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Decreased cardio-respiratory information transfer is associated with deterioration and a poor prognosis in critically ill patients with sepsis | Journal of Applied Physiology | American Physiological Society
Assessing illness severity in the intensive care unit (ICU) is crucial for early prediction of deterioration and prognosis. Traditional prognostic scores often treat organ systems separately, overlooking the body’s interconnected nature. Network physiology offers a new approach to understanding these complex interactions. This study used the concept of transfer entropy (TE) to measure information flow between heart rate (HR), respiratory rate (RR), and capillary oxygen saturation in critically ill patients with sepsis, hypothesizing that TE between these signals would correlate with disease outcome. The retrospective cohort study utilized the Medical Information Mart for Intensive Care III Clinical Database, including patients who met Sepsis-3 criteria on admission and had 30 min of continuous HR, RR, and data. TE between the signals was calculated to create physiological network maps. Cox regression assessed the relationship between cardiorespiratory network indices and both deterioration [Sequential Organ Failure Assessment (SOFA) score increase of ≥2 points at 48 h] and 30-day mortality. Among 164 patients, higher information flow from to HR [TE ( → HR)] and reciprocal flow between HR and RR [TE (RR → HR) and TE (HR → RR)] were linked to reduced mortality, independent of age, mechanical ventilation, SOFA score, and comorbidity. Reductions in TE (HR → RR), TE (RR → HR), TE ( → RR), and TE ( → HR) were associated with an increased risk of 48-h deterioration. After adjustment for potential confounders, only TE (HR → RR) and TE (RR → HR) remained statistically significant. The study confirmed that physiological network mapping using routine signals in patients with sepsis could indicate illness severity and that higher TE values were generally associated with improved outcomes. NEW & NOTEWORTHY This study adopts an integrative approach through physiological network analysis to investigate sepsis, with the goal of identifying differences in information transfer between physiological signals in sepsis survivors versus nonsurvivors. We found that greater information flow between heart rate, respiratory rate, and capillary oxygen saturation was associated with reduced mortality, independent of age, disease severity, and comorbidities. In addition, reduced information transfer was linked to an increased risk of 48-h deterioration in patients with sepsis.
