Predictive value of multimodal neurological monitoring in the postoperative neurological dysfunction after cardiovascular surgery with cardiopulmonary bypass.

OBJECTIVE: The use of multimodal neurologic monitoring (MNM) has rarely been reported in monitoring patients after cardiovascular surgery with cardiopulmonary bypass. This prospective observational cohort aims to the effectiveness of MNM in predicting neurologic dysfunction during the postoperative period for the patients undergoing cardiovascular surgery with cardiopulmonary bypass.

METHODS: A total of 156 patients who remained unawake 6 h after ICU admission (Glasgow Coma Scale [GCS] score < 8) were enrolled. These patients were monitored using a quantitative electroencephalogram (qEEG) and transcranial Doppler ultrasound. Neurologic dysfunction was classified according to the American College of Cardiology classification for neurologic injury following cardiac surgery, which includes Type I (focal injury, such as stroke diagnosed by CT/MRI, or coma assessed by GCS) and Type II (global injury, such as delirium assessed by confusion assessment method for the ICU [CAM-ICU], or cognitive dysfunction evaluated by MoCA). The patients were grouped into non-neurologic (n = 85) and neurologic dysfunction groups (n = 71).

RESULTS: The duration of extracorporeal circulation and extubation were significantly longer in the neurologic dysfunction group than the non-neurologic dysfunction group (p < 0.05). The abnormal amplitude-integrated electroencephalogram (aEEG), relative alpha variability (RAV) grade (III-IV), and pulsatility index (PI) of patients in the neurologic dysfunction group were higher and the band energy percentage (α%) and end diastolic velocities (EDVs) were lower than the non-neurologic dysfunction group (p < 0.05). Age, gender, days of tracheal intubation, aEEG, and RAV classification were significantly different between the subgroups that underwent different surgical procedures (p < 0.05). The RAV + A% + EDV + PI combination AUC for predicting neurologic dysfunction was 0.735 (95% CI: 0.658-0.812) with a specificity of 0.843 and a sensitivity of 0.507, which was better than other combined indicators (p < 0.001).

CONCLUSION: MNM can monitor the 24-h changes in postoperative brain function among these targeted patients. The AUC of RAV + α% + EDV + PI combination for predicting neurologic dysfunction was better than other combined or single indicators. Given its relatively low sensitivity, the RAV + α% + EDV + PI combination is suggested to serve best as a tool for identifying high-risk patients warranting intensified monitoring and preemptive neuroprotective strategies, rather than a standalone diagnostic test.