The answer to your question depends on the purpose of your Table 1.
One purpose of Table 1 would be to help your readers understand more about the subjects in whom you are investigating the association between smoking and plaque, adjusted for cofounders. In this case, Table 1 could include so-called demographic variables (e.g., age, gender) and possibly the confounders you are adjusting for in your model. You could set up this table so that it has the following columns:
Table 1: Descriptive statistics.
Variable Subjects Subjects All Subjects
With Plaque Without Plaque
(n = 20) (n = 80) (n = 100)
Age, mean (sd)
Gender, count (%)
Males
Females
Other
Etc.
Another purpose of Table 1 would be to help readers understand more about the variables that were included in your model. In that case, your table would look similar to the one suggested above, except that would include only variables that made it into your model.
If your outcome variable were to include missing values, you would have to capture that in your table (e.g., insert a column titled Subjects With Missing Plaque Status).
For your numeric variables (e.g., Age), you should report measures of center and spread that are most suitable given the distribution of the data.