Comparison of bispectral index and patient state index during sevoflurane anesthesia in children: a prospective observational study

Background and Aims: Patient state index (PSI) and bispectral index (BIS) are depth of anesthesia monitors utilized for the dosage of propofol usage for induction. We compare PSI, BIS, and Observer’s Assessment of Alertness/Sedation Scale (OAA/S) for propofol dose usage for induction. Material and Methods: Seventy-four ASA I and II patients, aged 18–65 years scheduled for laparoscopic cholecystectomy were included and divided into groups to titrate the drug dosage of propofol needed for induction of anesthesia, monitored by PSI (Group A), BIS (Group B), or clinical OAA/S (Group C). The drug dosage needed for induction was based on a PSI value of 25 ± 2, BIS value of 48 ± 2, and OAA/S value of ≤2 as the endpoint of induction in respective groups. Intraoperative hemodynamic variables and any complications were compared. Results: The mean doses of propofol needed for induction were 2.23 mg/kg (Group A), 2.05 mg/kg (Group B), and 2.11 mg/kg (Group C). A significantly decreased dose was needed to achieve the desired end in Group B compared to Group A (P = 0.01). The hemodynamic variables such as heart rate, systolic blood pressure, and diastolic blood pressure among the three groups were comparable. Conclusion: The clinical method of titrating the dose of propofol for induction and anesthetic depth by the loss of verbal response is comparable to both BIS and PSI monitoring.

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“…Sang–Hwan et al . [ 20 ] in their study, had demonstrated that BIS and PSI can both be used to monitor the maintenance state and recovery state.…”

Section: Discussionmentioning

confidence: 99%

Comparison between patient state index, bispectral index, and clinical parameters for propofol induction in Indian patients: A prospective study

Shajahan

Agrawal

Singla

2023

Journal of Anaesthesiology Clinical Pharmacology

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Estimating the Depth of Anesthesia from EEG Signals Based on a Deep Residual Shrinkage Network

Shi

Huang

Xiao

et al. 2023

Sensors

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The reliable monitoring of the depth of anesthesia (DoA) is essential to control the anesthesia procedure. Electroencephalography (EEG) has been widely used to estimate DoA since EEG could reflect the effect of anesthetic drugs on the central nervous system (CNS). In this study, we propose that a deep learning model consisting mainly of a deep residual shrinkage network (DRSN) and a 1 × 1 convolution network could estimate DoA in terms of patient state index (PSI) values. First, we preprocessed the four raw channels of EEG signals to remove electrical noise and other physiological signals. The proposed model then takes the preprocessed EEG signals as inputs to predict PSI values. Then we extracted 14 features from the preprocessed EEG signals and implemented three conventional feature-based models as comparisons. A dataset of 18 patients was used to evaluate the models’ performances. The results of the five-fold cross-validation show that there is a relatively high similarity between the ground-truth PSI values and the predicted PSI values of our proposed model, which outperforms the conventional models, and further, that the Spearman’s rank correlation coefficient is 0.9344. In addition, an ablation experiment was conducted to demonstrate the effectiveness of the soft-thresholding module for EEG-signal processing, and a cross-subject validation was implemented to illustrate the robustness of the proposed method. In summary, the procedure is not merely feasible for estimating DoA by mimicking PSI values but also inspired us to develop a precise DoA-estimation system with more convincing assessments of anesthetization levels.

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Comparison of bispectral index and patient state index during sevoflurane anesthesia in children: a prospective observational study

Cited by 2 publications

References 22 publications

Comparison between patient state index, bispectral index, and clinical parameters for propofol induction in Indian patients: A prospective study

Comparison between patient state index, bispectral index, and clinical parameters for propofol induction in Indian patients: A prospective study

Estimating the Depth of Anesthesia from EEG Signals Based on a Deep Residual Shrinkage Network

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