Bacterial infection leading to organ failure is the most common cause of death in critically ill patients. Early diagnosis and expeditious treatment is a cornerstone of therapy. Evaluating the systemic host response to infection as a complex system provides novel insights: however, bedside application with clinical value remains wanting. Providing an integrative measure of an altered host response, the patterns and character of heart rate fluctuations measured over intervals-in-time may be

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... sed with a panel of mathematical techniques that quantify overall fluctuation, spectral composition, scale-free variation, and degree of irregularity or complexity. Using these techniques, heart rate variability (HRV) has been documented to be both altered in the presence of systemic infection, and correlated with its severity. In this review and analysis, we evaluate the use of HRV monitoring to provide early diagnosis of infection, document the prognostic implications of altered HRV in infection, identify current limitations, highlight future research challenges, and propose improvement strategies. Given existing evidence and potential for further technological advances, we believe that longitudinal, individualized, and comprehensive HRV monitoring in critically ill patients at risk for or with existing infection offers a means to harness the clinical potential of this bedside application of complex systems science. APACHE = Acute Physiological and Chronic Health Evaluation; ApEn = approximate entropy; EGT = early goal-directed therapy; FFT = fast Fourier transform; HF = high frequency; HR = heart rate; HRC = heart rate characteristics; HRV = heart rate variability; LF = low frequency; MODS = multiple organ dysfunction syndrome; MSE = multiscale entropy; RMSSD = root mean square successive difference; SAA = sample asymmetry analysis; SampEn = sample entropy; SD = standard deviation.