ArticleCritical care (London, England)2019
Organ system network analysis and biological stability in critically ill patients.
Article in Critical care (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Can physiological network mapping reveal pathophysiological insights into emerging diseases? Lessons from COVID-19.PloS one · 2025Article
- Application of physiological network mapping in the prediction of survival in critically ill patients with acute liver failure.Scientific reports · 2024Article
- Physiological network approach to prognosis in cirrhosis: A shifting paradigm.Physiological reports · 2024Review
- Pupillary dynamics predict long-term outcome in a cohort of acute traumatic brain injury coma patients.Annals of clinical and translational neurology · 2023Article
- Differential Network Testing Reveals Diverging Dynamics of Organ System Interactions for Survivors and Non-survivors in Intensive Care Medicine.Frontiers in physiology · 2021Article
- Health and Disease Are Dynamic Complex-Adaptive States Implications for Practice and Research.Frontiers in psychiatry · 2021Article
- Organ System Network Disruption Is Associated With Poor Prognosis in Patients With Chronic Liver Failure.Frontiers in physiology · 2020Article
- Acute Kidney Injury Induces Innate Immune Response and Neutrophil Activation in the Lung.Frontiers in medicine · 2020Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundContinuous coordination among organ systems is necessary to maintain biological stability in humans. Organ system network analysis in addition to organ-oriented medicine is expected to improve patient outcomes. However, organ system networks remain beyond clinical application with little evidence for their importance on homeostatic mechanisms. This proof-of-concept study examined the impact of organ system networks on systemic stability in severely ill patients.
methodsPatients admitted to the intensive care unit of the University of Tokyo Hospital with one representative variable reflecting the condition of each of the respiratory, cardiovascular, renal, hepatic, coagulation, and inflammatory systems were enrolled. Relationships among the condition of individual organ systems, inter-organ connections, and systemic stability were evaluated between non-survivors and survivors whose organ system conditions were matched to those of the non-survivors (matched survivors) as well as between non-survivors and all survivors. We clustered these six organ systems using principal component analysis and compared the dispersion of the principal component scores of each cluster using the Ansari-Bradley test to evaluate systemic stability involving multiple organ systems. Inter-organ connections were evaluated using Spearman's rank test.
resultsAmong a total of 570 enrolled patients, 91 patients died. The principal component analysis yielded the respiratory-renal-inflammatory and cardiovascular-hepatic-coagulation system clusters. In the respiratory-renal-inflammatory cluster, organ systems were connected in both the survivors and the non-survivors. The principal component scores of the respiratory-renal-inflammatory cluster were dispersed similarly (stable cluster) in the non-survivors, the matched survivors, and the total survivors irrespective of the severity of individual organ system dysfunction. Conversely, in the cardiovascular-hepatic-coagulation cluster, organ systems were connected only in the survivors, and the principal component scores of the cluster were significantly dispersed (unstable cluster) in the non-survivors compared to the total survivors (P = 0.002) and the matched survivors (P = 0.004).
conclusionsThis study demonstrated that systemic instability was closely associated with network disruption among organ systems irrespective of their dysfunction severity. Organ system network analysis is necessary to improve outcomes in severely ill patients.
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