Effects of circadian rhythm on Narcotrend index and target-controlled infusion concentration of propofol anesthesia

Abstract Background The effects of circadian rhythms on drug metabolism and efficacy are being increasingly recognized. However, the extent to which they affect general anesthesia remains unclear. This study aims to investigate the effects of circadian rhythms on anesthetic depth and the concentrations of propofol target-controlled infusion (TCI). Methods Sixty patients undergoing laparoscopic surgeries were sequentially assigned to four groups. Group ND (n = 15): Propofol TCI with Narcotrend monitor during the day (8:00–18:00), Group NN (n = 15): Propofol TCI with Narcotrend monitor during the night (22:00–5:00), Group CLTD (n = 15): Propofol closed-loop TCI guided by bispectral index (BIS) during the day (8:00–18:00), Group CLTN (n = 15): Propofol closed-loop TCI guided by BIS during the night (22:00–5:00). The Narcotrend index, mean arterial pressure (MAP) and heart rate (HR) were compared between group ND and NN at 7 time points, from 5 min before induction to the end of operation. The propofol TCI concentrations, MAP and HR were compared between group CLTD and CLTN at 7 time points, from 5 min after induction to the end of operation. Results The Narcotrend index, MAP, and HR in group NN were lower than those in group ND from the beginning of mechanical ventilation to the end of operation (p < 0.05). The propofol TCI concentrations in group CLTN were lower than those in group CLTD from the beginning of operation to the end of operation (p < 0.05). Conclusion Circadian rhythms have a significant effect on the depth of anesthesia and drug infusion concentrations during propofol TCI. When using general anesthesia during night surgery, the propofol infusion concentration should be appropriately reduced compared to surgery during the day. Trial registration The present study was registered on the ClinicalTrials.gov website (NCT02440269) and approved by the Medical Ethics Committee of Southwest Hospital of Third Military Medical University (ethics lot number: 2016 Research No. 93). All patients provided informed written consent to participate in the study.

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A Crossover Comparison of the Sensitivity and the Specificity between BIS and AEP in Predicting Unconsciousness in General Anesthesia

Scientific Programming ◽

10.1155/2020/8899957 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Haitao Yang ◽

Guan Wang ◽

Jinxia Gao ◽

Jie Liu

Keyword(s):

General Anesthesia ◽

Sensitivity And Specificity ◽

Auditory Evoked Potentials ◽

High Sensitivity ◽

Anesthetic Technique ◽

Depth Of Anesthesia ◽

Anesthetic Depth ◽

Sevoflurane Group ◽

Anesthetic Drugs ◽

End Tidal

Background. There is an increasing concern of awareness and recall during general anesthesia for both the patient and the anesthetist. The bispectral index (BIS) is used to assess the level of sedation and depth of anesthesia and detect consciousness in different anesthetic drugs. Middle-latency auditory evoked potentials (AEPs) also quantify action of anesthetic drugs and detect the transition from consciousness to unconsciousness. We aim to compare the sensitivity and specificity between BIS and AEP in predicting unconsciousness in inhalational sevoflurane anesthesia and intravenous propofol anesthesia. Methods. Totally, 40 patients were randomly allocated into two groups: propofol or sevoflurane group. In the propofol group, anesthesia was induced with target-controlled infusion propofol. In the sevoflurane group, anesthesia was induced by increasing concentrations of sevoflurane. There were 3 end points during induction: sedation, unconsciousness, and anesthesia. Target and effect-site concentrations of propofol, end-tidal concentration of sevoflurane, and BIS and AEP were recorded at each stage. Results. We obtained good EC50 with both monitors, at which there is a 50% chance that the patient has reached the end point, but the index variation was affected by the anesthetic technique. Propofol had higher correlations with stage of anesthesia, BIS, and AEP than sevoflurane. BIS had higher correlations with depth of anesthesia than AEP, but we did not find an anesthetic depth monitor that had high sensitivity and specificity and is not affected by the anesthetic technique. Conclusions. The prediction powers of BIS and AEP do not seem as good as some papers mentioned.

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The influence of moderate or deep neuromuscular block status on anesthetic depth monitoring system during total intravenous anesthesia using propofol and remifentanil: A randomized trial

Science Progress ◽

10.1177/00368504211010629 ◽

2021 ◽

Vol 104 (2) ◽

pp. 003685042110106

Author(s):

Hyo-Seok Na ◽

Dae-Jin Lim ◽

Bon-Wook Koo ◽

Ah-Young Oh ◽

Pyung-Bok Lee

Keyword(s):

Laparoscopic Cholecystectomy ◽

General Anesthesia ◽

Total Dose ◽

Neuromuscular Block ◽

Total Intravenous Anesthesia ◽

Intravenous Anesthesia ◽

Anesthetic Depth ◽

Time Points ◽

Group Assignment ◽

Deep Neuromuscular Block

The neuromuscular block state may affect the electroencephalogram-derived index representing the anesthetic depth. We applied an Anesthetic Depth Monitoring for Sedation (ADMS) to patients undergoing laparoscopic cholecystectomy under total intravenous anesthesia, and evaluated the requirement of propofol according to the different neuromuscular block state. Adult patients scheduled to undergo laparoscopic cholecystectomy were enrolled and randomly assigned to either the moderate (MB) or deep neuromuscular block (DB) group. The UniCon sensor of ADMS was applied to monitor anesthetic depth and the unicon value was maintained between 40 and 50 during the operation. According to the group assignment, intraoperative rocuronium was administered to maintain proper neuromuscular block state, moderate or deep block state. The unicon value, electromyography (EMG) index, and total dose of propofol and rocuronium were analyzed. At similar anesthetic depth, less propofol was used in the DB group compared to the MB group (6.19 ± 1.36 in the MB mg/kg/h group vs 4.93 ± 3.02 mg/kg/h in the DM group, p = 0.042). As expected, more rocuronium were used in the DB group than in the MB group (0.8 ± 0.2 mg/kg in the MB group vs 1.2 ± 0.2 mg/kg in the DB group, p = 0.023) and the EMG indices were lower in the DB group than in the MB group, at several time points as follows: at starting operation ( p < 0.001); at 15 ( p = 0.019), 45 ( p = 0.011), and 60 min ( p < 0.001) after the initiation of the operation; at the end of operation ( p = 0.003); and at 5 min after the administration of sugammadex ( p < 0.001). At similar anesthetic depth, patients under the deep neuromuscular block state required less propofol with lower intraoperative EMG indices compared to those under the moderate neuromuscular block state during general anesthesia.

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One-Class-Based Intelligent Classifier for Detecting Anomalous Situations During the Anesthetic Process

Logic Journal of IGPL ◽

10.1093/jigpal/jzaa065 ◽

2020 ◽

Author(s):

Alberto Leira ◽

Esteban Jove ◽

Jose M Gonzalez-Cava ◽

José-Luis Casteleiro-Roca ◽

Héctor Quintián ◽

...

Keyword(s):

Side Effects ◽

Anomaly Detection ◽

General Anesthesia ◽

Closed Loop ◽

Real Data ◽

Successful Performance ◽

Final Model ◽

Detection Techniques ◽

Adverse Side Effects ◽

Operative Recovery

Abstract Closed-loop administration of propofol for the control of hypnosis in anesthesia has evidenced an outperformance when comparing it with manual administration in terms of drug consumption and post-operative recovery of patients. Unlike other systems, the success of this strategy lies on the availability of a feedback variable capable of quantifying the current hypnotic state of the patient. However, the appearance of anomalies during the anesthetic process may result in inaccurate actions of the automatic controller. These anomalies may come from the monitors, the syringe pumps, the actions of the surgeon or even from alterations in patients. This could produce adverse side effects that can affect the patient postoperative and reduce the safety of the patient in the operating room. Then, the use of anomaly detection techniques plays a significant role to avoid this undesirable situations. This work assesses different one-class intelligent techniques to detect anomalies in patients undergoing general anesthesia. Due to the difficulty of obtaining real data from anomaly situations, artificial outliers are generated to check the performance of each classifier. The final model presents successful performance.

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