openpharma / clinsight

ClinSight - An application for medical monitoring within clinical trials
https://openpharma.github.io/clinsight/
Other
3 stars 0 forks source link

Allow plotting 'by' a variable, like timepoint #121

Open aclark02-arcus opened 3 weeks ago

aclark02-arcus commented 3 weeks ago

In our vital signs data, we have some measurements gathered at different timepoints... for example: measuring blood pressure after lying down, standing, and standing for 5 mins (etc). Because of that, are converting that column to an item_type = 'other' and that's forcing the whole tab to only display a table. If we mark it as 'continuous', the plot will have several points plotted on the same day. I envision this use case being an enhancement to the plots more than anything. But in order to avoid facet_wrap(), timepoint would probably have to be a filter on the right hand side. Or perhaps give users the option to aggregate the measurements into a mean plotted over time? OR you could adapt the legend and to make each measurement a different shape? Definitely a lot of ways to go.

Originally posted by @aclark02-arcus in https://github.com/openpharma/clinsight/issues/117#issuecomment-2442091468

LDSamson commented 3 weeks ago

item_type = 'other' is meant for data incompatible for figures, so I think we should not use it this way. What if you plot them in separate figures for the time being, and give them names like SysBP 5min standing, SysBP laying down etc? It would be the easiest solution for now and you can still properly compare different conditions.

It is also the question what the medical monitors want to know and based on that you can provide a study-specific derivative value. For example, if they are interested in orthostatic hypotension, you could create a variable that shows the difference of the systolic blood pressure measured when laying down and when standing.

Can you maybe create an example dataset so that we can check out different visualization methods? If we introduce new figures they should of course be robust & reliable.