Methods to control the blood glucose (BG) levels of patients in intensive care units (ICU) improve the outcomes. The development of continuous BG levels monitoring devices has also permitted to optimize these processes. Recently it was shown that a complexity loss of the BG signal is linked to poor clinical outcomes. Thus, it becomes essential to decipher this relation to design efficient BG level control methods. In previous studies the BG signal complexity was calculated as a single index for the whole ICU stay. Although, these approaches did not grasp the potential variability of the BG signal complexity. Therefore, we setup this pilot study using a continuous monitoring of central venous BG levels in ten critically ill patients (EIRUS platform, Maquet Critical CARE AB, Solna, Sweden). Data were processed and the complexity was assessed by the detrended fluctuation analysis and multiscale entropy (MSE) methods. Finally, recordings were split into 24 h overlapping intervals and a MSE analysis was applied to each of them. The MSE analysis on time intervals revealed an entropy variation and allowed periodic BG signal complexity assessments. To highlight differences of MSE between each time interval we calculated the MSE complexity index defined as the area under the curve. This new approach could pave the way to future studies exploring new strategies aimed at restoring blood glucose complexity during the ICU stay.