@willball12 from a methodological perspective, you can adjust for things that are (1) not mediators and (2) latter on the 'causal path'. In the figure, either {X1} or {X2} are minimally sufficient sets. So, we can adjust for things that are not baseline (as long as *not* mediators).

There is a benefit to this: adjusting for variables closest to the outcome (e.g., X2) result in estimators with the greatest precision.

In this particular case, I don't know if I reasonably believe that those aren't mediators