The influence on accuracy of respiratory mechanics estimation with different inspiratory effort during noninvasive ventilation: a bench study_Chinese Journal of Respiratory and Critical Care Medicine

Authors：

 CHEN Yuqing ¹ , YUAN Yueyang ² , ZHANG Hai ¹ , LI Feng ¹ , LI Xingwang ³

1. Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, P. R. China;
2. School of Mechanical and Electrical Engineering, Hunan City University, Yiyang, Hunan 413049, P. R. China;
3. The Bio-X Institutes, Shanghai Jiao Tong University, Shanghai 200030, P. R. China;

Corresponding author：

CHEN Yuqing, Email: chenyqn69@163.com

Keywords：

Respiratory mechanics; Resistance; Compliance; Dynamic; Noninvasive ventilation

DOI：

10.7507/1671-6205.202104021

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

Objective To evaluate the influence on the estimation of respiratory mechanics with dynamic signal analysis approach during noninvasive positive pressure ventilation (NPPV) under different inspiratory effort conditions. Methods The Respironics V60 ventilator was connected to a ASL5000 lung simulator, which simulate lung mechanics in healthy adults with body weight from 65 to 70 kg, and patients with chronic obstructive pulmonary disease (COPD) and acute respiratory distress (ARDS). Each lung models was subjected to 4 different muscle pressures (P_mus): 0, 5.0, 10.0, and 15.0 cm H₂O. Inspiratory pressure support level was adjusted to maintain tidal volume (V_T) achieving 7.0 mL/kg outputted by ventilator respectively. Positive end expiratory pressure was set at 5.0 cm H₂O and back-up rate was 10 beats per minute. Measurements were conducted at system leaks with 25 to 28 L/min. The respiratory system compliance (C_rs), inspiratory and expiratory resistance (R_insp and R_exp) were estimated by special equations, which was derived from the exhaled V_T, flow rate and airway pressure. Results The driving pressure (DP) was decreased with P_mus increasing, and was 1.0 cm H₂O after P_mus exceeding 10.0 cm H₂O and the V_T was larger than 7.0 mL/kg in normal adult model. The estimated value of C_rs was affected by the changes of P_mus in all three lung models. The significant underestimation of R_aw and the overestimation of C_rs were observed when P_mus level exceed 10.0 cm H₂O. The measured errors of C_rs and R_exp were within 10% in COPD and ARDS model when P_mus was at 5.0 cm H₂O. The underestimation of R_insp was always existed in all P_mus level (P<0.01). Conclusions Using dynamic signal analysis approach, the real-time estimation of respiratory mechanics (C_rs and R_aw) is no need to interrupt the spontaneous breathing during NPPV. Excessive effort will increase the patient’s inspiratory workload, which is not benefit to accurate estimation of respiratory mechanics.

Citation： CHEN Yuqing, YUAN Yueyang, ZHANG Hai, LI Feng, LI Xingwang. The influence on accuracy of respiratory mechanics estimation with different inspiratory effort during noninvasive ventilation: a bench study. Chinese Journal of Respiratory and Critical Care Medicine, 2021, 20(10): 715-720. doi: 10.7507/1671-6205.202104021 Copy

1.	Hess DR. Respiratory mechanics in mechanically ventilated patients. Respir Care, 2014, 59(11): 1773-1794.
2.	Lucangelo U, Bernabè F, Blanch L. Lung mechanics at the bedside: make it simple. Curr Opin Crit Care, 2007, 13(1): 64-72.
3.	Henderson WR, Sheel AW. Pulmonary mechanics during mechanical ventilation. Respir Physiol Neurobiol, 2012, 180(2-3): 162-172.
4.	Mirza S, Clay RD, Koslow MA, et al. COPD Guidelines: A Review of the 2018 GOLD Report. Mayo Clin Proc, 2018, 93(10): 1488-1502.
5.	Gattinoni L, Marini JJ, Collino F, et al. The future of mechanical ventilation: lessons from the present and the past. Crit Care, 2017, 21(1): 183.
6.	Gattinoni L, Tonetti T, Cressoni M, et al. Ventilator-related causes of lung injury: the mechanical power. Intensive Care Med, 2016, 42(10): 1567-1575.
7.	Chiumello D, Carlesso E, Brioni M, et al. Airway driving pressure and lung stress in ARDS patients. Crit Care, 2016, 20: 276.
8.	Levine S, Nguyen T, Taylor N, et al. Rapid disuse atrophy of diaphragm fibers in mechanically ventilated humans. N Engl J Med, 2008, 358(13): 1327-1335.
9.	Yoshida T, Engelberts D, Otulakowski G, et al. Continuous abdominal negative pressure recruits lungs at lower distending pressures. Am J Respir Crit Care Med, 2018, 197(4): 534-537.
10.	Lichtwarck-Aschoff M, Kessler V, Sjöstrand UH, et al. Static versus dynamic respiratory mechanics for setting the ventilator. Br J Anaesth, 2000, 85(4): 577-586.
11.	陈宇清, 袁越阳, 张海, 等. 无创双水平正压通气状态下呼吸力学特性的测算分析研究. 中国呼吸与危重监护杂志, 2019, 18(6): 537-542.
12.	Chen YQ, Cheng KW, Zhou X. Effectiveness of inspiratory termination synchrony with automatic cycling during noninvasive pressure support ventilation. Med Sci Monit, 2016, 22(5): 1694-1701.
13.	Beloncle F, Akoumianaki E, Rittayamai N, et al. Accuracy of delivered airway pressure and work of breathing estimation during proportional assist ventilation: a bench study. Ann Intensive Care, 2016, 6(1): 30.
14.	Arnal JM, Garnero A, Saoli M, et al. Parameters for simulation of adult subjects during mechanical ventilation. Respir Care, 2018, 63(2): 158-168.
15.	Nava S, Bruschi C, Fracchia C, et al. Patient-ventilator interaction and inspiratory effort during pressure support ventilation in patients with different pathologies. Eur Respir J, 1997, 10(1): 177-183.
16.	Gama de Abreu M, Spieth PM, Pelosi P, et al. Noisy pressure support ventilation: a pilot study on a new assisted ventilation mode in experimental lung injury. Crit Care Med, 2008, 36(3): 818-827.
17.	Foti G, Cereda M, Banfi G, et al. End-inspiratory airway occlusion: a method to assess the pressure developed by inspiratory muscles in patients with acute lung injury undergoing pressure support. Am J Respir Crit Care Med, 1997, 156(4 Pt 1): 1210-1216.
18.	Bertoni M, Telias I, Urner M, et al. A novel non-invasive method to detect excessively high respiratory effort and dynamic transpulmonary driving pressure during mechanical ventilation. Crit Care, 2019, 23(1): 346.
19.	Teggia-Droghi M, Grassi A, Rezoagli E, et al. Comparison of two approaches to estimate driving pressure during assisted ventilation. Am J Respir Crit Care Med, 2020, 202(11): 1595-1598.
20.	Volta CA, Marangoni E, Alvisi V, et al. Respiratory mechanics by least squares fitting in mechanically ventilated patients: application on flow-limited COPD patients. Intensive Care Med, 2002, 28(1): 48-52.
21.	Iotti GA, Braschi A, Brunner JX, et al. Respiratory mechanics by least squares fitting in mechanically ventilated patients: applications during paralysis and during pressure support ventilation. Intensive Care Med, 1995, 21(5): 406-413.
22.	Khirani S, Polese G, Aliverti A, et al. On-line monitoring of lung mechanics during spontaneous breathing: a physiological study. Respir Med, 2010, 104(3): 463-471.
23.	Nassar BS, Collett ND, Schmidt GA. The flow-time waveform predicts respiratory system resistance and compliance. J Crit Care, 2012, 27(4): 418.e7-14.
24.	Guillaume Carteaux G, Jordi Mancebo J, Alain Mercat A, et al. Bedside adjustment of proportional assist ventilation to target a predefined range of respiratory effort. Crit Care Med, 2013, 41(9): 2125-2132.
25.	Albani F, Pisani L, Ciabatti G, et al. Flow index: a novel, non-invasive, continuous, quantitative method to evaluate patient inspiratory effort during pressure support ventilation. Crit Care, 2021, 25(1): 196.

1. Hess DR. Respiratory mechanics in mechanically ventilated patients. Respir Care, 2014, 59(11): 1773-1794.
2. Lucangelo U, Bernabè F, Blanch L. Lung mechanics at the bedside: make it simple. Curr Opin Crit Care, 2007, 13(1): 64-72.
3. Henderson WR, Sheel AW. Pulmonary mechanics during mechanical ventilation. Respir Physiol Neurobiol, 2012, 180(2-3): 162-172.
4. Mirza S, Clay RD, Koslow MA, et al. COPD Guidelines: A Review of the 2018 GOLD Report. Mayo Clin Proc, 2018, 93(10): 1488-1502.
5. Gattinoni L, Marini JJ, Collino F, et al. The future of mechanical ventilation: lessons from the present and the past. Crit Care, 2017, 21(1): 183.
6. Gattinoni L, Tonetti T, Cressoni M, et al. Ventilator-related causes of lung injury: the mechanical power. Intensive Care Med, 2016, 42(10): 1567-1575.
7. Chiumello D, Carlesso E, Brioni M, et al. Airway driving pressure and lung stress in ARDS patients. Crit Care, 2016, 20: 276.
8. Levine S, Nguyen T, Taylor N, et al. Rapid disuse atrophy of diaphragm fibers in mechanically ventilated humans. N Engl J Med, 2008, 358(13): 1327-1335.
9. Yoshida T, Engelberts D, Otulakowski G, et al. Continuous abdominal negative pressure recruits lungs at lower distending pressures. Am J Respir Crit Care Med, 2018, 197(4): 534-537.
10. Lichtwarck-Aschoff M, Kessler V, Sjöstrand UH, et al. Static versus dynamic respiratory mechanics for setting the ventilator. Br J Anaesth, 2000, 85(4): 577-586.
11. 陈宇清, 袁越阳, 张海, 等. 无创双水平正压通气状态下呼吸力学特性的测算分析研究. 中国呼吸与危重监护杂志, 2019, 18(6): 537-542.
12. Chen YQ, Cheng KW, Zhou X. Effectiveness of inspiratory termination synchrony with automatic cycling during noninvasive pressure support ventilation. Med Sci Monit, 2016, 22(5): 1694-1701.
13. Beloncle F, Akoumianaki E, Rittayamai N, et al. Accuracy of delivered airway pressure and work of breathing estimation during proportional assist ventilation: a bench study. Ann Intensive Care, 2016, 6(1): 30.
14. Arnal JM, Garnero A, Saoli M, et al. Parameters for simulation of adult subjects during mechanical ventilation. Respir Care, 2018, 63(2): 158-168.
15. Nava S, Bruschi C, Fracchia C, et al. Patient-ventilator interaction and inspiratory effort during pressure support ventilation in patients with different pathologies. Eur Respir J, 1997, 10(1): 177-183.
16. Gama de Abreu M, Spieth PM, Pelosi P, et al. Noisy pressure support ventilation: a pilot study on a new assisted ventilation mode in experimental lung injury. Crit Care Med, 2008, 36(3): 818-827.
17. Foti G, Cereda M, Banfi G, et al. End-inspiratory airway occlusion: a method to assess the pressure developed by inspiratory muscles in patients with acute lung injury undergoing pressure support. Am J Respir Crit Care Med, 1997, 156(4 Pt 1): 1210-1216.
18. Bertoni M, Telias I, Urner M, et al. A novel non-invasive method to detect excessively high respiratory effort and dynamic transpulmonary driving pressure during mechanical ventilation. Crit Care, 2019, 23(1): 346.
19. Teggia-Droghi M, Grassi A, Rezoagli E, et al. Comparison of two approaches to estimate driving pressure during assisted ventilation. Am J Respir Crit Care Med, 2020, 202(11): 1595-1598.
20. Volta CA, Marangoni E, Alvisi V, et al. Respiratory mechanics by least squares fitting in mechanically ventilated patients: application on flow-limited COPD patients. Intensive Care Med, 2002, 28(1): 48-52.
21. Iotti GA, Braschi A, Brunner JX, et al. Respiratory mechanics by least squares fitting in mechanically ventilated patients: applications during paralysis and during pressure support ventilation. Intensive Care Med, 1995, 21(5): 406-413.
22. Khirani S, Polese G, Aliverti A, et al. On-line monitoring of lung mechanics during spontaneous breathing: a physiological study. Respir Med, 2010, 104(3): 463-471.
23. Nassar BS, Collett ND, Schmidt GA. The flow-time waveform predicts respiratory system resistance and compliance. J Crit Care, 2012, 27(4): 418.e7-14.
24. Guillaume Carteaux G, Jordi Mancebo J, Alain Mercat A, et al. Bedside adjustment of proportional assist ventilation to target a predefined range of respiratory effort. Crit Care Med, 2013, 41(9): 2125-2132.
25. Albani F, Pisani L, Ciabatti G, et al. Flow index: a novel, non-invasive, continuous, quantitative method to evaluate patient inspiratory effort during pressure support ventilation. Crit Care, 2021, 25(1): 196.

Chinese Journal of Respiratory and Critical Care Medicine

The influence on accuracy of respiratory mechanics estimation with different inspiratory effort during noninvasive ventilation: a bench study

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content