{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T18:44:19Z","timestamp":1763750659164,"version":"3.45.0"},"reference-count":31,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:00:00Z","timestamp":1763683200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>Network physiology is a multidisciplinary field that offers a comprehensive view of the complex interactions within the human body, emphasising the critical role of organ system connectivity in health and disease. This approach has the potential to provide pathophysiological insights into complex and emerging diseases. This study aims to evaluate the effectiveness of physiological network mapping in predicting outcomes for COVID-19 patients, using data from the first wave of the pandemic. Routine clinical and laboratory data from 202 patients with COVID-19 were retrospectively analysed. Twenty-one physiological variables representing various organ systems were used to construct organ network connectivity through correlation analysis. Parenclitic network analysis was also employed to measure deviations in individual patients\u2019 organ system correlations from the reference physiological interactions observed in survivors. We observed distinct features in the correlation network maps of non-survivors compared to survivors. In non-survivors, there was a significant correlation between the level of consciousness and the liver enzyme cluster, a relationship not present in the survivor group. This relationship remained significant even after adjusting for age and degree of hypoxia. Additionally, a strong correlation along the BUN\u2013potassium axis was identified in non-survivors, suggesting varying degrees of kidney damage and impaired potassium homeostasis in non-survivors. These findings highlight the potential of network physiology as a valuable tool for uncovering complex inter-organ interactions in emerging diseases, with applications that could support clinicians, researchers, and policymakers in future epidemics.<\/jats:p>","DOI":"10.1371\/journal.pone.0337333","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T18:39:19Z","timestamp":1763750359000},"page":"e0337333","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Can physiological network mapping reveal pathophysiological insights into emerging diseases? 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