Had a convo over DM at #Bluesky about how I'd design and what to test in #longcovid trials. For whatever is worth, here are my thoughts about population selection, design, intervention, outcomes and the rationale to do things this way.
As always discource is welcome
As always discource is welcome
Comments
https://bsky.app/profile/christosargyrop.bsky.social/post/3licu4yscbc24
Ofc for an individualized outcome, one has to add a quant dimension. This citation makes my proposal complete. I will add it to th substack later today
https://open.substack.com/pub/christosargyropoulos/p/a-modest-proposal-for-a-clinical?utm_source=share&utm_medium=android&r=1tfbmy
Rob Wust has proven these physiological differences:
Stratify individuals via evidence of
a. persistence (which many have via antigen or sequencing testing in plasma, stool or other accessible biological matrix)
b. T cell Exhaustion markers
c. Evidence of vascular involvement(VEGF/caveolin/VVO relevant biomarkers)
and
A 2 antivirals with different MoA : protease inhibitors + remdisivir with and without maraviroc
B metformin
C. For those we can type the antigen (MassSpec) or RNA to one of the variants, add the monoclonal that was effective against that variant
#longcovid
1. Symptom burden, functioning and time to resolution of what individuals claim their LC was
2. Antigen , RNA levels, inflammation and vascular markers
3. Correlation between 2 and 1 (joint biomarker and time to event analysis) & get an idea of sensitivity/specifity
#longcovid
1. Generate a surrogate similar to the HIV TLOVR or snapshot from the virus and inflammatory biomarkers derived which will be used in subsequent trials to derive somewhat objective markers of response
Important to understand if a surrogate is even possible
#longcovid
If any of the interventions work, ithe design will tells us if we can a priori identify those who may respond & establish surrogates for simplification trials