Hello, everyone. A frequent type of problem that I deal with in my work can be characterized as follows: 1) I have some observational data that is obtained from various hospital records, 2) The primary exposure of interest is some intraoperative continuous measure such as heart rate or blood pressure, 3) The outcome is some sort of postoperative complication (e.g. postoperative delirium) and is usually binary, 4) The researchers are usually interested in characterizing the association between these and also finding an “optimal” cut-point.
The sample size is usually quite large, so I suggest using regression adjustment (instead of PS methods) and also use restricted cubic splines to allow for non-linear relationships. One problem here is that it is not obvious how the exposure variable should be summarized i.e. should I use min. mean arterial pressure (MAP), mean MAP, max MAP etc.? (Or perhaps all of them?)
Another problem arises when dealing with “optimal cut-points”. So, for example, the researchers might want to say that time-weighted-average (TWA) MAP < 50 mmHg is associated with increased risk of postoperative kidney injury. As I understand it, optimal cut-points don’t really make sense in a multivariate setting. Furthermore, you’re necessarily throwing away a lot of other data because most patients might not fall below 50 mmHg. So what do you do when a researchers requests an optimal cut-point?
To summarize, I have two main questions: 1) What is the best way to summarize the exposure variable and characterize its association the binary outcome? 2) How to deal with requests for optimal cut-points?
Apologies if this has already been answered satisfactorily elsewhere (my google search yielded many useful threads, but perhaps none that exactly answered my questions.) General advice, links to previous discussion, exemplary papers dealing with such analyses etc. are all welcome. Thank you!