Comparison of Pulmonary Compliance Measured by Multiple Linear Regression Versus Traditional Methods in Mechanically Ventilated Patients Publisher

Summary: Can lung stiffness be tracked with every breath? A ventilator study found regression estimates correlated with standard values but were lower. #CriticalCare #RespiratoryHealth

Habibzadeh M R ; Saghaei M ; Shojaei M
Source: Archives of Anesthesiology and Critical Care Published:2026

Abstract

Background: Pulmonary compliance measurement is a critical component of monitoring mechanically ventilated patients with respiratory failure. The traditional method calculates compliance by dividing delivered tidal volume by the resultant airway pressure (plateau pressure minus positive end-expiratory pressure [PEEP]). However, this approach requires intermittent ventilator disconnection, limiting its frequency. A novel method using multiple linear regression (MLR) analysis of continuous pressure and flow waveforms enables breath-to-breath compliance measurement without disrupting ventilation. This study compares pulmonary compliance values obtained by MLR and traditional methods. Methods: In this clinical study, pulmonary compliance was measured and compared in consecutive mechanically ventilated patients using both traditional and MLR methods. MLR-derived compliance was obtained using the ventilator’s integrated monitoring function, while traditional compliance was calculated as tidal volume divided by (plateau pressure – PEEP). Results: Among 200 enrolled patients, the two methods showed strong correlation (*r* = 0.9, *p* < 0.01). However, MLR-derived compliance values were consistently lower than those from the traditional method (44.74 ± 21.78 mL/cmH2O vs. 57.95 ± 26.64 mL/cmH2O, *p* < 0.01). Conclusion: MLR is a reliable alternative for continuous pulmonary compliance monitoring, though its systematically lower values—likely reflecting dynamic rather than static compliance—may necessitate a correction factor. The method’s ability to provide breath-to-breath measurements offers significant clinical advantages over traditional intermittent assessments. Copyright © 2026 Tehran University of Medical Sciences.