Figure 4.

Timing of optimal S100B sampling to predict intracranial lesion development. Timing of optimal S100B sampling was determined using a sliding window approach, using a logistic regression approach with intracranial lesion as binary outcome and S100B as independent predictor. As shown in (A), there were certain time points that conferred a high Nagelkerke's pseudo-R², indicating that there might be time points of particular interest for S100B sampling. In (B) the distribution of S100B samples across the retrospective study population is shown, with the y-axis representing the number (n) of S100B samples within each time interval (x). IQR, interquartile range.