impact factor: 2.502

7.  Ultra-short-term heart rate variability indexes at rest and post-exercise in athletes: evaluating the agreement with accepted recommendations.

Authors:  Michael R Esco; Andrew A Flatt
Journal:  J Sports Sci Med       Date:  2014-09-01       Impact factor: 2.988

8.  Can short-term heart rate variability be used to monitor fentanyl-midazolam induced changes in ANS preceding respiratory depression?

Authors:  Anne-Louise Smith; Harry Owen; Karen J Reynolds
Journal:  J Clin Monit Comput       Date:  2014-09-20       Impact factor: 2.502

Review 9.  Analysis of rapid heart rate variability in the assessment of anticholinergic drug effects in humans.

Authors:  Jani Penttilä; Tom Kuusela; Harry Scheinin
Journal:  Eur J Clin Pharmacol       Date:  2005-08-30       Impact factor: 2.953

10.  Resting heart rate, heart rate variability and functional decline in old age.

Authors:  Giulia Ogliari; Simin Mahinrad; David J Stott; J Wouter Jukema; Simon P Mooijaart; Peter W Macfarlane; Elaine N Clark; Patricia M Kearney; Rudi G J Westendorp; Anton J M de Craen; Behnam Sabayan
Journal:  CMAJ       Date:  2015-08-31       Impact factor: 8.262

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.