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Physiological network approach to prognosis in cirrhosis: A shifting paradigm.
- Source :
-
Physiological Reports . Jul2024, Vol. 12 Issue 13, p1-21. 21p. - Publication Year :
- 2024
-
Abstract
- Decompensated liver disease is complicated by multiāorgan failure and poor prognosis. The prognosis of patients with liver failure often dictates clinical management. Current prognostic models have focused on biomarkers considered as individual isolated units. Network physiology assesses the interactions among multiple physiological systems in health and disease irrespective of anatomical connectivity and defines the influence or dependence of one organ system on another. Indeed, recent applications of network mapping methods to patient data have shown improved prediction of response to therapy or prognosis in cirrhosis. Initially, different physical markers have been used to assess physiological coupling in cirrhosis including heart rate variability, heart rate turbulence, and skin temperature variability measures. Further, the parenclitic network analysis was recently applied showing that organ systems connectivity is impaired in patients with decompensated cirrhosis and can predict mortality in cirrhosis independent of current prognostic models while also providing valuable insights into the associated pathological pathways. Moreover, network mapping also predicts response to intravenous albumin in patients hospitalized with decompensated cirrhosis. Thus, this review highlights the importance of evaluating decompensated cirrhosis through the network physiologic prism. It emphasizes the limitations of current prognostic models and the values of network physiologic techniques in cirrhosis. [ABSTRACT FROM AUTHOR]
- Subjects :
- *CIRRHOSIS of the liver
*HEART beat
*LIVER failure
*PROGNOSIS
*PROGNOSTIC models
Subjects
Details
- Language :
- English
- ISSN :
- 2051817X
- Volume :
- 12
- Issue :
- 13
- Database :
- Academic Search Index
- Journal :
- Physiological Reports
- Publication Type :
- Academic Journal
- Accession number :
- 178468898
- Full Text :
- https://doi.org/10.14814/phy2.16133