Monitoring Depth Of Anesthesia Research Articles

Assessment of Anesthesia Depth Using Effective Brain Connectivity Based on Transfer Entropy on EEG Signal.

Introduction:Ensuring an adequate Depth of Anesthesia (DOA) during surgery is essential for anesthesiologists. Since the effect of anesthetic drugs is on the central nervous system, brain signals such as Electroencephalogram (EEG) can be used for DOA estimation. Anesthesia can interfere among brain regions, so the relationship among different areas can be a key factor in the anesthetic process.Methods:In this paper, by combining the Wiener causality concept and the conditional mutual information, a nonlinear effective connectivity measure called Transfer Entropy (TE) is presented to describe the relationship between EEG signals at frontal and temporal regions from eight volunteers in three anesthetic states (awake, unconscious and recovery). This index is also compared with Granger causality and partial directional coherence methods as common effective connectivity indexes.Results:Based on a statistical analysis of the probability predictive value and Kruskal-Wallis statistical method, TE can effectively fallow the effect-site concentration of propofol and distinguish the anesthetic states well, and perform better than the other effective connectivity indexes. This index is also better than Bispectral Index (BIS) as commercial DOA monitor because of the faster response and higher correlation with the drug concentration effect-site, less irregularity in the unconscious state and better ability to distinguish three states of anesthestesia.Conclusion:TE index is a confident indicator for designing a new monitoring system of the two EEG channels for DOA estimation.

Identification of the General Anesthesia Induced Loss of Consciousness by Cross Fuzzy Entropy-Based Brain Network.

Although the spatiotemporal complexity and network connectivity are clarified to be disrupted during the general anesthesia (GA) induced unconsciousness, it remains to be difficult to exactly monitor the fluctuation of consciousness clinically. In this study, to track the loss of consciousness (LOC) induced by GA, we first developed the multi-channel cross fuzzy entropy method to construct the time-varying networks, whose temporal fluctuations were then explored and quantitatively evaluated. Thereafter, an algorithm was further proposed to detect the time onset at which patients lost their consciousness. The results clarified during the resting state, relatively stable fuzzy fluctuations in multi-channel network architectures and properties were found; by contrast, during the LOC period, the disrupted frontal-occipital connectivity occurred at the early stage, while at the later stage, the inner-frontal connectivity was identified. When specifically exploring the early LOC stage, the uphill of the clustering coefficients and the downhill of the characteristic path length were found, which might help resolve the propofol-induced consciousness fluctuation in patients. Moreover, the developed detection algorithm was validated to have great capacity in exactly capturing the time point (in seconds) at which patients lost consciousness. The findings demonstrated that the time-varying cross-fuzzy networks help decode the GA and are of great significance for developing anesthesia depth monitoring technology clinically.

Comparison of Entropy vs. Bispectral Index Anesthetic Depth Monitoring during Isoflurane Anesthesia in Living Donor Liver Transplantation: Observational Study

Liver transplantation (LT) recipients are known to require less anesthetic agents. Providing minimally required anesthetics while avoiding awareness is especially important in LT recipients because it would help manage perioperative hemodynamic instability with less vasopressor and fast track recovery. This study aims to compare state entropy (SE) against bispectral index (BIS) during isoflurane anesthesia in LT. We adjusted anesthesia to BIS values 40 - 60, and compared it with concomitant SE values. BIS, SE values, and anesthetic requirements according to liver failure severity, etiology and LT stages were analyzed. For BIS-SE differences, SE value that is different from the concomitant BIS by more than 15 was defined as a significant disagreement. Mann Whitney, Kruskal Wallis test and a Poisson exact test were used for analysis. The BIS-SE pair sets of 2895 from 38 patients were analyzed. BIS, SE values and anesthetic requirements were significantly lower in MELD ≥ 20 (p < 0.001 in all) and in alcoholic etiology (p < 0.001 in all). For BIS-SE differences, 320 disagreement data pairs were seen at a rate of 1.33 times/hr (95% CI = [1.19, 1.48], p < 0.001). A significant disagreement was delineated in MELD score ≥ 20 (3.04 times/hr, CI = [2.64, 3.49], p < 0.001), alcoholic etiology (3.19 times/hr, [2.67, 3.78], p < 0.001) and postreperfusion stage (1.63 times/hr, [1.43, 1.85], p < 0.001). In these significant BIS-SE differences, 95.9% (307/320 disagreement data pairs) showed higher BIS than SE. In conclusion, in high MELD and alcoholic etiology, anesthetic requirements were significantly less, and BIS and SE showed great discrepancy with lower SE values. Therefore, when SE monitoring is used during LT, anesthesiologists may need to consider that in high MELD and alcoholic etiology, SE tends to show lower values than the concomitant BIS values that are within optimal anesthetic depth ranges.

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

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.

Bispectral index analysis in general anesthesia: An observational study

Introduction: Bispectral index monitoring (BIS) is one of the major techniques used in monitoring depth of anesthesia. The present study was carried out to observe the changes in BIS values vis-a-vis the changes in hemodynamic parameters during the standard general anaesthesia practices in our institute. Materials and Methods: This prospective observational study was carried out in 50 ASA I/II elective surgeries in adults under general anesthesia. Conditions and drugs likely to interfere with BIS values were excluded. Anesthesia protocol was kept uniform. Patients were induced with IV propofol 2mg/kg, IV pentazocine 0.5mg /kg and IV vecuronium 0.1mg/kg. Patients were intubated with appropopriate size endotracheal tube and oxygen, nitrous oxide, halothane and vecuronium were used for maintanence of anesthesia. Patients were reversed with IV neostigmine 0.05mg/kg and I V Atropine 20mcg/kg. The BIS values, hemodymanic changes, recovery characteristics (including awareness) were noted. Correlation between BIS scores and hemodynamic parameters was assessed. Results: There were predictable changes in BIS scores with the standard anesthesia technique followed in the present study. Similarly, hemodynamic changes were also on the expected lines during the course of anesthesia. However, the correlation between BIS score and hemodynamics could not be established. Conclusion: Bispectral Index Monitor is a useful tool to assess the depth of anesthesia in standard anesthetic management. Alterations in anesthetic management and drug dosages can be guided by BIS scores. Cost factor and the need to use updated and refined versions of the software are the possible limitations. Keywords: Electroencephalography, Consciousness monitors, Anesthesia, General, Hemodynamics.

Postoperative delirium - treatment and prevention.

Postoperative delirium (POD) is one of the most severe complications after surgery.The consequences are dramatic: longer hospitalization, a doubling of mortality and almost all cases develop permanent, yet subtle, cognitive deficits specific to everyday life. Actually, no global guideline with standardized concepts of management exists. Advances in prevention, diagnosis and treatment can improve recognition and risk stratification of delirium and its consequences. Management of POD is a multiprofessional approach and consists of different parts: First, the detection of high-risk patients with a validated tool, preventive nonpharmacological concepts and an intraoperative anesthetic management plan that is individualized to the older patient (e.g. avoiding large swings in blood pressure, vigilance in maintaining normothermia, ensuring adequate analgesia and monitoring of anesthetic depth). In addition to preventive standards, treatment and diagnostic concepts must also be available, both pharmaceutical and nonpharmacological. Not every POD can be prevented. It is important to detect patients with high risk for POD and have standardized concepts of management. The most important predisposing risk factors are a higher age, preexisting cognitive deficits, multimorbidity and an associated prodelirious polypharmacy. In view of demographic change, the implementation of multidisciplinary approaches to pharmacological and nonpharmacological POD management is highly recommended.

Modeling the Effect of Excitation on Depth of Anesthesia Monitoring in γ-Aminobutyric Acid Type A Receptor Agonist ABP-700: Erratum.

Modeling the Effect of Excitation on Depth of Anesthesia Monitoring in γ-Aminobutyric Acid Type A Receptor Agonist ABP-700: Erratum.

Bilateral spinae erector plane blockade as postoperative multimodal analgesia in cardiac surgery: an observational case series

Introduction The post-op acute pain in the thoracic region, characterizes for a component of a superficial deep somatic pain, which presents its most intensity within 24 hours and decreases progressively within the next few days. It has been seen that the highest pain intensity persists during the first 48 hours and decreases from the third day. Nonetheless, the inadequate analgesia in the post-op, could lead to a to a perioperative surgical response to uninhibited stress, which can relate in a direct form with the beginning of pathophysiological changes in all systems. The analgesic mechanism of the ESP block, it's due to the interruption of the sensitive input of the ventral and dorsal branch of the spinal nerve roots, the spinal-caudal spread extends 3 or 4 levels above and below the point of administration of the local anesthetic. Objetives To describe the impact of bilateral spinal erector plane block in cardiac surgery by assessing pain intensity using the Analog Pain Scale (VAS) 24 hours and 48 hours postoperatively at rest and in valsalva, and the Measurement of opioid consumption with the use of a hydromorphone PCA pump. Methods Admitted 19 patients to cardiac surgery of low risk receive bilateral ESP block at a T6 level, with local anesthesia with a total volume of 20cc, (10 cc 1% lidocaine and 10cc 0,5% bupivacaine). All patients received propofol 1mg / kg, fentanyl 2mcg / kg, rocuronium 0.6mg / kg or cisatracurium if CKD (0.1-0.2mg / kg) and initial bolus dexmedetomidine 0.5mcg / kg for induction. Maintenance with dexmedetomidine 0.4 mcg / kg / hr, sevoflurane guided by anesthetic depth monitoring, Dexamethasone 8 mg, paracetamol 1 gr every 6 hours and hydromorphone 0.4 mg. In de ICU, the pain management was paracetamol 1 gr every 6 horas, and opioid PCA is installed for objective assessment of the intake and VAS is evaluated immediately, 24 and 48 hours of postsurgical at rest and valsalva. Results Results: We signed up 19 patients, average age 54 years, with average VAS at rest and Valsalva respectively, immediate EVA 1.2 and 2,8, at 24 hours 1.4 and 4.4 at 48 hours 2,1 and 4.6, with an average consume of opioids 0.9 mg of hydromorphone at 24 hours and 1.3 mg at 48 hours Discussion Conclusions: The erector spine block is a tool to consider for the multidisciplinary management of postoperative pain in cardiac surgery, which offers adequate modulation of deep and superficial somatic pain during the first 48 hours, and a decrease in intravenous opioid consumption, and consequently the reduction of the secondary effects originated from the use of said drugs.

A longitudinal analysis of anesthesia data for cataract surgery: selection of working correlation structure

BackgroundCataract surgery is most commonly done under local anesthesia with anesthesia and sedation controlled. Anesthetic depth and awareness monitoring during surgery frequently lead to irregular-timed observations. Inappropriate choice of working correlation structure in generalized estimating equations (GEE) may lead to inefficient estimation of parameters. The aim of this study was to apply the two new criteria to the anesthesia data for cataract surgery, to select and compare different candidates for working structure.MethodsIn this randomized controlled trial, anesthesia depth and hemodynamic changes were considered to be the primary outcome. The first group received propofol at a dose of 50‑75 μg/kg/min and the second group received 1% isoflurane. We developed a GEE regression model based on several candidates for the working correlation framework and then evaluated it according to CEBIC (Constraint Empirical Bayesian Information Criterion) and CEAIC (Constraint Empirical Akaike Information Criterion) criteria. Data analysis was performed using the R software 3.6.1.ResultsThe mean age of the propofol group was 67.46 years (SD = 12.46 years) and 64.53 years for the isoflurane group (SD = 13.77 years). The mean BIS in isoflurane was higher among all time points than the propofol group, but only the difference between the two groups was statistically significant in 3 min after surgery (P = 0.04). On the basis of the CEAIC and CEBIC criteria, an independent working correlation was the best structure for the BIS outcome. In addition, the best structure was the unstructured correlation for HR. The MAP (mean arterial pressure) parameter estimate results revealed that the AR (1) structure was a good choice.ConclusionIn comparison to CIC and QIC, two CEAIC and CEBIC criteria have chosen a different structure for the working correlation between repeated measurements of anesthetic indices obtained during cataract surgery.

Application of Back Propagation Neural Network and Information Entropy in Deep Detection of Anesthesia

In order to study the monitoring of anesthesia depth during general anesthesia, the EEG (electroencephalogram) signals of 30 patients with laparoscopic general anesthesia were taken as the research objects. The approximate entropy, sample entropy, ranking entropy, and wavelet entropy of EEG signals under different anesthesia conditions were compared by BP (Back Propagation) neural network. The results showed that with the deepening of anesthesia, the four kinds of information entropies of EEG signal showed a downward trend. Among them, the sample entropy algorithm, ranking entropy algorithm, and wavelet entropy algorithm had a higher accuracy in the classification of anesthesia depth. Whereas, the network model established by combining sample entropy index and wavelet entropy index had the highest accuracy in judging anesthesia depth, which was 99.98%. To sum up, the method presented to monitor the depth of anesthesia by combining the characteristics of various EEG signals provides a new reference for the monitoring of the depth of anesthesia.

Clinical practice in the management of postoperative delirium by Chinese anesthesiologists: a cross-sectional survey designed by the European Society of Anaesthesiology.

ObjectiveIn this survey, we assessed the current clinical management of postoperative delirium (POD) among Chinese anesthesiologists, after publishing the European POD guideline.MethodsWe administered an electronic survey, designed according to the European POD guideline. The survey was completed using mobile devices.ResultsIn total, 1,514 respondents from China participated in the survey. Overall, 74.4% of participants reported that delirium is very important. More than 95% of participants stated that they routinely assessed POD. In total, 61.4% screened for POD using clinical observation and 37.6% used a delirium screening tool. Although the depth of anesthesia (a POD risk factor) was monitored, electroencephalogram monitoring was unavailable to 30.6% of respondents. Regarding treatment, only 24.1% of respondents used a standard algorithm; 58.5% used individualized treatment.ConclusionOur survey showed that there are high awareness levels among Chinese anesthesiologists regarding the importance of POD. However, routine assessment and monitoring of all patients, including perioperative anesthesia depth monitoring, and a treatment algorithm need to be implemented on a larger scale. According to the results, efforts should be made to improve the knowledge of POD among Chinese anesthesiologists.

A Real-Time Depth of Anesthesia Monitoring System Based on Deep Neural Network With Large EDO Tolerant EEG Analog Front-End.

In this article, we present a real-time electroencephalogram (EEG) based depth of anesthesia (DoA) monitoring system in conjunction with a deep learning framework, AnesNET. An EEG analog front-end (AFE) that can compensate ±380-mV electrode DC offset using a coarse digital DC servo loop is implemented in the proposed system. The EEG-based MAC, EEGMAC, is introduced as a novel index to accurately predict the DoA, which is designed for applying to patients anesthetized by both volatile and intravenous agents. The proposed deep learning protocol consists of four layers of convolutional neural network and two dense layers. In addition, we optimize the complexity of the deep neural network (DNN) to operate on a microcomputer such as the Raspberry Pi 3, realizing a cost-effective small-size DoA monitoring system. Fabricated in 110-nm CMOS, the prototype AFE consumes 4.33 μW per channel and has the input-referred noise of 0.29 μVrms from 0.5 to 100 Hz with the noise efficiency factor of 2.2. The proposed DNN was evaluated with pre-recorded EEG data from 374 subjects administrated by inhalational anesthetics under surgery, achieving an average squared and absolute errors of 0.048 and 0.05, respectively. The EEGMAC with subjects anesthetized by an intravenous agent also showed a good agreement with the bispectral index value, confirming the proposed DoA index is applicable to both anesthetics. The implemented monitoring system with the Raspberry Pi 3 estimates the EEGMAC within 20 ms, which is about thousand-fold faster than the BIS estimation in literature.

Predicting unconsciousness after propofol administration: qCON, BIS, and ALPHA band frequency power.

During anesthesia induction with propofol the level of arousal progressively decreases until reaching loss of consciousness (LOC). In addition, there is a shift of alpha activity from parieto-occipital to frontal zones, defined as anteriorization. Whilst monitoring LOC and anteriorization would be useful to improve propofol dosage and patient safety, the current devices for anesthetic depthmonitoring are unable to detect these events. The aim of this study was to observe LOC and anteriorization during anesthesia induction with propofol by applying electrodes placed in the frontal and parietal areas. Bispectral index (BIS) and quantium consciousness index (qCON) monitors were simultaneously employed. BIS™ and qCON sensors were placed in the frontal and parieto-occipital regions of 10 alopecic patients who underwent anesthesia with propofol, alfentanil, and remifentanil. The initial biophase target of propofol was 2.5 mcg/mL which was gradually increased until reaching LOC. Wilcoxon signed-rank test was used to study differences in alpha power and qCON/BIS indices along the study; and Pk value to evaluate predictive capability of anteriorization of BIS, qCON, and alpha waves. Parietal BIS and qCON values became significantly higher than frontal values 15min after loss of eye reflex. Anteriorization was observed with both monitors. Pk values for BIS and qCON were strongly predictive of frontal alpha absolute power. During anesthesia induction with propofol it is possible to identify anteriorization with BIS and qCON in the frontal and parieto-occipital regions. Both indices showed different patterns which need to be further studied.

Monitoring of anesthetic depth and EEG band power using phase lag entropy during propofol anesthesia

BackgroundPhase lag entropy (PLE) is a novel anesthetic depth indicator that uses four-channel electroencephalography (EEG) to measure the temporal pattern diversity in the phase relationship of frequency signals in the brain. The purpose of the study was to evaluate the anesthetic depth monitoring using PLE and to evaluate the correlation between PLE and bispectral index (BIS) values during propofol anesthesia.MethodsIn thirty-five adult patients undergoing elective surgery, anesthesia was induced with propofol using target-controlled infusion (the Schneider model). We recorded the PLE value, raw EEG, BIS value, and hemodynamic data when the target effect-site concentration (Ce) of propofol reached 2, 3, 4, 5, and 6 μg/ml before intubation and 6, 5, 4, 3, 2 μg/ml after intubation and injection of muscle relaxant. We analyzed whether PLE and raw EEG data from the PLE monitor reflected the anesthetic depth as the Ce of propofol changed, and whether PLE values were comparable to BIS values.ResultsPLE values were inversely correlated to changes in propofol Ce (propofol Ce from 0 to 6.0 μg/ml, r2 = − 0.83; propofol Ce from 6.0 to 2.0 μg/ml, r2 = − 0.46). In the spectral analysis of EEG acquired from the PLE monitor, the persistence spectrogram revealed a wide distribution of power at loss of consciousness (LOC) and recovery of consciousness (ROC), with a narrow distribution during unconsciousness. The power spectrogram showed the typical pattern seen in propofol anesthesia with slow alpha frequency band oscillation. The PLE value demonstrated a strong correlation with the BIS value during the change in propofol Ce from 0 to 6.0 μg/ml (r2 = 0.84). PLE and BIS values were similar at LOC (62.3 vs. 61.8) (P > 0.05), but PLE values were smaller than BIS values at ROC (64.4 vs 75.7) (P < 0.05).ConclusionsThe PLE value is a useful anesthetic depth indicator, similar to the BIS value, during propofol anesthesia. Spectral analysis of EEG acquired from the PLE monitor demonstrated the typical patterns seen in propofol anesthesia.Trial registrationThis clinical trial was retrospectively registered at ClinicalTrials.gov at October 2017 (NCT03299621).

Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.

Artificial intelligence has been advancing in fields including anesthesiology. This scoping review of the intersection of artificial intelligence and anesthesia research identified and summarized six themes of applications of artificial intelligence in anesthesiology: (1) depth of anesthesia monitoring, (2) control of anesthesia, (3) event and risk prediction, (4) ultrasound guidance, (5) pain management, and (6) operating room logistics. Based on papers identified in the review, several topics within artificial intelligence were described and summarized: (1) machine learning (including supervised, unsupervised, and reinforcement learning), (2) techniques in artificial intelligence (e.g., classical machine learning, neural networks and deep learning, Bayesian methods), and (3) major applied fields in artificial intelligence.The implications of artificial intelligence for the practicing anesthesiologist are discussed as are its limitations and the role of clinicians in further developing artificial intelligence for use in clinical care. Artificial intelligence has the potential to impact the practice of anesthesiology in aspects ranging from perioperative support to critical care delivery to outpatient pain management.

Effect of anesthesia depth on stress response during single-lung ventilation in thoracic surgery

Objective To study the effects of different anesthesia depths on stress response during single-lung ventilation in patients with thoracoscopic lobectomy. Methods Sixty patients selected for elective thoracoscopic lobectomy in the Second Hospital of Shanxi Medical University from September 2018 to May 2019 were randomly divided into three groups according to the digital random table method, with 20 patients in each group. Group A maintained deep anesthesia with the bispectral index (BIS) 36-45, group B maintained moderate anesthesia with BIS 46-55, and group C did not undergo BIS monitoring. The changes of heart rate, mean arterial pressure (MAP), stress indexes cortisol and blood glucose before anesthesia induction (T0), immediately after one-lung ventilation (T1), 60 min after one-lung ventilation (T2) and immediately after skin suture (T3) in the three groups were compared. Results The concentration of blood glucose in group A at T1, T2 and T3 was (5.28±0.49) mmol/L, (5.34±0.49) mmol/L and (5.40±0.47) mmol/L, and the cortisol was (142.75±31.45) ng/ml, (181.36±19.62) ng/ml and (153.81±33.92) ng/ml; the blood glucose in group B was (5.63±0.35) mmol/L, (6.06±0.19) mmol/L and (5.79±0.44) mmol/L, and the cortisol was (168.45±31.16) ng/ml, (171.09±25.28) ng/ml and (159.39±18.77) ng/ml; the blood glucose in group C was (6.35±0.56) mmol/L, (7.04±0.26) mmol/L and (6.17±0.54) mmol/L, and the cortisol was (191.13±46.00) ng/ml, (283.25±30.07) ng/ml and (183.01±19.71) ng/ml, respectively. The blood glucose and cortisol levels in group C at T1, T2 and T3 were higher than those in group A and group B (all P < 0.05). The MAP in group A at T1, T2 and T3 were (69±5) mmHg (1 mmHg= 0.133 kPa), (67±6) mmHg and (75±7) mmHg, respectively, and group B was (80±8) mmHg, (79±4) mmHg and (84±9) mmHg, the differences between the two groups were statistically significant (all P < 0.05). There was significant difference in cortisol between group A and group B at T1 (P < 0.05). The heart rate and MAP at T1, T2 and T3 in group A and group C were significantly different from those at T0 (all P < 0.05). The heart rate and MAP at T1 and T2 in groups B were significantly different from those at T0 (all P < 0.05). Conclusion BIS anesthesia depth monitoring should be performed during single-lung ventilation in thoracic surgery, and BIS should be maintained at 46-55, which can not only inhibit the stress response but also have a slight effect on hemodynamics. Key words: Surgical procedures, operative; Monitoriry, intraoperative; Stress; Depth of anesthesia; Bispectral index monitoring

Technical and clinical evaluation of a closed loop TIVA system with SEDLineTM spectral density monitoring: Multicentric prospective cohort study

IntroductionClosed loop total intravenous anesthesia is a technique in which the patient’s hemodynamic and anesthetic depth variables are monitored, and based on this information, a computer controls the infusion rate of drugs to keep them within pre-established clinical parameters.ObjectiveTo describe the technical and clinical performance of a closed loop system for total intravenous anesthesia with propofol and remifentanil, using the SEDLineTM monitorDesignMulticentric prospective cohort studySettingSurgery roomPatientsASA I-II undergoing elective surgeryMeasurementsThe authors designed a closed loop system that implements a control algorithm based on anesthetic depth monitoring and the Patient State Index (PSITM) of the SEDLine monitor for propofol, and on hemodynamic variables for remifentanil. The measurement of clinical performance was made based on the percentage of PSITM maintenance time in the range 20–50. Precision analysis was evaluated by measuring median performance error (MDPE) can be defined as the median difference between actual and desired values, which refers to the degree of precision in which the controller is able to maintain the control variable within the objective set by the anesthesiologist; it represents the direction (over-prediction or under-prediction) of performance error (PE) rather than size of errors, which is represented by MDAPE, median absolute percentage error, Wobble index, which is used for measuring the intrasubject variability in performance error.ResultsData were obtained from 93 patients in three healthcare centers. The percentage of PSITM maintenance time in the 20–50 range was 92% (80.7–97.0). MDPE was 10.7 (− 11.0–18.0), MDAPE 21.0 (14.2–26.8) and wobble 10.7 (7.0–16.9). No adverse surgical or anesthetic events were found.ConclusionsThe closed loop total intravenous anesthesia system with SEDLine developed by the authors was used without major complication and appear to be feasible its use in clinical performance.

A 10-year retrospective analysis on the incidence of anesthesia awareness with recall in adult patients under total intravenous anesthesia

Background: Intraoperative awareness occurrence ranges between 0.005% and 1.12% of general anesthesia cases and could be a devastating experience for a patient. The incidence of intraoperative awareness in total intravenous anesthesia (TIVA) is higher than in volatile anesthesia without the depth of anesthesia (DOA) monitoring. This retrospective study aimed to evaluate the incidence of intraoperative awareness with recall during TIVA in the isolated health facility. Methods: We performed a retrospective analysis of the incidence of intraoperative awareness with recall during TIVA that involved a large number of patients over 10 years (from January 2008 to July 2018). Cases of death, coma, dementia, severe psychological disorder, incomplete data, or patients aged under 20 years were excluded from this study. All data from the operating rooms' database and the anesthesia records were analyzed. Intraoperative awareness was detected by the patients who spontaneously self-reported accidental awareness during postoperative anesthetic visits within 2 days following the surgery. Moreover, we also visited highly suspected intraoperative awareness patients on a postoperative day 1 for clarifying intraoperative awareness with recall. Results: Of 13,002 patients under TIVA, 11,433 were included in this study. Two confirmed cases of intraoperative awareness were detected, with an incidence of 0.017% (2 of 11,433). As of the type of surgery, a 67-year-old male received elective general surgery and another 45-year-old male received elective orthopedic surgery. Only one patient was under DOA monitoring, and in both instances, no long-term psychological sequelae were reported. Conclusions: This study suggests that the incidence of intraoperative awareness during TIVA is a very rare event if the well-trained anesthesia staff for TIVA is present and when the DOA monitoring is routinely used in high-risk patients. Furthermore, based on the study data, we conclude that the two intraoperative awareness cases could have been prevented.

A 10-year retrospective analysis on the incidence of anesthesia awareness with recall in adult patients under total intravenous anesthesia

Background: Intraoperative awareness occurrence ranges between 0.005% and 1.12% of general anesthesia cases and could be a devastating experience for a patient. The incidence of intraoperative awareness in total intravenous anesthesia (TIVA) is higher than in volatile anesthesia without the depth of anesthesia (DOA) monitoring. This retrospective study aimed to evaluate the incidence of intraoperative awareness with recall during TIVA in the isolated health facility. Methods: We performed a retrospective analysis of the incidence of intraoperative awareness with recall during TIVA that involved a large number of patients over 10 years (from January 2008 to July 2018). Cases of death, coma, dementia, severe psychological disorder, incomplete data, or patients aged under 20 years were excluded from this study. All data from the operating rooms' database and the anesthesia records were analyzed. Intraoperative awareness was detected by the patients who spontaneously self-reported accidental awareness during postoperative anesthetic visits within 2 days following the surgery. Moreover, we also visited highly suspected intraoperative awareness patients on a postoperative day 1 for clarifying intraoperative awareness with recall. Results: Of 13,002 patients under TIVA, 11,433 were included in this study. Two confirmed cases of intraoperative awareness were detected, with an incidence of 0.017% (2 of 11,433). As of the type of surgery, a 67-year-old male received elective general surgery and another 45-year-old male received elective orthopedic surgery. Only one patient was under DOA monitoring, and in both instances, no long-term psychological sequelae were reported. Conclusions: This study suggests that the incidence of intraoperative awareness during TIVA is a very rare event if the well-trained anesthesia staff for TIVA is present and when the DOA monitoring is routinely used in high-risk patients. Furthermore, based on the study data, we conclude that the two intraoperative awareness cases could have been prevented.

Anaesthetic management of patients undergoing deep brain simulation: A retrospective review of 8 cases from a tertiary care center of Pakistan.

Objectives:To review anaesthesia related outcome, perioperative complications and overall length of stay (LOS) in hospital for patients who had deep brain stimulation (DBS).Methods:The study was retrospective review of patients medical records diagnosed with Parkinson disease (PD) and underwent DBS at The Aga Khan University Hospital, Karachi from 2017-2019. Data was reviewed from file notes and patient chart and recorded on predesigned Performa. Frequency and percentages were used to present the data.Results:All patients were anaesthetized using Sleep-Awake-Sleep technique (SAS). Dexmedetomidine was mainly used for conscious sedation. Bispectral index monitor (BIS) was used to monitor the depth of sedation, and kept between 70-85 during sedative phase. All patients had successful intraoperative neurological monitoring, stimulation, and placement of electrodes. Total duration of anesthesia varied significantly in between the patients. Maximum duration was 600 minutes. None of our patient had any intraoperative event related to anaesthetic management. Overall five patients had some adverse events during ward stay. Mean LOS in hospital was four days.Conclusion:Anaesthetic management of DBS is well-tolerated. It requires dedicated team. The SAS technique is excellent for intraoperative neurophysiological monitoring. Careful selection of sedative agents and monitoring depth of anaesthesia using BIS would be beneficial in terms of improving related outcomes.