Solved – Why does changing how I code the dumthe variable change significance

It usually makes no sense to interpret main effects in the presence of an interaction involving that variable because the main effects each have the meaning of being the difference in mean (or log-odds in a logistic regression) of the response when the other variable is at its reference level (or at zero if it is numeric). When you change the coding, you change the reference level and therefore you change the estimates. So the models are actually the same, they are just parameterised differently. Since the models are the same, but the parameters have different meanings, their statistical significance must differ too.

Edit: In your example, the intercept is the log-odds of the response when both variables are at their reference level (or zero if they are coded as numeric). In your first model with no pressure coded as 0, this is 0.37. In the model with pressure coded as 0 it is 1.28, a difference of 0.91 so this the contribution of pressure to the log-odds of the response when the other variable is 0. Now note that this is exactly the main effect of no_pressure in model 1, confirming the above interpretation of the main effect in the presence of an interaction. This analysis can be readily extended to the other main effect and the interaction.