Key result
Multimodal monitoring and AI may facilitate real-time autonomic function assessment in critically ill cancer patients.
Why the study?
In critically ill cancer patients, autonomic nervous system dysfunction may contribute to hemodynamic instability and organ dysfunction and may be exacerbated by malignancy-related injury and anticancer treatment.
Advanced multimodal assessment of autonomic dysfunction may improve risk stratification and individualized management in critically ill cancer patients.
May support AI-enhanced autonomic monitoring for risk stratification in cancer ICU patients; leaves open prospective validation before adoption.
In critically ill cancer patients, autonomic nervous system (ANS) dysfunction may contribute to hemodynamic instability and organ dysfunction and may be exacerbated by malignancy-related injury and anticancer treatment. This narrative review summarizes conventional methods for assessing ANS function, including heart rate variability (HRV), blood pressure variability (BPV), baroreflex sensitivity (BRS), and cardiovascular autonomic reflex testing, together with emerging approaches such as high-resolution multimodal monitoring (MMM) and artificial intelligence (AI). Host-organ unregulated response (HOUR) framework is used to integrate interactions among autonomic, neuroendocrine, inflammatory, immune, coagulation, metabolic, bioenergetic,and microcirculatory dysregulation. Collectively, these approaches may facilitate real-time assessment of autonomic function and tissue perfusion, thereby supporting risk stratification and individualized management in critically ill cancer patients.
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Gong et al. (2026) conducted a review in Critically ill cancer patients. Methods for assessing autonomic nervous system function was evaluated. Conventional and emerging multimodal assessment strategies, including high-resolution monitoring and AI, may facilitate real-time assessment of autonomic function in critically ill cancer patients.
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