making predictions from detrended data
I'm just guessing but I can think of two options: 


Train the model from the original data, including features which represent the current trend so that the model can integrate it. It makes the job of the model more complex so it might not work very well.
Since you can untrend the data I assume that you can calculate the trend function. So you could train an independent model for this trend function and apply it on the predictions obtained with the untrended model. In this case performance depend how accurately the trend is predicted.