Cecilia Morandotti, Matthew Wikner, Qijun Li, Emily Ito, Tope Oyelade, Calix Tan, Pin-Yu Chen, Anika Cawthorn, Watjana Lilaonitkul, Ali R Mani
{"title":"心肺信息传递减少与脓毒症重症患者病情恶化和预后不良有关。","authors":"Cecilia Morandotti, Matthew Wikner, Qijun Li, Emily Ito, Tope Oyelade, Calix Tan, Pin-Yu Chen, Anika Cawthorn, Watjana Lilaonitkul, Ali R Mani","doi":"10.1152/japplphysiol.00642.2024","DOIUrl":null,"url":null,"abstract":"<p><p>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 ([Formula: see text]) 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 [Formula: see text] 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 [Formula: see text] to HR [TE ([Formula: see text] → 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 ([Formula: see text] → RR), and TE ([Formula: see text] → 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.<b>NEW & NOTEWORTHY</b> 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.</p>","PeriodicalId":15160,"journal":{"name":"Journal of applied physiology","volume":" ","pages":"289-300"},"PeriodicalIF":3.3000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Decreased cardio-respiratory information transfer is associated with deterioration and a poor prognosis in critically ill patients with sepsis.\",\"authors\":\"Cecilia Morandotti, Matthew Wikner, Qijun Li, Emily Ito, Tope Oyelade, Calix Tan, Pin-Yu Chen, Anika Cawthorn, Watjana Lilaonitkul, Ali R Mani\",\"doi\":\"10.1152/japplphysiol.00642.2024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 ([Formula: see text]) 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 [Formula: see text] 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 [Formula: see text] to HR [TE ([Formula: see text] → 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 ([Formula: see text] → RR), and TE ([Formula: see text] → 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.<b>NEW & NOTEWORTHY</b> 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. 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Decreased cardio-respiratory information transfer is associated with deterioration and a poor prognosis in critically ill patients with sepsis.
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 ([Formula: see text]) 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 [Formula: see text] 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 [Formula: see text] to HR [TE ([Formula: see text] → 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 ([Formula: see text] → RR), and TE ([Formula: see text] → 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.
期刊介绍:
The Journal of Applied Physiology publishes the highest quality original research and reviews that examine novel adaptive and integrative physiological mechanisms in humans and animals that advance the field. The journal encourages the submission of manuscripts that examine the acute and adaptive responses of various organs, tissues, cells and/or molecular pathways to environmental, physiological and/or pathophysiological stressors. As an applied physiology journal, topics of interest are not limited to a particular organ system. The journal, therefore, considers a wide array of integrative and translational research topics examining the mechanisms involved in disease processes and mitigation strategies, as well as the promotion of health and well-being throughout the lifespan. Priority is given to manuscripts that provide mechanistic insight deemed to exert an impact on the field.