adaptive support ventilation
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2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Yuriko Hajika ◽  
Yuji Kawaguchi ◽  
Kenji Hamazaki ◽  
Yasuro Kumeda

Abstract Background Adaptive support ventilation (ASV) is a proposed treatment option for central sleep apnea (CSA). Although the effectiveness of ASV remains unclear, some studies have reported promising results regarding the use of ASV in patients with heart failure with preserved ejection fraction (HfpEF). To illustrate the importance of suspecting and diagnosing sleep-disordered breathing (SDB) in older adults unable to recognize symptoms, we discuss a case in which ASV was effective in a patient with CSA and HfpEF, based on changes in the Holter electrocardiogram (ECG). Case presentation. An 82-year-old man presented to our hospital with vomiting on April 19, 2021. Approximately 10 years before admission, he was diagnosed with type 1 diabetes mellitus and recently required full support from his wife for daily activities due to cognitive dysfunction. Two days before admission, his wife was unable to administer insulin due to excessively high glucose levels, which were displayed as “high” on the patient’s glucose meter; therefore, we diagnosed the patient with diabetic ketoacidosis. After recovery, we initiated intensive insulin therapy for glycemic control. However, the patient exhibited excessive daytime sleepiness, and numerous premature ventricular contractions were observed on his ECG monitor despite the absence of hypoglycemia. As we suspected sleep-disordered breathing (SDB), we performed portable polysomnography (PSG), which revealed CSA. PSG revealed a central type of apnea and hypopnea due to an apnea–hypopnea index of 37.6, which was > 5. Moreover, the patient had daytime sleepiness; thus, we diagnosed him with CSA. We performed ASV and observed its effect using portable PSG and Holter ECG. His episodes of apnea and hypopnea were resolved, and an apparent improvement was confirmed through Holter ECG. Conclusion Medical staff should carefully monitor adult adults for signs of or risk factors for SDB to prevent serious complications. Future studies on ASV should focus on older patients with arrhythmia, as the prevalence of CSA may be underreported in this population and determine the effectiveness of ASV in patients with HfpEF, especially in older adults.


Author(s):  
Inderpaul S. Sehgal ◽  
Raghava R. Gandra ◽  
Sahajal Dhooria ◽  
Ashutosh N. Aggarwal ◽  
Kuruswamy T. Prasad ◽  
...  

2021 ◽  
Vol 2 (3) ◽  
pp. 80-85
Author(s):  
Jean-Michel Arnal ◽  
Ehab Daoud

Adaptive Support Ventilation (ASV) is a fully closed loop ventilation where the operator input the desired PEEP, FiO2 and the target minute ventilation (MV) expressed as a percentage according to ideal body weight. The ventilator selects the target respiratory pattern (tidal volume, respiratory rate, and inspiratory time) based on the observed respiratory mechanics. However, there are no published guidelines on settings and adjusting the target MV in different disease states during ASV ventilation. INTELLiVENT-ASV, is the new generation modified algorithm of ASV, has made this issue much easier and simpler as the operator inputs a desired range of the end tidal exhaled carbon dioxide, and oxygen saturation and the algorithm will adjust the minute ventilation percentage as well as PEEP and FiO2 automatically to stay within that range. In this article we describe some evidence-based guidelines on how to set and adjust the target MV in various clinical conditions. Keywords: ASV, INTELLiVENT-ASV, Closed loop ventilation, End tidal CO2, ARDS, COPD, Respiratory failure


2021 ◽  
Vol 2 (2) ◽  
pp. 48-52
Author(s):  
Ronald Sanderson ◽  
Denise Whitley ◽  
Christopher Batacan

Background Automation of mechanical ventilation allows for reduction of variation in patient management and has the potential to provide increased patient safety by strict adherence to computer driven ventilator protocols. Methods: A retrospective, observational study compared a group of 196 of general ICU patients managed exclusively on automated mechanical ventilation, adaptive support ventilation (ASV), to another group of 684 managed by usual, non-automated mechanical ventilation (No ASV). The data was collected in a unique access database designed to collect data for assessment of mechanical ventilation outcomes in a small medical center ICU. Results: The length of ventilator stay was non-significant between both groups, (81.7 ± 35.2 hours) in the ASV group; vs. (94.1 ± 35.1 hours) in the No ASV. Percent mortality was significantly less in the ASV group, 8.6% compared to 27.3% in the No ASV. Conclusion: Automated ventilation appears to be a safe ventilator strategy; however, cause effect relationships cannot be determined without further, more sophisticated studies. Keywords: Closed loop ventilation, ASV, Ventilator length of stay, Percent minute ventilation


2021 ◽  
Vol 2 (2) ◽  
pp. 53-58
Author(s):  
Marissa Su ◽  
ehab daoud

Background: Adaptive support ventilation (ASV) is an intelligent mode of mechanical ventilation protocol which uses a closed-loop control between breaths. The algorithm states that for a given level of alveolar ventilation, there is a particular respiratory rate and tidal volume which achieve a lower work of breathing. The mode allows the clinician to set a desired minute ventilation percentage (MV%) while the ventilator automatically selects the target ventilatory pattern base on these inputs and feedback from the ventilator monitoring system. The goal is to minimize the work of breathing and reduce complications by allowing the ventilator to adjust the breath delivery taking into account the patient’s respiratory mechanics (Resistance, and Compliance). In this study we examine the effect of patients’ respiratory effort on target tidal volume (VT) and Minute Ventilation (V̇e) during ASV using breathing simulator. Methods: A bench study was performed by using the ASL 5000 breathing simulator to compare the target ventilator to actual VT and V̇e value in simulated patients with various level of respiratory effort during ASV on the Hamilton G5 ventilator. The clinical scenario involves simulated adult male with IBW 70kg and normal lung mechanics: respiratory compliance of 70 mL/cm H2O, and airway resistance of 9 cm H2O/L/s. Simulated patients were subjected to five different level of muscle pressure (Pmus): 0 (Passive), -5, -10, -15, -25 (Active) cm H2O at a set respiratory rate of 10 (below targeted VT) set at three different levels of minute ventilation goals: 100%, 200%, and 300%, with a PEEP of 5 cm H2O. Fifty breaths were analyzed in every experiment. Means and standard deviations (SD) of variables were calculated. One way analysis of variants was done to compare the values. Pearson correlation coefficient test was used to calculate the correlation between the respiratory effort and the VT, V̇e, and peak inspiratory pressure (PIP). Results: The targeted VT and V̇e were not significant in the passive patient when no effort was present, however were significantly higher in the active states at all levels of Pmus on the 100%, 200% and the 300 MV%. The VT and V̇e increase correlated with the muscle effort in the 100 and 200 MV% but did not in the 300%. Conclusions: Higher inspiratory efforts resulted in significantly higher VT and V̇e than targeted ones. Estimating patients’ effort is important during setting ASV. Keywords: Mechanical ventilation, ASV, InteliVent, Pmus, tidal volume, percent minute ventilation


2021 ◽  
Vol 2 (1) ◽  
pp. 34-44
Author(s):  
Denise Wheatley ◽  
Krystal Young

Ventilators functions and features have evolved with the advancement of technology along with the addition of microprocessors. It is important to understand and examine the benefits and risks associated with these advanced automated modes. Adaptive Support Ventilation (ASV) is a mode that is unique to the Hamilton Medical ventilators, thereby limiting the number of clinicians who have experience with using this mode. ASV can make changes to respiratory rate and tidal volume and adjusting the driving pressure in the absence of a professional. ASV changes ventilator strategies when it detects changes to a patient’s lung dynamics. The scope of ASV mode is not universally understood. Respiratory therapists may feel their position would be threatened with the use of smart automated modes. This paper will aim to review the literature on the ASV mode of ventilation. The literature review will address the following research questions to broaden the understanding of the risks and benefits of the ASV mode. 1) Is the ASV mode effective for weaning patients? 2) Is ASV a safe mode of ventilation for patients with COPD and ARDS? 3) Is ASV a safe mode of ventilation with changes in lung dynamics? 4) Does ASV impact the bedside respiratory therapist? Conclusions: ASV appears to be at least effective or even more superior to other modes especially during weaning off mechanical ventilation, and in other forms of respiratory failure. More studies in different clinical conditions and head-to-head with other modes. Keywords: ASV, COPD, ARDS, Weaning


2021 ◽  
Vol 25 (1) ◽  
Author(s):  
Dmytro Dmytriiev ◽  
Olga Kostiv ◽  
Mykola Melnychenko ◽  
Sviatoslav Kostiv ◽  
Kostiantyn Dmytriiev

An interesting clinical case of viral pneumonia in a patient with diabetes mellitus is considered in the article. This case deserves attention of anesthesiologists, especially today, during the COVID-19 epidemic. An important role in timely diagnosis belongs to the CT scan, as the X-ray does not always diagnose viral pneumonia. In our case, we adhered to the principles of restrictive infusion therapy, early intubation, protective ventilation and early weaning of the patient from the respirator. The article describes the successful experience of using the ASV intelligent ventilation mode – from intubation to extubation. We recommend you to use ASV in patients with viral pneumonia to achieve protective ventilation, rapid weaning, and low risk of complications.


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