Evidence Based Care

Evidence Based Care

From Reactive Correction to Predictive Personalization: The Next Frontier in Endotracheal Tube Cuff Pressure Management at the Point of Care

Document Type : Letter to editor

Authors
1 Department of Anesthesiology, Imam Reza Hospital, Mashhad University of Medical Sciences, Mashhad, Iran.
2 Department of Extra-Corporeal Circulation (ECC), Razavi Hospital, Imam Reza International University, Mashhad, Iran.
Abstract
Background: Endotracheal tube cuff pressure (ETCP) management is a critical aspect of mechanical ventilation in intensive care units, and positional changes significantly affect pressure fluctuations.
Aim: This letter reflects on our recently published study examining the effects of body position changes and vital signs on ETCP in children following Glenn shunt surgery and proposes a forward-looking roadmap for achieving optimal point-of-care (POC) management.
Implications for Practice: We propose four paradigm-shifting directions: (1) transitioning from intermittent to continuous closed-loop control using IoT-enabled devices; (2) developing predictive algorithms using machine learning to forecast pressure changes before repositioning; (3) individualizing ETCP targets via bedside point-of-care ultrasound (POCUS) for anatomical profiling; and (4) integrating drug-position-pressure interactions into clinical decision-making.
Conclusion: The future of ETCP management lies in anticipatory, automated, and individualized approaches. Multicenter trials comparing closed-loop, algorithm-driven systems against standard manual protocols are urgently needed.
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Articles in Press, Accepted Manuscript
Available Online from 15 September 2026