Predictive value of tidal volume and peak inspiratory pressure in normal frequency jet ventilation
Normal frequency jet ventilation (NFJV) is commonly used during rigid bronchoscopy; however, airway opening does not reliably measure or predict tidal volume (V<sub>T</sub>) or peak inspiratory pressure (PIP). This study aimed to investigate the comprehensive effects on V<sub>T</sub> and PIP concerning key variables, including driving pressure (DP<sub>pipeline</sub>), frequency (F<sub>jet</sub>), needle inner diameter (ID<sub>needle</sub>), and lung dynamic compliance (C<sub>dyn</sub>). Three jet needles (N<sub>1</sub>, N<sub>2</sub>, and N<sub>3</sub>) with different internal diameters (1.2-1.9 mm) were used to deliver jet ventilation via a rigid bronchoscope at DPs of 0.6-1.6 bar and frequencies of 10-60 min⁻¹. Airway pressure (Paw) was measured near the tracheal prominence of the simulated lung. Expiratory gas flow was diverted into a dedicated collection chamber fitted with a solenoid valve over a one-minute period, and the collected volume was measured as minute volume (MV). ①. Statistical analysis of the two lung models revealed consistent findings: both V<sub>T</sub> and PIP values in N<sub>2</sub> and N<sub>3</sub> demonstrated statistically significant differences compared to N<sub>1</sub> (P < 0.05). Additionally, significant differences in the V<sub>T</sub> and PIP values were observed between N<sub>2</sub> and N<sub>3</sub> (P < 0.05). ②. Multiple linear regression analyses indicated that DP<sub>pipeline</sub>, F<sub>jet</sub>, and ID<sub>needle</sub> had statistically significant effects on V<sub>T</sub> and PIP (P < 0.05). Conversely, C<sub>dyn</sub> significantly affected V<sub>T</sub> (P < 0.05) but did not have a significant impact on PIP (P > 0.05). The primary variables exerting a significant influence on V<sub>T</sub> and PIP were DP<sub>pipeline</sub>, F<sub>jet</sub>, and ID<sub>needle</sub>. Furthermore, C<sub>dyn</sub> significantly affected V<sub>T</sub> but not PIP. V<sub>T</sub> and PIP can be accurately predicted using regression equations.
Authors
- Jianliang Peng (ORCID: https://orcid.org/0009-0006-8763-316X)
- Jing Lv (ORCID: https://orcid.org/0000-0002-6432-6785)
Institutions
- First Affiliated Hospital of Xiamen University (CN)
- The Second Affiliated Hospital of Xiamen Medical College
Publication Details
- Journal
- Scientific Reports
- Published
- 2025-10-22
- DOI
- https://doi.org/10.1038/s41598-025-20681-8
- Primary Topic
- Respiratory Support and Mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 0.00