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In this issue of RESPIRATORY CARE, 2 studies used bench testing to compare responses of positive airway pressure (PAP) devices to simulated respiratory events. The first by Fasquel et al1 tested the response of 3 autoCPAP devices to events with and without unintentional air leak. The second by Delorme et al2 tested the response of adaptive pressure settings of 4 noninvasive ventilators to simulated central and obstructive respiratory events. These papers highlight that a greater understanding of how different PAP algorithms work can facilitate their optimal use and help troubleshoot clinical responses. Whereas the authors state that the algorithms are largely an unknown black box, some manufacturers have shared and verified key elements that are reported in Principles and Practice of Sleep Medicine, 7th edition,3 and 2 other publications.4-5
Fasquel et al1 concluded that ResMed’s AirSense S10 autoCPAP “was not able to respond correctly to obstructive apnea and hypopnea” in the setting of unintentional air leak. In response to events and unintentional air leak, AirSense S10’s algorithm rapidly maintained fairly constant pressure of 7–8 cm H2O, whereas Philips’ DreamStation slowly increased the pressure to near 10 cm H2O and Löwenstein Medical’s prisma20A slowly increased to almost 15 cm H2O. We differ with their opinion that the correct response to these events in the setting of unintentional air leak is to keep raising the pressure.
The main difference between invasive ventilation and noninvasive ventilation (NIV) or PAP therapy is the need to adjust for leak. Algorithms need to adjust for both intentional leak from the outflow through mask exhalation ports and unintentional air leak from mouth opening or around the mask. Appropriate leak control and algorithm response are critical for both function and tolerance. …
Correspondence: Karin G Johnson MD, Department of Neurology, Baystate Medical Center, University of Massachusetts Medical School-Baystate, 759 Chestnut Street, Springfield, MA 01199. E-mail: Karin.johnson{at}baystatehealth.org
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