• 1. Department of Respiratory Care, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, P. R. China;
  • 2. Department of Respiratory and Critical Care Medicine, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan 610072, P. R. China;
  • 3. Department of Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, P. R. China;
  • 4. Department of Critical Care Medicine, West China Tianfu Hospital of Sichuan University, Chengdu, Sichuan 610213, P. R. China;
ZHOU Yongfang, Email: zyfmg@163.com; KANG Yan, Email: kangyan@scu.edu.cn
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Objective To evaluate the accuracy of invasive ventilator monitoring for airway resistance (Raw) and respiratory compliance (Crs), and identify factors influencing measurement precision in pressure control ventilation (PCV) mode. Methods Utilizing an ASL5000 lung simulator, we configured airway resistance settings (3 cmH2O·L–1·s–1 and 15 cmH2O·L–1·s–1) and compliance values (15 mL/cmH2O and 50 mL/cmH2O). ASL5000 was connected to SV800 ventilator via endotracheal tubes (internal diameters 6.5 mm, 7.0 mm, 7.5 mm, and 8.0 mm) in PCV mode, inspiratory pressures was set 5 cmH2O, 10cmH2O, 15cmH2O, 20 cmH2O, yielding 352 datasets. Absolute differences (ΔRaw, ΔCrs) and percentage differences (ΔRaw%, ΔCrs%) between ventilator-monitored and simulator-setted were calculated. Correlation and multiple linear regression analyses were employed to evaluate the main and interaction effects of tube diameter, simulated airway resistance/respiratory compliance, and inspiratory pressure on ΔRaw% and ΔCrs%.Results In pressure control mode, median ΔRaw was 2.0 (0.0, 4.0) cmH2O·L–1·s–1 ; median ΔCrs was 6.5 (5.0, 11.0) mL/cmH2O. Tube diameter (β=–44.32, 95%CI –50.90 to –37.74, P<0.001) and simulated resistance (β=–12.24, 95%CI –12.83 to –11.66, P<0.001) were significant negative predictors of ΔRaw%, while inspiratory pressure (β=4.88, 95%CI 4.25 to 5.50, P<0.001) and simulated compliance (β=1.10, 95%CI 0.90 to 1.30, P<0.001) were significant positive predictors. The negative association between simulated resistance and ΔRaw% was attenuated by increased simulated compliance (β=–0.10, 95%CI –0.13 to –0.07, P<0.001); the negative effect of tube diameter on ΔRaw% was less pronounced at higher inspiratory pressures (β=–1.89, 95%CI –2.99 to –0.79, P=0.001). Inspiratory pressure had no significant effect on ΔCrs% (P=0.909), Tube diameter (β=–4.30, 95%CI –5.19 to –3.40, P<0.001), simulated compliance (β=–0.18, 95%CI –0.21 to –0.16, P<0.001) were significant negative predictors of ΔCrs%; simulated resistance (β=–0.11, 95%CI –0.19 to –0.03, P=0.009) negatively affected ΔCrs% initially, but its interaction with simulated compliance was not significant (P=0.438). The interaction between tube diameter and inspiratory pressure significantly reduced ΔCrs% (β=–0.21, 95%CI –0.37 to –0.05, P=0.011). Conclusions In PCV mode, the SV800 ventilator achieved manufacturer-specified monitoring accuracy. ΔRaw% correlated negatively with tube diameter and simulated resistance, interaction effects between simulated resistance and compliance, interaction effects between tube diameter-inspiratory pressure, and positively with simulated compliance and inspiratory pressure. Inspiratory pressure demonstrated no impact on compliance monitoring, whereas tube diameter, simulated compliance, tube diameter interaction with inspiratory pressure reduced ΔCrs%.

Citation: CHEN Lijuan, WANG Peng, ZHOU Yongfang, KANG Yan. Accuracy and its influencing factors of airway resistance and respiratory compliance monitored by pressure controlled mechanical ventilation: a bench study. Chinese Journal of Respiratory and Critical Care Medicine, 2026, 25(5): 319-325. doi: 10.7507/1671-6205.202601115 Copy

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