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•An additional intravenous dose of ramosetron once daily until the second-day post-surgery did not reduce the incidence of PONV in female patients undergoing breast surgery compared to the standard intravenous dose (0.3 mg) of ramosetron administered only once immediately before the end of surgery.•In predicting the occurrence of PONV, the Apfel model showed high sensitivity; however, its specificity and accuracy were lower than ML-based models.•In an adjusted analysis using a logistic regression model, the history of PONV or motion sickness and ASA were significant risk factors for PONV, and the odds ratio was high in this order. The study aimed to compare the postoperative nausea and vomiting (PONV) preventive effect of repeated administration of ramosetron with the standard treatment group and compare models to predict the incidence of PONV using machine-learning techniques. A total of 261 patients scheduled for breast surgery were analyzed to evaluate the effectiveness of repeated intravenous administration of ramosetron. All patients were administered 0.3 mg ramosetron just before the end of surgery. For the repeated dose of ramosetron group, an additional dose of 0.3 mg was administered at 4, 22, and 46 hours after the end of the surgery. Postoperative nausea, vomiting, and retching were evaluated using the Rhodes Index of Nausea, Vomiting, and Retching at 6, 24, and 48 hours postoperatively. Previously published randomized controlled data were combined with the data of this study to create a new dataset of 1390 patients, and machine-learning–based PONV prediction models (classification tree, random forest, extreme gradient boosting, and neural network) was constructed and compared with the Apfel model. Fifty patients (38.5%) and 60 patients (45.8%) reported nausea, vomiting, or retching 48 hours postoperatively in the standard and repeated-dose groups, respectively (P = 0.317, χ2 test). Median sensitivity, specificity, and accuracy of the Apfel model analyzed using the training set were 0.815, 0.344, and 0.495, respectively. The repeated administration of ramosetron did not reduce the incidence of PONV. The Apfel model had high sensitivity, however, its specificity and accuracy were lower than that in machine-learning–based models.

We evaluated the performance of the Surgical Plethysmographic Index (SPI) and the Analgesia Nociception Index (ANI) as surrogate pain measures and determined their respective cut-off values for detecting pain in conscious postoperative patients. In total, 192 patients after elective surgery were enrolled. Baseline SPI and ANI data were acquired for 10 min in the operating room prior to surgery when the patients rated their pain as 0 on the numerical rating scale (NRS). Upon arrival in the post-anaesthesia care unit (PACU) after surgery, SPI and ANI data were recorded for 10 min. The means of the recorded data at OR and PACU were defined as the values representing baseline and postoperative pain, respectively. SPI and ANI data obtained from 189 patients were analysed, who were anesthetized with propofol (n = 149) or sevoflurane (n = 40). Remifentanil was continuously infused intraoperatively in all patients. The values of SPI and ANI were significantly different in conscious patients without (NRS = 0) and with pain (NRS > 0). The areas under the receiver operating curves for SPI and ANI were 0.73 (P < 0.0001) and 0.67 (P < 0.0001), respectively. The cut-off values for SPI and ANI in predicting postoperative pain were 44 (sensitivity: 84%, specificity: 53%) and 63 (sensitivity: 52%, specificity: 82%), respectively, which are different from those suggested by their respective manufacturers for use in intraoperative state under general anaesthesia. The cut-off values of SPI and ANI for detecting pain were similar regardless of the type of anesthesia.

Measuring complexity from noisy time series provides a crucial insight into the understanding and monitoring of pattern dynamics of complex dynamical systems, including physiological systems such as complex electroencephalogram (EEG) times series observed during anesthesia. We introduce a simple, yet noble complexity measure, called the lumped permutation entropy (LPE) based on the permutation entropy (PE), which allows a tie rank on the pattern formation and shows the robustness under the influence of strong noise, overcoming some limitations of PE and its variants in noisy signals. The robustness of LPE is demonstrated for complex time series from a typical chaotic dynamical system and is applied to empirical electroencephalographic (EEG) data obtained from subjects anesthetized by propofol. In particular, we found that the entropic complexity of EEG time series based on LPE is inversely correlated with plasma concentration of propofol and shows better performance and more robustness than PE and other types of entropic algorithms in indicating the anesthetic depth during the progress of general anesthesia. LPE can be used as complexity measure for real-time monitoring of anesthetic depth during anesthesia.

Side effects occur when excessive or low doses of analgesics are administered compared to the required amount to mediate the pain induced during surgery. It is important to accurately assess the pain level of the patient during surgery. We proposed a pain classifier based on a deep belief network (DBN) using photoplethysmography (PPG). Our DBN learned about a complex nonlinear relationship between extracted PPG features and pain status based on the numeric rating scale (NRS). A bagging ensemble model was used to improve classification performance. The DBN classifier showed better classification results than multilayer perceptron neural network (MLPNN) and support vector machine (SVM) models. In addition, the classification performance was improved when the selective bagging model was applied compared with the use of each single model classifier. The pain classifier based on DBN using a selective bagging model can be helpful in developing a pain classification system.

In Korea, the approved anesthetic regimen of remimazolam starts with 6 mg/kg/h or 12 mg/kg/h until loss of consciousness, followed by maintenance at 1–2 mg/kg/h. Some patients receiving remimazolam for general anesthesia experience occasional difficulty maintaining bispectral index (BIS) value ˂ 60. This retrospective study aimed to analyze the data from patients undergoing elective surgery under remimazolam based-general anesthesia to determine the frequency and physical characteristics of patients with BIS values ˂ 60. The criterion was established for patients with a poorly maintained BIS value < 60. The frequency and physical characteristics of patients who satisfied this criterion were investigated through their medical records. The modified Brice interview was conducted within 24 h after surgery. Among the 1500 patients included in the analysis, 61 (4.1%) met the criteria for BIS ˂ 60. Based on the modified Brice interview, none of the patients with poorly maintained BIS ˂ 60 complained of intraoperative awareness based on the modified Brice interview or exhibit specific physical characteristics. These patients accounted for less than 5% of the total population studied. Notably, physical characteristics alone are insufficient to predict such patients before surgery.

The precise mechanism and optimal measure of anesthetic-induced unconsciousness has yet to be elucidated. Preferential inhibition of feedback connectivity from frontal to parietal brain networks is one potential neurophysiologic correlate, but has only been demonstrated in animals or under limited conditions in healthy volunteers. We recruited eighteen patients presenting for surgery under general anesthesia; electroencephalography of the frontal and parietal regions was acquired during (i) baseline consciousness, (ii) anesthetic induction with propofol or sevoflurane, (iii) general anesthesia, (iv) recovery of consciousness, and (v) post-recovery states. We used two measures of effective connectivity, evolutional map approach and symbolic transfer entropy, to analyze causal interactions of the frontal and parietal regions. The dominant feedback connectivity of the baseline conscious state was inhibited after anesthetic induction and during general anesthesia, resulting in reduced asymmetry of feedback and feedforward connections in the frontoparietal network. Dominant feedback connectivity returned when patients recovered from anesthesia. Both analytic techniques and both classes of anesthetics demonstrated similar results in this heterogeneous population of surgical patients. The disruption of dominant feedback connectivity in the frontoparietal network is a common neurophysiologic correlate of general anesthesia across two anesthetic classes and two analytic measures. This study represents a key translational step from the underlying cognitive neuroscience of consciousness to more sophisticated monitoring of anesthetic effects in human surgical patients.

Hepatitis C virus (HCV) is the major cause of progressive liver disease such as chronic hepatitis, cirrhosis, and hepatocellular carcinoma. Previously, we reported that a 29 nucleotide-long 2’-F pyrimidine modified RNA aptamer against the HCV nonstructural protein 5B efficiently inhibited HCV replication and suppressed HCV infectious virus particle formation in a cell culture system. In this study, we modified this aptamer through conjugation of cholesterol for in vivo availability. This cholesterol-conjugated aptamer (chol-aptamer) efficiently entered the cell and inhibited HCV RNA replication, without any alteration in gene expression profiling including innate immune response-related genes. Moreover, systemic administration of the chol-aptamer was well tolerated without any abnormalities in mice. To evaluate the pharmacokinetics of the chol-aptamer in vivo, dose proportionality, bioavailability, and pharmacokinetic parameters were evaluated by noncompartmental analyses in normal BALB/c mice. Population analysis was performed using nonlinear mixed effects modeling. Moreover, the pharmacokinetics of two different routes (intravenous, IV, versus intraperitoneal, IP) were compared. Cholesterol conjugation showed dose proportionality, extended the time that the aptamer was in the plasma, and enhanced aptamer exposure to the body. Noticeably, the IV route was more suitable than the IP route due to the chol-aptamer remaining in the plasma for a longer period of time.

We characterized the volume kinetics of crystalloid solutions (Ringer’s lactate solution and 5% dextrose water) and colloid solutions (6% tetrastarch and 10% pentastarch) by nonlinear mixed-effects modeling in healthy volunteers. We also assessed whether the bioelectrical impedance analysis parameters are significant covariates for volume kinetic parameters. Twelve male volunteers were randomly allocated to four groups, and each group received the four fluid solutions in specified sequences, separated by 1-week intervals to avoid any carryover effects. Volunteers received 40 ml/kg Ringer’s lactate solution, 20 ml/kg 5% dextrose water, 1000 ml 6% tetrastarch, and 1000 ml 10% pentastarch over 1 h. Arterial blood samples were collected to measure the hemoglobin concentration at different time points. Bioelectrical impedance spectroscopy (BIS, INBODY S10, InBody CO., LTD, Seoul, Korea) was also carried out at preset time points. In total, 671 hemoglobin-derived plasma dilution data points were used to determine the volume kinetic characteristics of each fluid. The changes in plasma dilution induced by administration of crystalloid and colloid solutions were well-described by the two-volume and one-volume models, respectively. Extracellular water was a significant covariate for the peripheral volume of distribution at baseline in the volume kinetic model of Ringer’s lactate solution. When the same amount was administered, the colloid solutions had ~4 times more plasma expansion effect than did the crystalloid solutions. Starches with larger molecular weights maintained the volume expansion effect longer than those with smaller molecular weights.

In a previous study, we developed a new analgesic index using nasal photoplethysmography (nasal photoplethysmographic index, NPI) and showed that the NPI was superior to the surgical pleth index (SPI) in distinguishing pain above numerical rating scale 3. Because the NPI was developed using data obtained from conscious patients with pain, we evaluated the performance of NPI in comparison with the SPI and the analgesia nociception index (ANI) in patients under general anaesthesia with target-controlled infusion of propofol and remifentanil. The time of nociception occurrence was defined as when the signs of inadequate anaesthesia occurred. The median values of NPI, SPI, and ANI for 1 minute from the time of the sign of inadequate anaesthesia were determined as the value of each analgesic index that represents inadequate anaesthesia. The time of no nociception was determined as 2 minutes before the onset of skin incision, and the median value for 1 minute from that time was defined as the baseline value. In total, 81 patients were included in the analysis. NPI showed good performance in distinguishing inadequate anaesthesia during propofol-remifentanil based general anaesthesia. NPI had the highest value in terms of area under the receiver operating characteristic curve, albeit without statistical significance (NPI: 0.733, SPI: 0.722, ANI: 0.668). The coefficient of variations of baseline values of NPI, SPI, and ANI were 27.5, 47.2, and 26.1, respectively. Thus, the NPI was effective for detecting inadequate anaesthesia, showing similar performance with both indices and less baseline inter-individual variability than the SPI.

This study aimed to investigate the effect of epoch length of hypnotic depth indicators on the blood–brain equilibration rate constant (ke0) estimates of propofol. Propofol was administered by zero-order infusion (1.5, 3.0, 6, and 12 mg·kg−1·h−1) for one hour in 63 healthy volunteers. The ke0 of propofol was estimated using an effect-compartment model linking pharmacokinetics and pharmacodynamics, in which response variables were electroencephalographic approximate entropy (ApEn) or bispectral index (BIS) (n = 32 each for propofol infusion rates of 6 and 12 mg·kg−1·h−1). Epoch lengths of ApEn were 2, 10, 30, and 60 seconds (s). The correlations between plasma propofol concentrations (Cp) and BIS and ApEn 2, 10, 30, and 60 s were determined, as was the Ce associated with 50% probability of unconsciousness (Ce50,LOC). The pharmacokinetics of propofol were well described by a three-compartment model. The correlation coefficient between Cp and ApEn 2, 10, 30, and 60 s were −0.64, −0.54, −0.39, and −0.26, respectively, whereas correlation coefficient between Cp and BIS was −0.74. The blood-brain equilibration half-life based on the ke0 estimates for ApEn at 2, 10, 30, 60 s and BIS were 4.31, 3.96, 5.78. 6.54, 5.09 min, respectively, whereas the Ce50,LOC for ApEn at 2, 10, 30, 60 s and BIS were 1.55, 1.47, 1.28, 1.04, and 1.55 μg·ml−1, respectively. Since ke0, which determines the onset of drug action, varies according to the epoch length, it is necessary to consider the epoch length together when estimating ke0.