Decomplexification in critical illness and injury: Relationship between heart rate variability, severity of illness, and outcome

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Abstract
Objectives: To determine if decomplexification of heart rate dynamics occurs in critically ill and injured pediatric patients. We hypothesized that heart rate power spectra, a measure of heart rate dynamics, would inversely correlate with measures of severity of illness and outcome. Design: A prospective clinical study. Setting: A 12-bed pediatric intensive care unit (ICU) in a tertiary care children's hospital. Patients: One hundred thirty-five consecutive pediatric ICU admissions. Interventions: None. Measurements and Main Results: We compared heart rate power spectra with the Pediatric Risk of Mortality (PRISM) score, the Pediatric Cerebral Performance Category (PCPC), and the Pediatric Overall Performance Category (POPC). We found significant negative correlations between minimum low-frequency and high-frequency heart rate power spectral values recorded during ICU stay and the maximum PRISM score (log low-frequency heart rate power vs. PRISM, r2 = .293, p < .001; and log high-frequency heart rate power vs. PRISM, r2 = .243, p < .001) and outcome at ICU discharge (log low-frequency heart rate power vs. POPC or PCPC, r2 = .429, p < .001; and log high-frequency heart rate power vs. POPC or PCPC, r2 = .271, p < .001). Conclusions: Our data support the hypothesis that measures of heart rate power spectra are inversely related and negatively correlated to severity of illness and outcome in critically ill and injured children. The phenomenon of decomplexification of physiologic dynamics may have important clinical implications in critical illness and injury. (Crit Care Med 1998; 26:352-357) For years, physicians have believed that physiologic systems existed in a so-called “steady” or “homeostatic” state and that these systems exhibited a linear response when stimulated. It is now clear that physiologic systems exist in a nonlinear, dynamic state [1-4]. In other words, physiologic systems constantly change over time and respond to stimuli in a nonlinear manner. Furthermore, healthy physiologic systems exhibit marked signal variability, while aging or diseased systems show a loss of variability [2,5]. This decreased variability, or increased regularity, in physiologic dynamics has been termed “decomplexification” [1]. Commonly monitored physiologic signals, including mean heart rate, blood pressure, and cardiac output, correlate poorly with survival in both experimental models of circulatory shock and in critically ill patients [6]. These first-order linear measures do not adequately describe dynamic changes. Power spectral analysis of heart rate variability, a second-order linear measure, allows for quantification in the frequency domain of dynamic changes in beat-to-beat heart rate oscillations [1,5-10]. Power spectral analysis of heart rate variability has been used to quantify physiologic changes in many diseases, including hypovolemia, congestive heart failure, hypertension, diabetes mellitus, renal failure, cardiac transplantation, traumatic quadriplegia, and sepsis [10-19]. We hypothesized that decomplexification of heart rate dynamics would occur over a broad range of critical illness and injury, and would inversely correlate with disease severity and outcome in a pediatric population. To test this hypothesis, we prospectively studied 135 consecutive admissions to the Strong Children's Critical Care Center. We compared heart rate power spectra with a previously validated measure of severity of illness, the Pediatric Risk of Mortality (PRISM) score [20], and with validated measures of outcome from pediatric intensive care, the Pediatric Overall Performance Category (POPC) [21] and Pediatric Cerebral Performance Category (PCPC) [21] scores.