mrueschman

Omer,

The RDI* variables in SHHS are not necessarily "AHI + arousals". They are more like AHI variables, but all events (apneas and hypopneas) are required to be associated with a desaturation (of 4%, for instance, in RDI4P).

I assume there are people trying to "diagnose" sleep apnea using only an oximetry channel. Naturally, the ODI closely aligns with AHI in many cases.

Do you have any specific data questions? Or inconsistent data findings? I wasn't sure exactly what I was looking at in your image.

Note that if you derived "new" oxygen desaturations from the raw signal then you would want to be sure your methodology matched with whatever was used by the original sleep scoring software. Otherwise your new metrics would not be comparable.

Mike

Thanks for checking out the resource.

If you search "menopause" in the main search box, certain variables will come up: https://sleepdata.org/search?search=menopause

At a glance, HeartBEAT and CFS have menopause-related variables. Of these, only CFS was done in a laboratory setting. You can look deeper in the CFS variable pages to find out how many female subjects are in the age group you're looking for.

Great! Yes, Sara Mariani created the "nsrr" fork of the tool and made some enhancements to the interface in recent years.

Good luck - please let us know how it goes!

Jun,

Could you try the NSRR fork of this tool? https://github.com/nsrr/SpectralTrainFig (download source code and extract on your computer)

I was able to get this working with the example EDF/XML. I changed the XML Suffix to ".EDF.XML" since that's what the example file has for the extension.

I am sorry about the struggles you have had with the tools up until this point - the original authors of SpectralTrainFig are no longer connected to the NSRR, so we don't have in-house support.

It sounds like you want HRV examples from healthy subjects. Unfortunately, I think the only datasets with posted HRV results are "special" in one way or another. SHHS has subjects with cardiovascular risk factors, CHAT has children with OSA, MESA has adults with atherosclerosis, etc.

There are certainly a wide range of subjects in each dataset, so you could look for the subjects with the lowest AHI values, lowest number of risk factors, etc. In other words, create some sort of "healthiness" index for a given dataset based on a pre-determined set of factors/variables.

Richard,

I'm not 100% sure what you're asking for. Could you provide more information?

Some of our datasets have "processed" HRV data already available. See these links for examples:

• https://sleepdata.org/datasets/shhs/pages/13-hrv-analysis.md
• https://sleepdata.org/datasets/chat/pages/hrv-analysis.md
• https://sleepdata.org/datasets/mesa/pages/hrv-analysis.md

Happy New Year - thanks for using NSRR!

Reza,

Thanks for adding that to the discussion! I will make a note on the introduction page. Unfortunately, the original raw data and scoring for those 4 studies were lost due to a server crash many years ago.

Jun,

Can you post the URL of the instructions you were following? Thanks!

Austin,

Thanks for inquiring and for your interest in NSRR/dbGaP data. I am going to ping a couple others on the NSRR team who are more familiar with dbGaP and ask them to comment if they have additional information.

Here's my best attempt at answering your questions:

1. Not to my knowledge. I think you are locked into going through Framingham, CHS, and ARIC on dbGaP separately.
2. We made an effort a couple years ago to create and attach ID linking files (NSRR <-> dbGaP) into the cohort-level dbGaP repositories. Based on my records, I believe this was completed for Framingham and (maybe) CHS. Once you have access to both data sources you could assess what you have and then follow-up with additional questions. Even if the ID translations are not immediately apparent we can probably help in figuring out a solution.

Good luck, please let us know if we can assist further!

Mike