TY - JOUR
T1 - Characterization of common measures of heart period variability in healthy human subjects
T2 - Implications for patient monitoring
AU - Rickards, Caroline A.
AU - Ryan, Kathy L.
AU - Convertino, Victor A.
N1 - Funding Information:
The authors would like to thank Gary Muniz and Gilbert Moralez for their technical assistance with data collection and analysis, and the subjects who participated in this study for their time and cheerful co-operation. This research was supported by funding from the US Army Combat Casualty Care Program. The views expressed herein are the private views of the authors and are not to be construed as representing those of the Department of Defense or the Department of the Army. This research was performed while Caroline A. Rickards held a National Research Council Postdoctoral Research Associateship at the US Army Institute of Surgical Research.
PY - 2010/2
Y1 - 2010/2
N2 - Objective: Heart period variability has been considered for clinical assessment of autonomic function, determining the presence of haemorrhage or disease states, and for predicting mortality from traumatic injury. However, for heart period variability to be clinically useful, a number of important methodological issues should be addressed, including the minimum number of R-R intervals (RRI) required for accurate derivation, and the reproducibility of these metrics. Methods: ECGs were recorded for ≥10 min in 18 resting, supine subjects (12 M/6 F; 19-55 years). Heart period variability analyses included 21 time, frequency and complexity domain metrics. For assessment of minimum RRIs required, measurements were made from ECG recordings of 5 min down to 30 s for time and frequency domain metrics, and from 800 RRIs down to 100 RRIs for complexity metrics, by methodical truncation of the data set. Inter-subject variability was assessed by calculating the range and co-efficient of variation (%CV) across all subjects. Two independent 30 s or 100 RRI ECG segments were used to assess intra-subject variability via calculation of %CV in each subject. Results: Six time and frequency domain metrics were robust down to 30 s of data, while five complexity metrics were robust down to 100 RRIs. All time and frequency domain metrics (except for RRI) exhibited high inter-subject variability (CVs ≥ 30.0%), while five of eleven complexity metrics displayed low inter-subject variability (CVs ≤ 8.5%). In the assessment of intra-subject variability in metrics valid with 30 s or 100 RRIs of ECG, only one time domain and four complexity metrics had CVs < 10%. Conclusions: Metrics that are highly reproducible and require few RRIs are advantageous for patient monitoring as less time is required to assess physiological status and initiate early interventions. Based on our analyses from healthy, resting humans, we have identified a select cohort of heart period variability metrics that performed well in regards to these two criteria.
AB - Objective: Heart period variability has been considered for clinical assessment of autonomic function, determining the presence of haemorrhage or disease states, and for predicting mortality from traumatic injury. However, for heart period variability to be clinically useful, a number of important methodological issues should be addressed, including the minimum number of R-R intervals (RRI) required for accurate derivation, and the reproducibility of these metrics. Methods: ECGs were recorded for ≥10 min in 18 resting, supine subjects (12 M/6 F; 19-55 years). Heart period variability analyses included 21 time, frequency and complexity domain metrics. For assessment of minimum RRIs required, measurements were made from ECG recordings of 5 min down to 30 s for time and frequency domain metrics, and from 800 RRIs down to 100 RRIs for complexity metrics, by methodical truncation of the data set. Inter-subject variability was assessed by calculating the range and co-efficient of variation (%CV) across all subjects. Two independent 30 s or 100 RRI ECG segments were used to assess intra-subject variability via calculation of %CV in each subject. Results: Six time and frequency domain metrics were robust down to 30 s of data, while five complexity metrics were robust down to 100 RRIs. All time and frequency domain metrics (except for RRI) exhibited high inter-subject variability (CVs ≥ 30.0%), while five of eleven complexity metrics displayed low inter-subject variability (CVs ≤ 8.5%). In the assessment of intra-subject variability in metrics valid with 30 s or 100 RRIs of ECG, only one time domain and four complexity metrics had CVs < 10%. Conclusions: Metrics that are highly reproducible and require few RRIs are advantageous for patient monitoring as less time is required to assess physiological status and initiate early interventions. Based on our analyses from healthy, resting humans, we have identified a select cohort of heart period variability metrics that performed well in regards to these two criteria.
KW - ECG
KW - Electrocardiography
KW - Heart period variability
KW - Heart rate
KW - Reference values
KW - Reliability and validity
KW - Reproducibility of results
UR - http://www.scopus.com/inward/record.url?scp=77249104443&partnerID=8YFLogxK
U2 - 10.1007/s10877-009-9210-z
DO - 10.1007/s10877-009-9210-z
M3 - Article
C2 - 20157801
AN - SCOPUS:77249104443
SN - 1387-1307
VL - 24
SP - 61
EP - 70
JO - Journal of Clinical Monitoring and Computing
JF - Journal of Clinical Monitoring and Computing
IS - 1
ER -