Very Interesting Article(Long!)

Giggle. Snork!

rested gal wrote:... -SWS understands the workings of all these machines the best of anyone on the forum, imho...and better than most doctors understand them. ...

Surely, RG, you don't REALLY believe there are many, much less ANY, sleep doctors that REALLY understand - or even care about - the intracacies and sophisticated capabilities of xPAPs???? I KNOW YOU are NOT that naive!!

rested gal wrote:

ozij wrote:Farrell's Favorites (I knew I saw them recently!)
http://www.resmed.com/int/clinicians/re ... nc=dealers

I went there just now, but don't see a link associated with:
Bliss P, Eiken T, McCoy R. Performance of auto-adjust nasal CPAP devices in a simulation of varied breathing. (white paper, 2003)

There was a link there last night, but clicking it just took a person back to the homepage.

Oh well.

Maybe too many of us were trying to go to that link at the same time last night.
I waited and waited and it didn't seem to be going anywhere, so I gave up.....


Den

Google scholar to the rescue:


Try here for the Bliss whitepaper:
http://www.myresmed.com/Shared/StaticFi ... -paper.pdf

(as long as it lasts...).

O.

Interesting article Dori, thanks for posting it. I stopped getting/reading Sleep review a couple of years ago (not enough meat(articles) and too much potatoes(adverts)). I worked for Todd in '06-'07 and I do know that he reads CPAPTALK, it was one of several websites that he put on a suggested reading list given to patients during their pre study interview/mask fitting.

DoriC wrote:http://www.sleepreviewmag.com/issues/ar ... -09_02.asp

I don't know if I should be worried but I can't believe I actually read this whole article and understood a lot of it. It answered many questions about the different machines. I used to wonder about people who posted these articles here. Don't they have a life? : Your eyes may glaze over but you'll learn a lot if you stay with it.

Thanks for posting that interesting article, DoriC.

I am glad that some writing sleep professionals recognize that feeding the same machine-generated SDB signal into an APAP again and again fails to help assess an overall APAP treatment algorithm. It's kind of like assessing each member of a chess team by watching nothing more than their opening move---again and again and again!

The article you linked above was also published the prior month in that same magazine---minus the manufacturers' responses: http://www.rtmagazine.com/issues/articl ... -08_05.asp . And we side-discussed that initial article just a bit in this thread: viewtopic.php?f=1&t=44743&start=0 .

In an altogether different thread, jnk rhetorically described some of the challenges in attempting to predictively compare APAP responses for any given patient:

jnk wrote: I wonder if using one brand's estimates of events with its definitions, detections, and reactions are easily applicable to how another brand might, or might not, have defined, detected, and reacted. Don't different brands define, detect, and react to precursors differently? If so, isn't it very difficult to guess what different brands would do in different situations based on the detections, definitions, and reactions of one brand for one person on one night with no PSG data to know what really happened, let alone what would have happened?

For example, isn't it impossible to know whether another brand would have been riding at a higher baseline pressure to start with, in reaction to it's detection and reaction to precursors, and would thus have prevented all the events in the chart, or if it would have been riding at a lower pressure based on its interpretation of precursors and then had many more events to contend with, or ignore, as the case may be? And wouldn't the question of whether either brand's estimates of events would accurately report what wasn't prevented be a further complicating factor?

It's especially hard to compare all that when you submit machine-generated opening chess moves to an APAP algorithm. Unfortunately there is no interactive back-and-forth---no crucial sequences of human responses each followed by machine counter-responses--- in any methodology like that. There is thus no unveiling of each APAP algorithm's treatment strategy. And if any given testing methodology precludes observance of that treatment strategy, then that same treatment strategy logically cannot be assessed by the methodology. Oh well.

ozij wrote:Science is finally catching up with members of this forum...

Gee, that sounds awfully familiar...

Yeah, I've been thinking of SnoreDog too. RIP, you ole fart. We miss you.

Couldn't post a response on the "burst of air thread" (kept getting internal server error) so I'm bumping this instead

ozij wrote:Couldn't post a response on the "burst of air thread" (kept getting internal server error) so I'm bumping this instead

I kept getting the same Error message when I tried to post on that thread. It seems that trying to include a PDF link previously posted by anyone else causes that error. After I left out some of the quoted link, I could post my reply.

The "burst of air thread" (started by Jayjonbeach) is here:
viewtopic.php?p=554396#p554396

Thanks DoriC!

Given the variability of the human and limited research and development resources in any economy, what breathing waveforms would be appropriate for a bench study or baseline comparison?

Since members of this forum are very knowledgeable about using available technology and are eminently qualified as coaches, are there studies or experiments that are ongoing or planned that we can participate by medical facilities, research organizations or equipment manufacturers? I run across articles that cannot claim statistical significance because subject groupings are so small. We could certainly get into the brains of the designers by volunteering for sleep studies where equipment is being tested and objective measurements are being made.

Big S wrote:Thanks DoriC!

Given the variability of the human and limited research and development resources in any economy, what breathing waveforms would be appropriate for a bench study or baseline comparison?

The waveforms as such are fine. The poblem is that they are pre-recorded, and none of the autos get the respons they do when there's a realy human being breathing in and out on the other side.

DeVilbiss' machine hardly responded because DeVilbiss choice of how to define a cetral apena is wrong about 15% of the time -- and it just so happened that the real obstructive apnea thrown at all the machines was misidentified by the DeVilbiss algorithm.

Since members of this forum are very knowledgeable about using available technology and are eminently qualified as coaches, are there studies or experiments that are ongoing or planned that we can participate by medical facilities, research organizations or equipment manufacturers? I run across articles that cannot claim statistical significance because subject groupings are so small. We could certainly get into the brains of the designers by volunteering for sleep studies where equipment is being tested and objective measurements are being made.

Well "this study" http://clinicaltrials.gov/ct2/show/NCT00646477 has been "currently recruiting for the last three years....
Or at least, never published...

Big S wrote:Thanks DoriC!

Given the variability of the human and limited research and development resources in any economy, what breathing waveforms would be appropriate for a bench study or baseline comparison?

The waveforms as such are fine. The poblem is that they are pre-recorded, and none of the autos get the respons they do when there's a realy human being breathing in and out on the other side.

DeVilbiss' machine hardly responded because DeVilbiss choice of how to define a cetral apena is wrong about 15% of the time -- and it just so happened that the real obstructive apnea thrown at all the machines was misidentified by the DeVilbiss algorithm.

Since members of this forum are very knowledgeable about using available technology and are eminently qualified as coaches, are there studies or experiments that are ongoing or planned that we can participate by medical facilities, research organizations or equipment manufacturers? I run across articles that cannot claim statistical significance because subject groupings are so small. We could certainly get into the brains of the designers by volunteering for sleep studies where equipment is being tested and objective measurements are being made.

Well "this study" http://clinicaltrials.gov/ct2/show/NCT00646477 has been "currently recruiting for the last three years....
Or at least, never published...

I've never seen this question posted before but is there a way to determine if one machine's algorithm would work as well as another's based on patient's long-term data usage? For instance, Mike has only used the Respironics M Series Auto for over 2yrs with good data results. Is there a way of knowing how he'd do on the Resmed S9 Autoset algorithm without having to purchase one first to find out? Thanks.

My guess... a few people (not me! people like -SWS and ozij ) might be able to make an educated guess as to how Mike would fare on a ResMed S9 compared to what his data has shown for the past couple of years on his Respironics machine.

But it would probably still be a guess. Proof of the pudding would be after he had used an S9 for quite awhile, tweaking, etc.

A one month rental, if a DME were willing to do that, might be one way to find out.

Or -- if you knew someone with a spare S9 who would loan it to you. I would, but I don't have an S9.

He's doing quite well on his current machine as best I recall from your posts, Dori. No real need to try another. Other than that you seem to have the same curious bent so many of us here have. Always wondering about a "better mousetrap."

Or "the grass is always greener "!

Great article indeed, has me wondering about the comparison between these two machines:

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ResMed: The treatment pressure required by a patient may vary through the night—and from night to night—due to changes in sleep state, body position, and airway resistance. Pressure needs for maintaining an open upper airway in a sleep apnea patient can also be influenced by long-term variance due to weight gain or loss and use of alcohol or pharmaceuticals.

ResMed's AutoSet™ algorithm monitors the patient on a breath-by-breath basis to maintain upper airway patency for any given breath. The AutoSet algorithm adjusts treatment pressure as a function of three parameters: inspiratory flow limitation, snore, and apnea. By analyzing inspiratory flow limitation in minute detail during each respiratory cycle, the AutoSet algorithm is able to detect and distinguish obstructive hypopnea from central hypopnea: the AutoSet algorithm is able to detect and treat obstructive hypopnea (with flow limitation) and detect and record central hypopnea (without flow limitation) events. These three lines of defense allow the AutoSet algorithm to treat the patient effectively, as the patient needs it, throughout the night.

Philips Respironics: The main goal of the REMstar Auto algorithm is to normalize sleep by delivering the lowest CPAP pressure. What makes the REMstar Auto algorithm unique is its sophisticated three-layered algorithm. Unlike other auto-titrating devices in the market, the REMstar Auto can manage a respiratory event in the early stages rather than waiting for it to occur.

The primary function of the algorithm is to conduct a proactive analysis of the patient's upper airway and its potential to collapse. It makes subtle, programmed CPAP pressure adjustments in response to detected changes in flow.

The second layer consists of programmed responses to apneas, hypopneas, flow limitations, and vibratory snores.

In the third layer, the algorithm operates in a variety of exception conditions. For example, the algorithm ceases to increase pressure for patients who may experience sleep-disordered breathing events that are not responsive to pressure increases (such as central apneas). The algorithm decreases CPAP pressure when the patient is experiencing a large mask leak. The result is clinically proven, effective therapy at minimal CPAP pressure.

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Phillips did a good job selling their algorithm there, lets say one point Phillips.

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ResMed: The AutoSet algorithm is truly a predictive approach allowing proactive treatment of sleep apnea rather than simply reacting with a pressure change after an event has occurred; this is achieved by detailed analysis of the inspiratory flow versus time curve. Flow limitation analysis in the AutoSet algorithm is a complex blend of clinical sleep science and engineering; it provides very small adjustments in pressure, sometimes as little as 0.2 cm H2O at a time to ensure that the patient is not aroused from sleep (as measured by EEG) with such pressure changes. This approach allows AutoSet to preemptively treat many obstructive sleep apnea events before they even occur. When an event does occur that is not possible to prevent by the flow limitation approach, AutoSet will respond reactively as well. ResMed's AutoSet algorithm assesses the severity of the event using a blend of the inputs such as duration of the event severity and frequency of the event over time. The AutoSet algorithm then determines the optimal pressure change solution to treat the event and prevent future events and applies it comfortably with minimal disturbance to the patient's sleep.

AutoSet responds to events based on a five-breath moving average of the inspiratory flow-time curve in order to prevent the device from responding to sporadic breathing events, such as sighs or coughs. Inspiratory flow limitation, or partial airway closure, usually precedes snoring and obstructive hypopnea and apnea events; it is also most often associated with obstructive hypopneas as they occur. AutoSet adjusts in increments as small as 0.2 cm H2O to ensure that pressure increases only as much as is necessary.

For flow limitation, AutoSet calculates the shape of the inspiratory flow-time curve and the value for every breath (using a metric known as the flattening index); however, it responds based on the average value of the most recent five breaths, as described above. Detection of flow limitation enables the device to increase the pressure before obstruction occurs, making treatment preemptive, and thus reducing the number of respiratory events and arousals. The apnea response is determined by the severity of the event and current therapy pressure. Apnea pressure changes are delivered after the event such that the pressure change will not arouse the patient. Snore response is measured using the severity of the vibrations of the snore. A more severe snore will give a larger pressure response, but this proportional response is delivered over the next series of breaths such that the pressure change does not disturb the sleeping patient.

If no further flow limitation, snore, or apneas are detected, therapy is reduced over time toward the minimum pressure prescribed by the physician with a 20-minute time constant. This approach allows the pressure from ResMed's AutoSet algorithm to return to lower pressures for increased patient comfort in the absence of any respiratory events.

Philips Respironics: With its proactive and continuous analysis throughout the therapy session, the REMstar Auto algorithm has the unique ability to deliver just enough CPAP pressure necessary to ward off a potential event. Since the pressure delivered at any given time is slightly higher than the pressure level necessary to open the airway, if an event does occur, the device does not need to rapidly respond by increasing pressure quickly. When the REMstar Auto detects a clustering of events, it determines the patient's airway to be unstable and slowly increases pressure to achieve a higher level of CPAP for a new 5-minute period.

The REMstar Auto detects and responds to apneas, hypopneas, flow limitations, and vibratory snores. To detect an apnea or hypopnea, the algorithm calculates a baseline patient flow based on a moving average of patient flow. The baseline flow and any changes in flow are based on the algorithm's analysis of four parameters of the flow signal: flatness, roundness, peak, and shape. This precise recognition of unique patient flow patterns is the reason why the REMstar Auto reacts better than other devices.

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Ummm lets say one point Resmed

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ResMed: ResMed's AutoSet algorithm was the first published auto-titration positive airway pressure algorithm in the peer-reviewed literature. The AutoSet was first developed in the early 1990s by researchers in Sydney, Australia, and Essen, Germany. Michael Berthon-Jones, MD, PhD, and Professor Helmut Teschler, MD, PhD, published a seminal article in the peer-reviewed literature (Thorax, 1998) comparing AutoSet versus continuous positive airway pressure. This study showed clinical equivalence of outcomes from AutoSet and CPAP in terms of respiratory disturbance index (RDI) and other important SDB parameters. Another important early analysis in the peer-reviewed press from the mid 1990s was published in the blue journal by Lloberes et al (Am J Respir Crit Care Med, 1996) showing equivalence of sleep architecture in terms of sleep efficiency, stage 1-2 sleep, slow-wave sleep, and REM sleep between AutoSet and CPAP using gold-standard PSG analyses.

Just a few of the many dozen other articles published on AutoSet in the last 15 years are summarized below:

Improvement in compliance as well as quality-of-life parameters such as SF-36 Vitality Scores and mental health metrics for patients on AutoSet versus CPAP, when CPAP pressures are equal to or greater than 10 cm H2O (Massie et al. Am J Respir Crit Care Med, 2003)
Superiority of AutoSet versus competitive APAP algorithms in studies completed by independent, non-industry-sponsored analyses (Farre et al. Am J Respir Crit Care Med, 2002)
Equivalent clinical outcomes (AHI, oxygen saturation) as well as equivalent or superior quality-of-life (SF-36, FOSQ, EuroQOL) when AutoSet was compared to gold-standard CPAP (Am J Respir Crit Care Med, 2004)
Economic and cost-effective use of AutoSet in the home setting for treating obstructive sleep apnea (Bachour et al. Sleep Medicine, 2007)
Literally millions of patients have been prescribed the AutoSet algorithm by physicians globally during the last decade, on products across product platforms from ResMed since the mid 1990s, including the AutoSet Clinical, the AutoSet Portable, the AutoSet P2+, the AutoSet T, and the S8 AutoSet. Today, patients can receive therapy from the latest AutoSet algorithm in the S8 AutoSet II device. The S8 AutoSet II device combines not only the advances of the world-pioneering auto-adjusting algorithm described in this article, but also one of the smallest, quietest, and most reliable sleep apnea devices in the world.

Philips Respironics: The theory of the algorithm was developed based on clinical understanding and practices used in titrating CPAP pressures during a PSG titration process. Additionally, there has been extensive clinical and bench test validation of the algorithm's effectiveness. These studies have been conducted by Philips Respironics and independent medical professionals. Several studies have been published in medical and other trade journals.

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Resmed, scores a knockout.


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I'd be interested in hearing from people who have used both machines for sure and their thoughts, obviously everyone is different and could respond differently but it makes good discussion at any rate.