I’ve been discussing a bit with @jreps , @msuchard , @Patrick_Ryan @SCYou @krfeeney @hripcsa and others the possibility of training new models for the prediction of hospital admission in younger people with covid. The reasons I think this is important (and altogether a whole different model vs COVER) are two: 1.there is an over-representation of young people amongst those affected in the upcoming/ongoing 2nd wave; and 2.the clinician still beating inside me tells me predictors of outcomes amongst youngsters are going to be very different.
This is therefore the T, TAR and O I would propose:
- T - people age <50 years old diagnosed with COVID19 or tested+ before or not admitted to hospital on that same day (ie diagnosed in an outpatient setting)
- TAR - <=30 days after index date (index date being the earlier of a clinical diagnosis or a test+)
- O - I would propose we try to train models for O1 hospital admission and O2 death, although I suspect the number of O2 will be probably too small…
Anyone interested to contribute and join this venture? I’m “looking” at my fav prediction wizards (@RossW @Rijnbeek plus the above mentioned) but also about anybody else with knowledge and/or data potentially useful for this (@tduarte @Sara_Khalid1 @scottduvall and many others)
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