I am a medical doctor with limited statistical knowledge, so bare with me...

I am trying to answer the question: Does dispatching a critical care team (CCT) to out-of-hospital cardiac arrest improve survival? I have a dataset of 2000 cases and survival rates are 7.5% overall.

In reality, both 'CCT' dispatch and 'survival' are influenced by additional continuous and categorical variables:

Age

Location of arrest

Witnessed arrest

Bystander CPR

Initial cardiac rhythm

Ambulance response time

To control for these variables, we tried case-control matching but experienced too much data loss. I had a junior colleague run multiple logistic regression on STATA, and the results seem intuitively correct.

I have two questions regarding multiple logistic regression and interactions:

1. As I am only interested in the effects of 'CCT' on 'survival', do I need to check for and include interactions between the other variables? For example, I know that 'bystander CPR' has an effect on 'initial cardiac rhythm'. Will adding an interaction variable for 'bystander CPR' and 'initial cardiac rhythm' have an effect on the odds ratio of 'CCT' for 'survival'?

2. I guess I will have to include interactions between 'CCT' and variables I suspect to influence CCT dispatch, such as 'age' and 'location of arrest'? Do I do this one variable at a time and then check after each addition to see if the interaction actually improves the model?

Any comments much appreciated, I hope that I am not too far off target with all of this!

Regards,

Johannes