Yohannes R, Jeffries G, Eskandari S, Calamaro J, Zetola NM, Healy WJ. Physiology-guided mechanical ventilation: Monitoring, proportional assist, and bounded automation. World J Crit Care Med 2026; 15(3): 119806 [DOI: 10.5492/wjccm.119806]
Corresponding Author of This Article
William J Healy, MD, Assistant Professor, Division of Pulmonary, Critical Care, and Sleep Medicine, Medical College of Georgia, 120 15th Street, Augusta, GA 30912, United States. wihealy@augusta.edu
Research Domain of This Article
Critical Care Medicine
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review-article
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World J Crit Care Med. Sep 9, 2026; 15(3): 119806 Published online Sep 9, 2026. doi: 10.5492/wjccm.119806
Physiology-guided mechanical ventilation: Monitoring, proportional assist, and bounded automation
Robel Yohannes, Gavin Jeffries, Shervin Eskandari, Jacob Calamaro, Nicola M Zetola, William J Healy
Robel Yohannes, Gavin Jeffries, Shervin Eskandari, Jacob Calamaro, Medical College of Georgia, Augusta University, Augusta, GA 30912, United States
Nicola M Zetola, William J Healy, Division of Pulmonary, Critical Care, and Sleep Medicine, Medical College of Georgia, Augusta, GA 30912, United States
Author contributions: Yohannes R, Jeffries G, Eskandari S, Calamaro J and Healy WJ conceived and designed the manuscript framework; Yohannes R drafted the initial manuscript; Jeffries G and Eskandari S contributed to literature review and synthesis of physiologic monitoring and proportional ventilation sections; Calamaro J contributed to drafting and revision of sections related to computational and artificial intelligence applications; Zetola NM and Healy WJ provided critical revision for important intellectual content and clinical accuracy; Healy WJ supervised the project; and all authors have read and approved the final manuscript.
AI contribution statement: During the preparation of this manuscript, Grammarly was utilized solely for spelling, grammar, and syntax refinement. Its use was limited to improving clarity and readability of text that had already been fully developed by the authors. No AI tools were used to generate any portion of the manuscript, including the Abstract, Introduction, Materials and Methods, Results, Discussion, or Conclusion. No AI tool was used for language polishing, translation, data analysis, or writing assistance of the manuscript. AI tools did not contribute to the design of the study or the interpretation of its results, and no images included in this manuscript were generated using AI. All content was created, reviewed, and verified by the authors to ensure accuracy and maintain the originality and integrity of the work.
Conflict-of-interest statement: The authors declare that they have no financial or non-financial conflicts of interest related to the content of this manuscript.
Corresponding author: William J Healy, MD, Assistant Professor, Division of Pulmonary, Critical Care, and Sleep Medicine, Medical College of Georgia, 120 15th Street, Augusta, GA 30912, United States. wihealy@augusta.edu
Received: February 6, 2026 Revised: March 5, 2026 Accepted: May 14, 2026 Published online: September 9, 2026 Processing time: 196 Days and 15.8 Hours
Abstract
Mechanical ventilation has evolved into a complex intervention that influences lung injuries, respiratory muscle function, and hemodynamic stability. Although lung-protective strategies improve outcomes in acute respiratory distress syndrome, bedside management remains limited by incomplete monitoring of key physiologic variables, including lung stress, inspiratory effort and regional ventilation. This constrains decision such as positive end-expiratory pressure titration and ventilatory assist targeting. Emerging technologies aim to address these gaps by improving physiological assessment and enabling more individualized care. Tools such as esophageal manometry, airway occlusion pressure (P0.1), diaphragm electrical activity, and electrical impedance tomography provide insight into lung mechanics, respiratory drive, and regional ventilation. Proportional modes of ventilation improve patient-synchrony, though their impact on patient-centered outcomes remains variables. Automation and artificial intelligence are increasingly applied to ventilator management, supporting wave analysis, detection of asynchrony, and prediction of weaning readiness. These tools may also assist clinical decision-making within predefined safety limit. We propose a pragmatic, clinical-directed framework integrating physiologic monitoring, proportional assist, and bounded decision support to optimize lung protection, diaphragm function, and hemodynamica stability.
Core Tip: Mechanical ventilation should be approached as a dynamic, patient-specific therapy rather than a fixed protocol. Integrating physiologic monitoring of respiratory effort, lung stress, and regional ventilation can help clinicians individualize support while balancing lung protection and diaphragm preservation. For example, ventilatory assist may be titrated to maintain moderate inspiratory effort rather than targeting airway pressures or tidal volume alone. Emerging monitoring, proportional assist modes, and bounded automation are best viewed as tools that augment physiologic assessment while preserving clinician judgment in the management of critically ill patients.
