Amatica Patient-centred chronic disease research

"If you’re a Clinician or patient who knows a proactive Long Covid & ME/CFS clinician - we’d love to talk.

Please reach out via dm or email (team@amaticahealth.com)

Clinicians are integral to acquiring high quality data, solving the disease won’t be possible without them".

 
For what it's worth, I reached out a few weeks ago about some of the methods used in their labs. Specifically, I'm interested in high AngII/long Ang1-7 in Long Covid, and their package includes those tests. From what I am able to dig up online, these tests are not readily available commercially and require flash freezing of blood samples, etc. So, I asked if he could tell me about the methods used for testing AngII and Ang1-7. I never got a response, which is probably telling.
 
"Coming soon we have a series on our first PEM findings.

Below: one patient's ACE levels before and after PEM

Despite being for many patients the single symptom that prevents them from returning to life, PEM is not well understood. Our goal is to add much needed resolution".
 
Answers by them from the replies
Will make a list when I have some time of anecdotes I’ve heard for different treatments!
Gives me hope that is largely just dysfunction vs damage. I think many treatments or cures could maybe take months, but symptom modulation and severity changes can definitely be almost instant
[question about very severe]
For sure. I think it will be more difficult and they may be more sensitive. But I know of reports of very severe people having huge gains over night with different treatments.
 
Sorry to revive this, I used to be a big fan at the start but I'm not anymore.

Unfortunately, they demonstrate very poor data hygiene and overall understanding of how to interpret data.

For example, looking at the before-after scatterplots above, there is no difference at all. Cherry picking one data point to prove a point is a huge red flag. They cannot interpret their data well at all.

Another problem is they simply don't have enough HC and they also forget that HC may have different biomarkers.

Also, their thesis of subgroups will likely fall victim to Simpson's paradox - "a statistical phenomenon where a trend seen in different data subgroups reverses or disappears when the subgroups are combined, "
 
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