Evaluation of Adaptive Support Ventilation in Paralysed Patients and in a Physical Lung Model

2004 ◽  
Vol 27 (8) ◽  
pp. 709-716 ◽  
Author(s):  
M. Belliato ◽  
A. Palo ◽  
D. Pasero ◽  
G.A. Iotti ◽  
F. Mojoli ◽  
...  
2009 ◽  
Vol 111 (4) ◽  
pp. 863-870 ◽  
Author(s):  
Demet Sulemanji ◽  
Andrew Marchese ◽  
Paul Garbarini ◽  
Marc Wysocki ◽  
Robert M. Kacmarek

Background Adaptive support ventilation (ASV) allows the clinician to set a maximum plateau pressure (PP) and automatically adjusts tidal volume to keep PP below the set maximum. Methods ASV was compared to a fixed tidal volume of 6 ml/kg. ASV determined the respiratory rate and tidal volume based on its algorithms. Maximum airway pressure limit was 28 cm H2O in ASV. Six sets of lung mechanics were simulated for two ideal body weights: 60 kg, Group I; 80 kg, Group II. Positive end expiratory pressure was 8, 12, and 16 cm H2O, and target minute volume 120%, 150%, and 200% of predicted minute volume. Results ASV "sacrificed" tidal volume and minute ventilation to maintain PP in 9 (17%) of 54 scenarios in Group I and 20 (37%) of 54 scenarios in Group II. In Group I, the number of scenarios with PP of 28 cm H2O or more was 14 for ASV (26%) and 19 for 6 ml/kg (35%). In these scenarios, mean PP were ASV 28.8 +/- 0.86 cm H2O (min 28, max 30.3) and 6 ml/kg 33.01 +/- 3.48 cm H2O (min 28, max 37.8) (P = 0.000). In group II, the number of scenarios PP of 28 cm H2O or more was 10 for ASV (19%) and 21 for 6 ml/kg (39%). In these cases, mean PP values were ASV 28.78 +/- 0.54 cm H2O (min 28, max 29.6) and 6 ml/kg 32.66 +/- 3.37 cm H2O (min 28.2, max 38.2) (P = 0.000). Conclusion In a lung model with varying mechanics, ASV is better able to prevent the potential damaging effects of excessive PP (greater than 28 cm H2O) than a fixed tidal volume of 6 ml/kg by automatically adjusting airway pressure, resulting in a decreased tidal volume.


Author(s):  
Wou Young Chung ◽  
Keu Sung Lee ◽  
Joo Hun Park ◽  
Seung Soo Sheen ◽  
Sung Chul Hwang ◽  
...  

2017 ◽  
Vol 1 (1) ◽  
pp. 8-12
Author(s):  
L.K. Rajbanshi ◽  
M. Dali ◽  
S.B. Karki ◽  
K. Khanal ◽  
B. Aryal ◽  
...  

Introduction Adaptive support ventilation (ASV) is a close loop dual control mechanical ventilation mode. This mode can automatically change its parameters to weaning mode once the patient is actively breathing converting volume targeted pressure control mode to volume targeted pressure support mode. We aimed to observe the outcome of the patients ventilated with ASV as a sole mode in terms of duration of mechanical ventilation, duration of weaning from the ventilatory support and length of Intensive care unit (ICU) stay.Methodology We conducted a prospective observational study for the duration of six months (Sept 2015 to Feb 2016) to assess the clinical outcome of the patients ventilated by ASV as a sole mode of ventilation. The study conducted observation of 78 patients without chronic respiratory, renal, hepatic and neurological disease who were admitted in our intensive care unit for invasive ventilatory support.Results Out of the 187 patients who required invasive and noninvasive ventilation, only 78 patients fulfilled the criteria to be included in the study. It was observed that the mean duration of mechanical ventilation was 5.4 days while weaning as well as tracheal extubation was successful within 13 hours of initiation of weaning. The mean duration of ICU stay was found to be 6.3 days.Conclusion We concluded that the patient ventilated by ASV mode were effectively weaned without the need of changing the ventilator mode. However, the safety of ASV mode needs to be established by large randomized control trail in a wide spectrum of patients.Birat Journal of Health Sciences 2016 1(1): 8-12


2001 ◽  
Vol 7 (3) ◽  
pp. 425-440 ◽  
Author(s):  
R CAMPBELL ◽  
R BRANSON ◽  
J JOHANNIGMAN

2010 ◽  
Vol 33 (5) ◽  
pp. 302-309 ◽  
Author(s):  
Denise P. Veelo ◽  
Dave A. Dongelmans ◽  
Jan M. Binnekade ◽  
Frederique Paulus ◽  
Marcus J. Schultz

2013 ◽  
Vol 17 (1) ◽  
pp. 16-22 ◽  
Author(s):  
Jaime Fernández ◽  
Dayra Miguelena ◽  
Hernando Mulett ◽  
Javier Godoy ◽  
Federico Martinón-Torres

Sign in / Sign up

Export Citation Format

Share Document