Reduced heart rate multiscale entropy predicts death in critical illness: a study of physiologic complexity in 285 trauma patients

Journal of Critical Care
Patrick R NorrisJohn A Morris

Abstract

We have shown previously that reduced integer heart rate variability (HRVi) predicts death in trauma patients. We hypothesized that heart rate multiscale entropy (MSE), a potential measurement of physiologic complexity, would predict death more robustly than HRVi. Two hundred eighty-five patients had heart rate data meeting completeness and density criteria (>12 hours, >/=0.4 Hz) available in the first 24 hours after admission. Missing data points were interpolated, and a publicly available algorithm (MSE of Costa et al; Phys Rev E Stat Nonlin Soft Matter Phys. 2005;71[2 Pt 1]) was applied (www.physionet.org, m = 2, r = 0.15). Integer heart rate variability was computed using methods described previously (percentage of 5-minute intervals having heart rate SD between 0.3 and 0.6). Sample entropy was compared between survivors and nonsurvivors at each scale factor using Wilcoxon rank sum test. Logistic regression was used to assess risk of death based on HRVi, MSE, and/or covariates (age, sex, injury severity). Decreased HRVi and MSE each predicted hospital mortality (median day of death, 3; mean, 7.1). Multiscale entropy-based risk stratification (area under the receiver operating characteristic curve [AUC] = 0.76, scale 15) was...Continue Reading

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