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Characterization of Common Measures of Heart Period Variability in Healthy Human Subjects: Implications for Patient Monitoring

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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 greater than or equal to 10 min in 18 resting, supine subjects 12 M6 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 30s 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 greater than or equal to 30.0, while five of eleven complexity metrics displayed low inter-subject variability CVs less than or equal to 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 less than 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.

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  • Anatomy and Physiology
  • Medicine and Medical Research
  • Biomedical Instrumentation and Bioengineering

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