You should present demographics for every round available for accuracy, completeness, and your own personal sanity. Drop-outs and people lost to follow-ups, are still data points, especially in medical/psychological/sociological studies. They may not have any associated data, but they were recruited and participated at least during the initial phase of data collection (demographics), and not counting them can imply other things.
Anyways, I like using an example to show why it helps present a clearer image.
Let's say 100 animals sign up for a study at Round 1. The demographics are as follows: 50 dogs, 50 cats.
However, when Round 2 rolls around, 20 cats are nowhere to be found. The results are collected from the remaining subjects; 25 dogs are peanut butter lovers, and 15 cats are peanut butter lovers.
If you only say that 20 animals dropped out, the information presented here doesn't mean very much, since you don't know what animals dropped out. In actuality, both dogs and cats had a 50% split based on the population of data collected, but presenting information only partway can be misconstrued as perhaps it was 25/40 dogs and 15/40 cats, because you haven't provided any. In addition, neglecting to mention that you originally had 50 dogs and 50 cats and only presenting that you had 50 dogs and 30 cats in the final results could indicate selection bias or a lack of interest, as opposed to losing cats to follow-up exams.
So you would present in a nice table or summary:
During Round 1, 50 dogs and 50 cats were recruited for the peanut butter study. However, 20 of the original 50 cats (40.0%) dropped out before Round 2 testing and could not be replaced. During Round 2 testing, it was found that 25 of 50 dogs (50.0%) and 15 of 30 cats (50.0%) preferred peanut butter.