Abstract: Abstract： Objective　To evaluate the feasibility and safety of automated administration guided by electroencephalogram (EEG) wavelet index in clinical application. Methods　A total of 52 patients underwent laparoscopic colorectal cancer surgery were selected and divided into the artificial intelligence administration group (IT group) and the manual adjustment group (CT group) by random number table. In the IT group, the infusion rates of remifentanil and propofol were automatically adjusted by automated administration based on EEG wavelet index during anesthesia induction and maintenance. In the CT group, constant speed pumps were used to manually adjust the infusion rates of remifentanil and propofol during induction and maintenance of anesthesia. The target sedation index (WLi) and pain threshold index (PTi) were set at 40-60 in the both groups. Intraoperative doses of remifentanil and propofol and manual adjustment were recorded. Mean arterial pressure (MAP), blood pressure difference (ΔP) and heart rate (HR) were recorded before induction (T0), after induction (T1), immediately after surgery (T2), 1 h after surgery (T3) and at the end of surgery (T4). The intraoperative dose of vasoactive drugs, extubation time after anesthesia, the duration of postoperative anesthesia recovery room (PACU), the percentage of different blood pressure levels in the total operative duration and intraoperative adverse events and complications within 7 days after surgery were recorded. Results　Compared with the CT group, the amount of intraoperative propofol and manual adjustment was significantly decreased in the IT group (P＜0.05). There were no significant differences in the incidence of intraoperative adverse events and complications within 7 days after operation between the two groups (P＞0.05). Conclusion　The automated administration guided by EEG wavelet index can reduce the amount of intraoperative propofol, reduce the incidence of intraoperative hypotension and reduce the workload of anesthesiologists, without increasing the incidence of complications, which can be safely used in patients with laparoscopic radical colorectal cancer surgery.

Key words: artificial intelligence, deep sedation, analgesia, hypotension, postoperative complications, wavelet index