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2021 ◽  
Author(s):  
Ling Liu ◽  
Daijiro Takahashi ◽  
Haibo Qui ◽  
Arthur S. Slutsky ◽  
Christer Sinderby ◽  
...  

Background During conventional Neurally Adjusted Ventilatory Assist (NAVA), the electrical activity of the diaphragm (EAdi) is used for triggering and cycling-off inspiratory assist, with a fixed PEEP (so called “Triggered Neurally Adjusted Ventilatory Assist” or “tNAVA”). However, significant post-inspiratory activity of the diaphragm can occur, believed to play a role in maintaining end-expiratory lung volume. Adjusting pressure continuously, in proportion to both inspiratory and expiratory EAdi (Continuous NAVA, or cNAVA), would not only offer inspiratory assist for tidal breathing, but also may aid in delivering a “neurally adjusted PEEP”, and more specific breath-by-breath unloading. Methods Nine adult New Zealand white rabbits were ventilated during independent conditions of: resistive loading (RES1 or RES2), CO2 load (CO2) and acute lung injury (ALI), either via tracheotomy (INV) or non-invasively (NIV). There were a total of six conditions, applied in a non-randomized fashion: INV-RES1, INV-CO2, NIV-CO2, NIV-RES2, NIV-ALI, INV-ALI. For each condition, tNAVA was applied first (3 min), followed by 3 min of cNAVA. This comparison was repeated 3 times (repeated cross-over design). The NAVA level was always the same for both modes, but was newly titrated for each condition. PEEP was manually set to zero during tNAVA. During cNAVA, the assist during expiration was proportional to the EAdi. During all runs and conditions, ventilator-delivered pressure (Pvent), esophageal pressure (Pes), and diaphragm electrical activity (EAdi) were measured continuously. The tracings were analyzed breath-by-breath to obtain peak inspiratory and mean expiratory values. Results For the same peak Pvent, the distribution of inspiratory and expiratory pressure differed between tNAVA and cNAVA. For each condition, the mean expiratory Pvent was always higher (for all conditions 4.0 ± 1.1 vs. 1.1 ± 0.5 cmH2O, P < 0.01) in cNAVA than in tNAVA. Relative to tNAVA, mean inspiratory EAdi was reduced on average (for all conditions) by 19 % (range 14 %–25 %), p < 0.05. Mean expiratory EAdi was also lower during cNAVA (during INV-RES1, INV-CO2, INV-ALI, NIV-CO2 and NIV-ALI respectively, P < 0.05). The inspiratory Pes was reduced during cNAVA all 6 conditions (p < 0.05). Unlike tNAVA, during cNAVA the expiratory pressure was comparable with that predicted mathematically (mean difference of 0.2 ± 0.8 cmH2O). Conclusion Continuous NAVA was able to apply neurally adjusted PEEP, which led to a reduction in inspiratory effort compared to triggered NAVA.


2021 ◽  
Author(s):  
Ling Liu ◽  
Daijiro Takahashi ◽  
Haibo Qui ◽  
Arthur S. Slutsky ◽  
Christer Sinderby ◽  
...  

Background During conventional Neurally Adjusted Ventilatory Assist (NAVA), the electrical activity of the diaphragm (EAdi) is used for triggering and cycling-off inspiratory assist, with a fixed PEEP (so called “Triggered Neurally Adjusted Ventilatory Assist” or “tNAVA”). However, significant post-inspiratory activity of the diaphragm can occur, believed to play a role in maintaining end-expiratory lung volume. Adjusting pressure continuously, in proportion to both inspiratory and expiratory EAdi (Continuous NAVA, or cNAVA), would not only offer inspiratory assist for tidal breathing, but also may aid in delivering a “neurally adjusted PEEP”, and more specific breath-by-breath unloading. Methods Nine adult New Zealand white rabbits were ventilated during independent conditions of: resistive loading (RES1 or RES2), CO2 load (CO2) and acute lung injury (ALI), either via tracheotomy (INV) or non-invasively (NIV). There were a total of six conditions, applied in a non-randomized fashion: INV-RES1, INV-CO2, NIV-CO2, NIV-RES2, NIV-ALI, INV-ALI. For each condition, tNAVA was applied first (3 min), followed by 3 min of cNAVA. This comparison was repeated 3 times (repeated cross-over design). The NAVA level was always the same for both modes, but was newly titrated for each condition. PEEP was manually set to zero during tNAVA. During cNAVA, the assist during expiration was proportional to the EAdi. During all runs and conditions, ventilator-delivered pressure (Pvent), esophageal pressure (Pes), and diaphragm electrical activity (EAdi) were measured continuously. The tracings were analyzed breath-by-breath to obtain peak inspiratory and mean expiratory values. Results For the same peak Pvent, the distribution of inspiratory and expiratory pressure differed between tNAVA and cNAVA. For each condition, the mean expiratory Pvent was always higher (for all conditions 4.0 ± 1.1 vs. 1.1 ± 0.5 cmH2O, P < 0.01) in cNAVA than in tNAVA. Relative to tNAVA, mean inspiratory EAdi was reduced on average (for all conditions) by 19 % (range 14 %–25 %), p < 0.05. Mean expiratory EAdi was also lower during cNAVA (during INV-RES1, INV-CO2, INV-ALI, NIV-CO2 and NIV-ALI respectively, P < 0.05). The inspiratory Pes was reduced during cNAVA all 6 conditions (p < 0.05). Unlike tNAVA, during cNAVA the expiratory pressure was comparable with that predicted mathematically (mean difference of 0.2 ± 0.8 cmH2O). Conclusion Continuous NAVA was able to apply neurally adjusted PEEP, which led to a reduction in inspiratory effort compared to triggered NAVA.


2021 ◽  
Vol 286 ◽  
pp. 103617
Author(s):  
James Manifield ◽  
Nikolaos Chynkiamis ◽  
Charikleia Alexiou ◽  
Dimitrios Megaritis ◽  
Emily Hume ◽  
...  

2021 ◽  
Vol 13 (4) ◽  
pp. 667 ◽  
Author(s):  
Dmitry Edemsky ◽  
Alexei Popov ◽  
Igor Prokopovich ◽  
Vladimir Garbatsevich

Deployment of a ground penetrating radar (GPR) on a flying machine allows one to substantially extend the application area of this geophysical method and to simplify carrying out large surveys of dangerous and hard-to-reach terrain, where usual ground-based methods are hardly applied. There is a necessity to promote investigations in this direction by modifying hardware characteristics and developing specific proceeding algorithms. For this purpose, we upgraded commercial ground-based subsurface sounding hardware and performed corresponding computer simulation and real experiments. Finally, the first experimental flights were done with the constructed GPR prototype mounted on a helicopter. Using our experience in the development of ground-based GPR and the results of numerical simulations, an appropriate configuration of antennas and their placing on the flying machine were chosen. Computer modeling allowed us to select an optimal resistive loading of transmitter and receiver dipoles; calculate radiation patterns on fixed frequencies; analyze the efficiency of different conductor diameters in antenna circuit; calculate cross-coupling of transmitting and receiving antennas with the helicopter. Preliminary laboratory experiments to check the efficiency of the designed system were performed on an urban building site, using a tower crane with the horizontal jib to operate the measuring system in the air above the ground area to be sounded. Both signals from the surface and subsurface objects were recorded. To interpret the results, numerical modeling was carried out. A two-dimensional model of our experiment was simulated, it matches well the experimental data. Laboratory experiments provided an opportunity to estimate the level of spurious reflections from the external objects, which helps to recognize weak signals from subsurface objects in GPR surveys under live conditions.


2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Bruno da Silva Guimarães ◽  
Leonardo Cordeiro de Souza ◽  
Hebe Faria Cordeiro ◽  
Thiago Loureiro Regis ◽  
Cristiane Almeida Leite ◽  
...  

2020 ◽  
Vol 11 ◽  
Author(s):  
Marine Van Hollebeke ◽  
Rik Gosselink ◽  
Daniel Langer

IntroductionInspiratory muscle training (IMT) protocols are typically performed using pressure threshold loading with inspirations initiated from residual volume (RV). We aimed to compare effects of three different IMT protocols on maximal inspiratory pressures (PImax) and maximal inspiratory flow (V̇Imax) at three different lung volumes. We hypothesized that threshold loading performed from functional residual capacity (FRC) or tapered flow resistive loading (initiated from RV) would improve inspiratory muscle function over a larger range of lung volumes in comparison with the standard protocol.Methods48 healthy volunteers (42% male, age: 48 ± 9 years, PImax: 110 ± 28%pred, [mean ± SD]) were randomly assigned to perform three daily IMT sessions of pressure threshold loading (either initiated from RV or from FRC) or tapered flow resistive loading (initiated from RV) for 4 weeks. Sessions consisted of 30 breaths against the highest tolerable load. Before and after the training period, PImax was measured at RV, FRC, and midway between FRC and total lung capacity (1/2 IC). V̇Imax was measured at the same lung volumes against a range of external threshold loads.ResultsWhile PImax increased significantly at RV and at FRC in the group performing the standard training protocol (pressure threshold loading from RV), it increased significantly at all lung volumes in the two other training groups (all p &lt; 0.05). No significant changes in V̇Imax were observed in the group performing the standard protocol. Increases of V̇Imax were significantly larger at all lung volumes after tapered flow resistive loading, and at higher lung volumes (i.e., FRC and 1/2 IC) after pressure threshold loading from FRC in comparison with the standard protocol (all p &lt; 0.05).ConclusionOnly training with tapered flow resistive loading and pressure threshold loading from functional residual capacity resulted in consistent improvements in respiratory muscle function at higher lung volumes, whereas improvements after the standard protocol (pressure threshold loading from residual volume) were restricted to gains in PImax at lower lung volumes. Further research is warranted to investigate whether these results can be confirmed in larger samples of both healthy subjects and patients.


2020 ◽  
Vol 282 ◽  
pp. 103531
Author(s):  
Ching-Feng Cheng ◽  
Wei-Chieh Hsu ◽  
Yu-Hsuan Kuo ◽  
Tzu-Wei Chen ◽  
Yu-Chi Kuo

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