3
The Löwenstein Difference The Löwenstein devices consistently demonstrate clinical efficacy (AHI<5/hour), with further key clinical features as follows: » Prisma RECOVER - Innovative feature that estimates deep sleep. » High accuracy of AHI detection - 96% accuracy level with PG as reference. » Proactive algorithm regulation - epoch-based response with structured treatment pattern. » Dynamic & Standard Algorithm - 2 settings to suit different patients & stage of treatment. » Stability of pressure adjustment - therapeutically effective with no unnecessary fluctuation.
» Efficiency of pressure - consistently low Pmax & Pmean. » Pressure relief SoftPAP - No compromise on clinical outcome. Features are explored in detail below & in subsequent appendices.
Prisma RECOVER The Löwenstein white paper edition “Sleep Quality in CPAP/APAP Therapy”* challenges the traditional perception of AHI as the only metric in APAP/CPAP Therapy. The paper outlines the importance of restorative or deep sleep (slow-wave-sleep) which shows a greater correlation to an improvement in daytime sleepiness compared to AHI. The innovative Prisma RECOVER algorithm (inbuilt within Prisma devices) analyses respiratory minute volume to provide an estimation of deep sleep. Deep sleep could be considered an important new metric of sleep quality in PAP therapy.
to treating sleep disordered breathing efficiently. The prisma devices have a forced oscillation amplitude of approx. 0.4 hpa (or cmH20) which is superimposed by the device blower.* The minor amplitude would suggest little chance of disruption to the patient’s sleep, with a precise event recognition achieved. “Study Hunter: Benchtest of AHI agreement in APAP (20A)”** was carried out with 4 devices: AirSense 10 (Resmed), Dreamstation Auto (Philips), S. Box (Sefam), Prisma20A (Löwenstein). It was concluded that Prisma20A together with Dreamstation Auto showed the highest accuracy level at 96% with PG as reference.
*Refer to Appendix 2 pages 1-8 **Refer to Appendix 3 Proactive Algorithm
*Refer to Appendix 1
Accuracy of AHI via FOT Modern algorithms frequently use forced oscillation technique (FOT) to reliably distinguish between obstructive & central sleep events, which is a prerequisite
Löwenstein devices measure each breath of the patient & airway obstruction occurring, this can then be observed in detailed graphs: respiratory flow graph & respiratory
next generation sourcing
Made with FlippingBook Online newsletter