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[Pressure] Please help me self-titrate (OSCAR data provided)
Please help me self-titrate (OSCAR data provided)
Hi all,

I am currently on a three-month waiting list for a sleep study to confirm that I have sleep apnea, which my sleep specialist says is overwhelmingly likely due to the anatomy of my face and my symptoms. But as you all know, putting up with another three minutes of this miserable sleep-deprived existence would be hell, let alone three months. While I fully intend to do the sleep study, I wanted to get a head start in any way I could.

So I bought a CPAP machine and started using it, after extensive research as to what I should get. It's a ResMed AirSense 10 Autoset (the 11 isn't available here in Australia yet) and I got a full-face mask to go with it as I am prone to mouth breathing due to sinus issues. I've had some success with it so far, on some days I feel a little better than I used to, but I'm very tired and needing to nap almost every day.

So I'd be extremely grateful if some of you wise people could look over my data and see if I can optimise the settings I've put into my machine so far. I followed the wiki's guide and put my minimum pressure at one below my median - the median is usually around 12, so I put in 11. I also started wearing a soft cervical collar, which significantly reduced my AHI.

Screenshots of OSCAR data are below. My worst night so far was an AHI of around 9, with min pressure 4, max 20, and no collar. My best is 1.3, with min 11, max 20, and a collar.

Something that concerns me is that my breathing seems to be stopping a lot more often than the machine is detecting. I believe apneas are cessations in airflow that last at least ten seconds, and while I have a few of those, close examination of my data shows that I am also having frequent mini-apneas of around six to eight seconds, much more frequently than the 'proper' apneas. If these were included in my AHI, I think it would be at least in the 20-30 range even with the machine. I have included some zoomed-in detail shots of the data to demonstrate this.

Thank you all so much for your help!

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