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Abstract Titrating tacrolimus concentration in liver transplantation recipients remains a challenge in the early post-transplant period. This multicenter retrospective cohort study aimed to develop and validate a machine-learning algorithm to predict tacrolimus concentration. Data from 443 patients undergoing liver transplantation between 2017 and 2020 at an academic hospital in South Korea were collected to train machine-learning models. Long short-term memory (LSTM) and gradient-boosted regression tree (GBRT) models were developed using time-series doses and concentrations of tacrolimus with covariates of age, sex, weight, height, liver enzymes, total bilirubin, international normalized ratio, albumin, serum creatinine, and hematocrit. We conducted performance comparisons with linear regression and populational pharmacokinetic models, followed by external validation using the eICU Collaborative Research Database collected in the United States between 2014 and 2015. In the external validation, the LSTM outperformed the GBRT, linear regression, and populational pharmacokinetic models with median performance error (8.8%, 25.3%, 13.9%, and − 11.4%, respectively; P

Abstract We present the INSPIRE dataset, a publicly available research dataset in perioperative medicine, which includes approximately 130,000 surgical operations at an academic institution in South Korea over a ten-year period between 2011 and 2020. This comprehensive dataset includes patient characteristics such as age, sex, American Society of Anesthesiologists physical status classification, diagnosis, surgical procedure code, department, and type of anaesthesia. The dataset also includes vital signs in the operating theatre, general wards, and intensive care units (ICUs), laboratory results from six months before admission to six months after discharge, and medication during hospitalisation. Complications include total hospital and ICU length of stay and in-hospital death. We hope this dataset will inspire collaborative research and development in perioperative medicine and serve as a reproducible external validation dataset to improve surgical outcomes.

Abstract This study evaluated the effect of hyperbilirubinemia on the accuracy of continuous non-invasive hemoglobin (SpHb) measurements in liver transplantation recipients. Overall, 1465 SpHb and laboratory hemoglobin (Hb) measurement pairs (n = 296 patients) were analyzed. Patients were grouped into normal ( 3.0 mg/dL) hyperbilirubinemia groups based on the preoperative serum total bilirubin levels. Bland–Altman analysis showed a bias of 0.20 (95% limit of agreement, LoA: − 2.59 to 3.00) g/dL, 0.98 (95% LoA: − 1.38 to 3.35) g/dL, and 1.23 (95% LoA: − 1.16 to 3.63) g/dL for the normal, mild-to-moderate, and severe groups, respectively. The four-quadrant plot showed reliable trending ability in all groups (concordance rate > 92%). The rates of possible missed transfusion (SpHb > 7.0 g/dL for Hb

Background Use of endotracheal tubes (ETTs) with appropriate size and depth can help minimize intubation-related complications in pediatric patients. Existing age-based formulae for selecting the optimal ETT size present several inaccuracies. We developed a machine learning model that predicts the optimal size and depth of ETTs in pediatric patients using demographic data, enabling clinical applications. Methods Data from 37,057 patients younger than 12 years who underwent general anesthesia with endotracheal intubation were retrospectively analyzed. Gradient boosted regression tree (GBRT) model was developed and compared with traditional age-based formulae. Results The GBRT model demonstrated the highest macro-averaged F1 scores of 0.502 (95% CI [0.486, 0.568]) and 0.669 (95% CI [0.640, 0.694]) for predicting the uncuffed and cuffed ETT size (internal diameter), outperforming the age-based formulae that yielded 0.163 (95% CI [0.140, 0.196], P < 0.001) and 0.392 (95% CI [0.378, 0.406], P < 0.001), respectively. In predicting the ETT depth (distance from tip to lip corner), the GBRT model showed the lowest mean absolute error of 0.71 cm (95% CI [0.69, 0.72]) and 0.72 cm (95% CI [0.70, 0.74]) compared to the age-based formulae that showed an error of 1.18 cm (95% CI [1.16, 1.20], P < 0.001) and 1.34 cm (95% CI [1.31, 1.38], P < 0.001) for uncuffed and cuffed ETT, respectively. Conclusions The GBRT model using only demographic data accurately predicted the ETT size and depth. If these results are validated, the model may be practical for predicting optimal ETT size and depth for pediatric patients.

Abstract Predicting in-hospital cardiac arrest in patients admitted to an intensive care unit (ICU) allows prompt interventions to improve patient outcomes. We developed and validated a machine learning-based real-time model for in-hospital cardiac arrest predictions using electrocardiogram (ECG)-based heart rate variability (HRV) measures. The HRV measures, including time/frequency domains and nonlinear measures, were calculated from 5 min epochs of ECG signals from ICU patients. A light gradient boosting machine (LGBM) algorithm was used to develop the proposed model for predicting in-hospital cardiac arrest within 0.5–24 h. The LGBM model using 33 HRV measures achieved an area under the receiver operating characteristic curve of 0.881 (95% CI: 0.875–0.887) and an area under the precision-recall curve of 0.104 (95% CI: 0.093–0.116). The most important feature was the baseline width of the triangular interpolation of the RR interval histogram. As our model uses only ECG data, it can be easily applied in clinical practice.

Abstract Early allograft dysfunction (EAD) and acute kidney injury (AKI) are common and clinically important complications after liver transplantation. Serum lactate level at the end of surgery could predict EAD and neutrophil gelatinase-associated lipocalin (NGAL) is known as a biomarker for AKI after liver transplantation. The authors investigated whether the combination of these two laboratory tests could be used as an early predictor of these two complications of EAD and AKI. We reviewed cases undergoing living donor liver transplantation (n = 353). Lactate-adjusted NGAL level, a combination of these two predictors, was calculated as the sum of each value multiplied by the odds ratio for EAD or AKI. We evaluated whether this combined predictor at the end of surgery is significantly associated with both postoperative AKI or EAD. We compared the area under the receiver operating characteristic curve (AUC) between our multivariable regression models with and without NGAL, lactate, or lactate-adjusted NGAL. NGAL, lactate and lactate-adjusted NGAL are significant predictors for EAD and AKI. The regression model for EAD or AKI including lactate-adjusted NGAL showed a greater AUC (for EAD: odds ratio [OR] 0.88, 95% confidence interval [CI] 0.84–0.91; for AKI: OR 0.89, 95% CI 0.85–0.92) compared to the AUC of the models including lactate (for EAD: OR 0.84, 95% CI 0.81–0.88; for AKI: OR 0.79, 95% CI 0.74–0.83) or NGAL alone (for EAD: OR 0.82, 95% CI 0.77–0.86; for AKI: OR 0.84, 95% CI 0.80–0.88) or the model without lactate or NGAL (for EAD: OR 0.64, 95% CI 0.58–0.69, for AKI: OR 0.75, 95% CI 0.70–0.79). In conclusion, lactate-adjusted NGAL level at the end of surgery could be a reliable combined laboratory predictor for postoperative EAD or AKI after liver transplantation with a greater discriminative ability than lactate or NGAL alone.

Abstract Continuous, comfortable, convenient (C3), and accurate blood pressure (BP) measurement and monitoring are needed for early diagnosis of various cardiovascular diseases. To supplement the limited C3 BP measurement of existing cuff-based BP technologies, though they may achieve reliable accuracy, cuffless BP measurement technologies, such as pulse transit/arrival time, pulse wave analysis, and image processing, have been studied to obtain C3 BP measurement. One of the recent cuffless BP measurement technologies, innovative machine-learning and artificial intelligence-based technologies that can estimate BP by extracting BP-related features from photoplethysmography (PPG)-based waveforms have attracted interdisciplinary attention of the medical and computer scientists owing to their handiness and effectiveness for both C3 and accurate, i.e., C3A, BP measurement. However, C3A BP measurement remains still unattainable because the accuracy of the existing PPG-based BP methods was not sufficiently justified for subject-independent and highly varying BP, which is a typical case in practice. To circumvent this issue, a novel convolutional neural network(CNN)- and calibration-based model (PPG2BP-Net) was designed by using a comparative paired one-dimensional CNN structure to estimate highly varying intrasubject BP. To this end, approximately $$70\%$$ 70 % , $$20\%$$ 20 % , and $$10\%$$ 10 % of 4185 cleaned, independent subjects from 25,779 surgical cases were used for training, validating, and testing the proposed PPG2BP-Net, respectively and exclusively (i.e., subject-independent modelling). For quantifying the intrasubject BP variation from an initial calibration BP, a novel ‘standard deviation of subject-calibration centring (SDS)’ metric is proposed wherein high SDS represents high intrasubject BP variation from the calibration BP and vice versa. PPG2BP-Net achieved accurately estimated systolic and diastolic BP values despite high intrasubject variability. In 629-subject data acquired after 20 minutes following the A-line (arterial line) insertion, low error mean and standard deviation of $$0.209\pm 7.509$$ 0.209 ± 7.509 and $$0.150\pm 4.549\;\textrm{mmHg}$$ 0.150 ± 4.549 mmHg for highly varying A-line systolic and diastolic BP values, respectively, where their SDSs are 15.375 and 8.745. This study moves one step forward in developing the C3A cuffless BP estimation devices that enable the push and agile pull services.

Abstract R-peak detection is an essential step in analyzing electrocardiograms (ECGs). Previous deep learning models reported their performance primarily in a single database, and some models did not perform at the highest levels when applied to a database different from the testing database. To achieve high performances in cross-database validations, we developed a novel deep learning model for R-peak detection using stationary wavelet transform (SWT) and separable convolution. Three databases (i.e., the MIT-BIH Arrhythmia [MIT-BIH], the Institute of Cardiological Technics [INCART], and the QT) were used in both the training and testing models, and the MIT-BIH ST Change (MIT-BIH-ST), European ST-T, TELE and MIT-BIH Noise Stress Test (MIT-BIH-NST) databases were further used for testing. The detail coefficient of level 4 decomposition by SWT and the first derivative from filtered ECGs were used for model inputs, and the interval of 150 ms centered at marked peaks was used for labels. Separable convolution with atrous spatial pyramidal pooling was selected as the model’s architecture, and noise-augmented waveforms of 5.69 s duration (2048 size in 360 Hz) were used in training. The model performance was evaluated using cross-database validation. The F1 scores of the peak detection model were 0.9994, 0.9985, and 0.9999 in the MIT-BIH, INCART, and QT databases, respectively. When the above three databases were pooled, the F1 scores were 0.9993 for fivefold cross-validation and 0.9991 for cross-database validation. The model performance remained high for MIT-BIH-ST, European ST-T, and TELE, with F1 scores of 0.9995, 0.9988, and 0.9790, respectively. The model performance when trained by severe noise augmentation increased for the MIT-BIH-NST database (F1 scores from 0.9504 to 0.9759) and decreased for the MIT-BIH database (F1 scores from 0.9994 to 0.9991). The present SWT and separable convolution-based model for R-peak detection yields a high performance even for cross-database validations.

Background Post-reperfusion syndrome (PRS) results in sudden hemodynamic instability following graft reperfusion. Although PRS is known to influence outcomes following liver transplantation, little is known regarding the effects of anesthetics on PRS. This study investigated the association between the type of anesthetic agent and PRS in liver transplantation. Methods This single-center retrospective cohort study included patients who underwent liver transplantation between June 2016 and December 2019. Patients were divided into sevoflurane and propofol groups according to the anesthetic agent used. Stabilized inverse probability of treatment weighting (IPTW) analysis was performed to investigate the association between PRS identified based on blood pressure recordings and the type of anesthesia. Associations between the anesthetic agent and the duration of hypotension as well as early postoperative outcomes were also investigated. Results Data were analyzed for 398 patients, 304 (76.4%) and 94 (23.6%) of whom were anesthetized with propofol and sevoflurane, respectively. PRS developed in 40.7% of the 398 patients. Following stabilized IPTW analysis, the association with PRS was lower in the sevoflurane group than in the propofol group (odds ratio, 0.47; P = 0.018). However, there was no association between the type of anesthetic used and early postoperative outcomes. Conclusions The association of PRS was lower in the sevoflurane group than in the propofol group. However, there was no association between the type of anesthetic and the early postoperative outcomes. Further studies are required to determine the optimal anesthetic for liver transplantation.

Measurement(s) vital signs of patients during surgery • perioperative patient information Technology Type(s) Vital Signs Measurement • Electronic Medical Record Factor Type(s) vital signs data including various numeric and waveform data acquired from multiple patient monitors • perioperative patient information acquired from the electronic medical record system Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment hospital Sample Characteristic - Location South Korea

Recent advancements in artificial intelligence (AI) techniques have enabled the development of accurate prediction models using clinical big data. AI models for perioperative risk stratification, intraoperative event prediction, biosignal analyses, and intensive care medicine have been developed in the field of perioperative medicine. Some of these models have been validated using external datasets and randomized controlled trials. Once these models are implemented in electronic health record systems or software medical devices, they could help anesthesiologists improve clinical outcomes by accurately predicting complications and suggesting optimal treatment strategies in real-time. This review provides an overview of the AI techniques used in perioperative medicine and a summary of the studies that have been published using these techniques. Understanding these techniques will aid in their appropriate application in clinical practice.

Background Appropriate monitoring of intradialytic biosignals is essential to minimize adverse outcomes because intradialytic hypotension and arrhythmia are associated with cardiovascular risk in hemodialysis patients. However, a continuous monitoring system for intradialytic biosignals has not yet been developed. Methods This study investigated a cloud system that hosted a prospective, open-source registry to monitor and collect intradialytic biosignals, which was named the CONTINUAL (Continuous mOnitoriNg viTal sIgN dUring hemodiALysis) registry. This registry was based on real-time multimodal data acquisition, such as blood pressure, heart rate, electrocardiogram, and photoplethysmogram results. Results We analyzed session information from this system for the initial 8 months, including data for some cases with hemodynamic complications such as intradialytic hypotension and arrhythmia. Conclusion This biosignal registry provides valuable data that can be applied to conduct epidemiological surveys on hemodynamic complications during hemodialysis and develop artificial intelligence models that predict biosignal changes which can improve patient outcomes.

Background Reducing the duration of intraoperative hypoxemia in pediatric patients by means of rapid detection and early intervention is considered crucial by clinicians. We aimed to develop and validate a machine learning model that can predict intraoperative hypoxemia events 1 min ahead in children undergoing general anesthesia. Methods This retrospective study used prospectively collected intraoperative vital signs and parameters from the anesthesia ventilator machine extracted every 2 s in pediatric patients undergoing surgery under general anesthesia between January 2019 and October 2020 in a tertiary academic hospital. Intraoperative hypoxemia was defined as oxygen saturation Results In total, 1,540 (11.73%) patients with intraoperative hypoxemia out of 13,130 patients’ records with 2,367 episodes were included for developing the model dataset. After model development, 200 (13.25%) of the 1,510 patients’ records with 289 episodes were used for holdout validation. Among the models developed, the GBM had the highest AUROC of 0.904 (95% confidence interval [CI] 0.902 to 0.906), which was significantly higher than that of the LSTM (0.843, 95% CI 0.840 to 0.846 P < .001) and the transformer model (0.885, 95% CI, 0.882–0.887, P < .001). In holdout validation, GBM also demonstrated best performance with an AUROC of 0.939 (95% CI 0.936 to 0.941) which was better than LSTM (0.904, 95% CI 0.900 to 0.907, P < .001) and the transformer model (0.929, 95% CI 0.926 to 0.932, P < .001). Conclusions Machine learning models can be used to predict upcoming intraoperative hypoxemia in real-time based on the biosignals acquired by patient monitors, which can be useful for clinicians for prediction and proactive treatment of hypoxemia in an intraoperative setting.

Lac dye is a natural colorant derived mainly from the insect Kerria lacca (Kerr) and has been used in food and beverage as a red-coloring additive. Despite its increasing use for human consumption as an alternative for allergy-associated cochineal, its toxicity profile remained incomplete to sufficiently assess its safety for the intended use. In this study, we evaluated systemic and genetic toxicity by performing acute and subacute oral toxicity studies in Sprague–Dawley (SD) rats using highly purified lac dye (LD) formulated in water and a battery of genotoxicity tests, respectively. To assess antigenic potentials, we carried out an in vivo passive cutaneous anaphylaxis test. A single dose of LD did not cause mortality at 5000 mg/kg body weight (BW), setting oral LD50 of >5000 mg/kg BW in SD rats. In the 90-day study, transient salivation without accompanying histopathological lesions in the salivary glands in 200 and 500 mg/kg BW groups and red-purple pigmentation on the surface of femora and skulls in 500 mg/kg groups were observed as nonadverse effects associated with LD, and no adverse effect was detected in all of the parameters examined, establishing a 500 mg/kg BW as no-observed-adverse-effect-level (NOAEL). Furthermore, LD was not mutagenic nor clastogenic in the genotoxicity tests. When tested for antigenicity, LD did not induce anaphylactic skin responses as opposed to the positive reaction by ovalbumin, suggesting a lack of antigenicity. Taken together, these findings provide extended toxicity information on LD with direct evidence supporting the lack of antigenicity, providing essential guidance for its safe use in humans.

Abstract Background Citrus sunki Hort. ex Tanaka peel has been traditionally used as an ingredient in folk medicine due to its therapeutic effects on promotion of splenic health and diuresis as well as relief of gastrointestinal symptoms. Although a growing interest in health-promoting natural products and the development of highly concentrated products have facilitated consumption of C. sunki peel, its safety assessment has not been explored, posing a potential health risk. In this study, we carried out a series of systemic and genetic toxicity tests on fermented C. sunki peel extract (FCPE) to provide the essential information required for safe use in human. Methods We conducted acute and 90-day repeated oral toxicity studies in Sprague-Dawley rats to evaluate systemic toxicity, and three genotoxicity assays to measure bacterial mutation reversion, cellular chromosome aberration and in vivo micronucleus formation. Results Single oral administration of FCPE did not cause any clinical signs and lethality in all animals, establishing LD50 to be over 2000 mg/kg BW. Repeated administration of up to 2000 mg/kg BW FCPE for 90 days revealed no test substance-related toxicity as demonstrated in analysis of body weight gain, food/water intake, blood, serum biochemistry, organ weight and histopathology, collectively determining that the no-observable-adverse-effect-level of FCPE is over 2000 mg/kg BW. In addition, we detected no mutagenicity and clastogenicity in FCPE at 5000 μg/plate for the in vitro assays and 2000 mg/kg BW for the in vivo micronucleus test. Conclusion FCPE did not cause systemic and genetic toxicity in our model systems at the tested dose levels. These results suggest a guideline for safe consumption of C. sunki peel in human.

To develop deep learning models for predicting Interoperative hypotension (IOH) using waveforms from arterial blood pressure (ABP), electrocardiogram (ECG), and electroencephalogram (EEG), and to determine whether combination ABP with EEG or CG improves model performance. Data were retrieved from VitalDB, a public data repository of vital signs taken during surgeries in 10 operating rooms at Seoul National University Hospital from January 6, 2005, to March 1, 2014. Retrospective data from 14,140 adult patients undergoing non-cardiac surgery with general anaesthesia were used. The predictive performances of models trained with different combinations of waveforms were evaluated and compared at time points at 3, 5, 10, 15 minutes before the event. The performance was calculated by area under the receiver operating characteristic (AUROC), area under the precision-recall curve (AUPRC), sensitivity and specificity. The model performance was better in the model using both ABP and EEG waveforms than in all other models at all time points (3, 5, 10, and 15 minutes before an event) Using high-fidelity ABP and EEG waveforms, the model predicted IOH with a AUROC and AUPRC of 0.935 [0.932 to 0.938] and 0.882 [0.876 to 0.887] at 5 minutes before an IOH event. The output of both ABP and EEG was more calibrated than that using other combinations or ABP alone. The results demonstrate that a predictive deep neural network can be trained using ABP, ECG, and EEG waveforms, and the combination of ABP and EEG improves model performance and calibration.

Abstract Background The relationship between intraoperative low bispectral index (BIS) values and poor clinical outcomes has been controversial. Intraoperative hypotension is associated with postoperative complication. The purpose of this study was to investigate the influence of intraoperative low BIS values and hypotension on postoperative mortality in patients undergoing major abdominal surgery. Methods This retrospective study analyzed 1862 cases of general anesthesia. We collected the cumulative time of BIS values below 20 and 40 as well as electroencephalographic suppression and documented the incidences in which these states were maintained for at least 5 min. Durations of intraoperative mean arterial pressures (MAP) less than 50 mmHg were also recorded. Multivariable logistic regression was used to evaluate the association between suspected risk factors and postoperative mortality. Results Ninety-day mortality and 180-day mortality were 1.5 and 3.2% respectively. The cumulative time in minutes for BIS values falling below 40 coupled with MAP falling below 50 mmHg was associated with 90-day mortality (odds ratio, 1.26; 95% confidence interval, 1.04–1.53; P = .019). We found no association between BIS related values and 180-day mortality. Conclusions The cumulative duration of BIS values less than 40 concurrent with MAP less than 50 mmHg was associated with 90-day postoperative mortality, not 180-day postoperative mortality.

BackgroundArterial pressure-based cardiac output (APCO) is a less invasive method for estimating cardiac output without concerns about complications from the pulmonary artery catheter (PAC). However, inaccuracies of currently available APCO devices have been reported. Improvements to the algorithm by researchers are impossible, as only a subset of the algorithm has been released. ObjectiveIn this study, an open-source algorithm was developed and validated using a convolutional neural network and a transfer learning technique. MethodsA retrospective study was performed using data from a prospective cohort registry of intraoperative bio-signal data from a university hospital. The convolutional neural network model was trained using the arterial pressure waveform as input and the stroke volume (SV) value as the output. The model parameters were pretrained using the SV values from a commercial APCO device (Vigileo or EV1000 with the FloTrac algorithm) and adjusted with a transfer learning technique using SV values from the PAC. The performance of the model was evaluated using absolute error for the PAC on the testing dataset from separate periods. Finally, we compared the performance of the deep learning model and the FloTrac with the SV values from the PAC. ResultsA total of 2057 surgical cases (1958 training and 99 testing cases) were used in the registry. In the deep learning model, the absolute errors of SV were 14.5 (SD 13.4) mL (10.2 [SD 8.4] mL in cardiac surgery and 17.4 [SD 15.3] mL in liver transplantation). Compared with FloTrac, the absolute errors of the deep learning model were significantly smaller (16.5 [SD 15.4] and 18.3 [SD 15.1], P

Anesthesia with desflurane and remifentanil can be maintained with either fixed or titrated desflurane concentration. We hypothesized that the fixed-gas concentration (FG) method would reduce the number of anesthetic titrations without hypnotic and hemodynamic instability compared to the bispectral index (BIS)-guided (BG) method. Forty-eight patients were randomly allocated to the FG or BG groups. In the FG group, desflurane vaporizer setting was fixed at 1 age-corrected minimum alveolar concentration (MAC). In the BG group, desflurane was titrated to target a BIS level at 50. Remifentanil was titrated to maintain a systolic arterial pressure (SAP) of 120 mmHg in both groups. Our primary endpoint was the hypnotic stability measured by the wobble of BIS in performance analysis, and the secondary endpoints included the wobble of SAP, mean BIS value during surgery, and the number of anesthetic titrations. The BIS in the FG group showed significantly less wobble (3.9 ± 1.1% vs 5.5 ± 1.5%, P

Background and purpose — New oral anticoagulants have been developed to prevent venous thromboembolism (VTE) after knee or hip arthroplasty. Although there have been several network meta-analyses (NMA) to compare different regimens, an NMA including 2 different enoxaparin doses and edoxaban has not been performed. Methods — Standard NMA for fondaparinux, dabigatran, rivaroxaban, apixaban, edoxaban, and enoxaparin was performed. Outcome variables included a composite of total VTE and major/clinically relevant bleeding. The rank probabilities of each treatment outcome were summarized by the surface under the cumulative ranking curve. Results — Fondaparinux, rivaroxaban, and apixaban were associated with a reduced risk of VTE compared with enoxaparin, while dabigatran was not. None of these 3 drugs increased bleeding compared with enoxaparin 30 mg twice daily. However, fondaparinux and rivaroxaban increased bleeding compared with enoxaparin 40 mg once daily, while apixaban did not. Apixaban was even associated with decreased major/clinically relevant bleeding compared with enoxaparin 30 mg twice daily or 40 mg once daily. When edoxaban was included in the NMA, edoxaban decreased VTE and did not increase bleeding compared with enoxaparin. Interpretation — A higher efficacy of fondaparinux and rivaroxaban compared with enoxaparin was associated with increased bleeding tendency, while apixaban was superior to enoxaparin regarding both efficacy and safety. A clustered ranking plot showed that apixaban might be the most preferred regarding efficacy and safety. However, our results were driven by indirect statistical inference and were limited by the heterogeneity of the bleeding outcome definitions, drug initiation and continuation, and different surgery types.

For ABO-incompatible liver transplantation (ABO-i LT), therapeutic plasma exchange (TPE) is performed preoperatively to reduce the isoagglutinin titer of anti-ABO blood type antibodies. We evaluated whether perioperative high isoagglutinin titer is associated with postoperative risk of acute kidney injury (AKI). In 130 cases of ABO-i LT, we collected immunoglobulin (Ig) G and Ig M isoagglutinin titers of baseline, pre-LT, and postoperative peak values. These values were compared between the patients with and without postoperative AKI. Multivariable logistic regression analysis was used to evaluate the association between perioperative isoagglutinin titers and postoperative AKI. Clinical and graft-related outcomes were compared between high and low baseline and postoperative peak isoagglutinin groups. The incidence of AKI was 42.3%. Preoperative baseline and postoperative peak isoagglutinin titers of both Ig M and Ig G were significantly higher in the patients with AKI than those without AKI. Multivariable logistic regression analysis showed that preoperative baseline and postoperative peak Ig M isoagglutinin titers were significantly associated with the risk of AKI (baseline: odds ratio 1.06, 95% confidence interval 1.02 to 1.09; postoperative peak: odds ratio 1.08, 95% confidence interval 1.04 to 1.13). Cubic spline function curves show a positive relationship between the baseline and postoperative peak isoagglutinin titers and the risk of AKI. Clinical outcomes other than AKI were not significantly different according to the baseline and postoperative peak isoagglutinin titers. Preoperative high initial and postoperative peak Ig M isoagglutinin titers were significantly associated with the development of AKI. As the causal relationship between high isoagglutinin titers and risk of AKI is unclear, the high baseline and postoperative isoagglutinin titers could be used simply as a warning sign for the risk of AKI after liver transplantation.

Abstract Profound hypotension during liver transplantation is aggressively treated with vasopressors thus frequently unrevealed in a retrospective study. The relationship between concealed intraoperative hypotension and in-hospital mortality after liver transplantation was evaluated using performance measurement (PM) of systolic arterial pressure (SAP). Median performance error (MDPE), median absolute performance error (MDAPE), and wobble of SAP were calculated using preoperative SAP as the reference value, and prereperfusion and postreperfusion SAPs as measured values. Univariable and multivariable logistic regression analyses were performed using 6 PM parameters and 36 traditional SAP-derived parameters to predict in-hospital mortality. In-hospital mortality was 3.9% (22/569 cases). Prereperfusion MDAPE and postreperfusion wobble were the only significant SAP-derived predictors of in-hospital mortality. The area under receiver operating characteristic curve of prediction model was 0.769 (95% confidence interval 0.732–0.803, P

ABO-incompatible liver transplantation (ABO-i LT) is associated with a higher risk of acute kidney injury (AKI) compared to ABO-compatible liver transplantation (ABO-c LT). We compared the risk of AKI associated with transfusion between ABO-c and ABO-i living donor liver transplantation (LDLT). In 885 cases of LDLT, we used a propensity score analysis to match patients who underwent ABO-c (n = 766) and ABO-i (n = 119) LDLT. Baseline medical status, laboratory findings, and surgical- and anesthesia-related parameters were used as contributors for propensity score matching. AKI was defined according to the “Kidney Disease Improving Global Outcomes” criteria. After 1:2 propensity score matching, a conditional logistic regression analysis was performed to evaluate the relationship between the intraoperative transfusion of packed red blood cells (pRBCs) and fresh frozen plasma (FFP) on the risk of AKI. The incidence of AKI was higher in ABO-i LT than in ABO-c LT before and after matching (after matching, 65.8% in ABO-i vs 39.7% in ABO-c, p < 0.001). The incidence of AKI increased in direct proportion to the amount of transfusion, and this increase was more pronounced in ABO-i LT. The risk of pRBC transfusion for AKI was greater in ABO-i LT (multivariable adjusted odds ratio (OR) 1.32 per unit) than in ABO-c LT (OR 1.11 per unit). The risk of FFP transfusion was even greater in ABO-i LT (OR 1.44 per unit) than in ABO-c LT (OR 1.07 per unit). In conclusion, the association between transfusion and risk of AKI was stronger in patients with ABO-i LT than with ABO-c LT. Interventions to reduce perioperative transfusions may attenuate the risk of AKI in patients with ABO-i LT.

Objective Positive end-expiratory pressure (PEEP) causes carotid baroreceptor unloading, which leads to thermoregulatory peripheral vasoconstriction. However, the effects of PEEP on intraoperative thermoregulation in the prone position remain unknown. Methods Thirty-seven patients undergoing spine surgery in the prone position were assigned at random to receive either 10 cmH 2 O PEEP (Group P) or no PEEP (Group Z). The primary endpoint was core temperature 180 minutes after intubation. Secondary endpoints were delta core temperature (difference in core temperature between 180 minutes and immediately after tracheal intubation), incidence of intraoperative hypothermia (core temperature of

The widespread use of remifentanil during total intravenous anesthesia (TIVA) has raised concerns about the risk of postoperative remifentanil-associated pain. Although a recent meta-analysis suggests that remifentanil-associated pain is unlikely to occur in patients with TIVA because of the protective effect of co-administered propofol, the evidence is not conclusive. We retrospectively assessed 635 patients who received robotic thyroid surgery under TIVA to evaluate the risk of remifentanil-associated pain. Postoperative pain was evaluated using 11-point numeric rating scale (NRS). Time dependent Cox proportional hazards regression analysis was used to determine the risk factors of treatment-requiring pain (NRS > 4) during the first 48 postoperative hours. Postoperative pain rapidly decreased, and treatment-requiring pain remained in 12.8% (81 out of 635) of patients at 48 hours postoperatively. After adjusting for the time-dependent analgesic consumption, intraoperative use of remifentanil > 0.2 mcg/kg/min was a positive predictor of postoperative pain with a hazard ratio of 1.296 (95% C.I., 1.014-1.656, P = 0.039) during 48 hours after surgery. In conclusion, excessive use of remifentanil during TIVA was associated with increased risk of pain after robotic thyroid surgery. Prospective trials are required to confirm these results and determine whether decreasing remifentanil consumption below the threshold can reduce postoperative pain.

Objective To investigate the effect-site concentration of remifentanil required to blunt haemodynamic responses during tracheal intubation with a single-lumen tube (SLT) or a double-lumen tube (DLT). Methods Patients scheduled for thoracic surgery requiring one-lung ventilation were randomly allocated to either the SLT or DLT group. All patients received a target-controlled infusion of propofol and a predetermined concentration of remifentanil. Haemodynamic parameters during intubation were recorded. The effect-site concentration of remifentanil was determined using a delayed up-and-down sequential allocation method. Results A total of 92 patients were enrolled in the study. The effective effect-site concentrations of remifentanil required to blunt haemodynamic responses in 50% of patients (EC 50 ) estimated by isotonic regression with bootstrapping was higher in the DLT than the SLT group (8.5 ng/ml [95% confidence interval (CI) 8.0–9.5 ng/ml] versus 6.5 ng/ml [95% CI 5.6–6.7 ng/ml], respectively). Similarly, the effective effect-site concentrations of remifentanil in 95% of patients in the DLT group was higher than the SLT group (9.9 ng/ml [95% CI 9.8–10.0 ng/ml] versus 7.0 ng/ml [95% CI 6.9–7.0 ng/ml], respectively). Conclusions This study demonstrated that a DLT requires a 30% higher EC 50 of remifentanil than does an SLT to blunt haemodynamic responses during tracheal intubation when combined with a target-controlled infusion of propofol. Trial registration Clinicaltrials.gov identifier: NCT01542099.

The benefit of aspirin use after coronary artery bypass graft surgery has been well proven. However, the effect of preoperative aspirin use in patients undergoing off-pump coronary artery bypass graft surgery (OPCAB) has not been evaluated sufficiently. To evaluate platelet function changes during OPCAB due to preoperative aspirin use, we conducted a randomized controlled trial using flow cytometry and the Multiplate® analyzer. Forty-eight patients scheduled for elective OPCAB were randomized to the aspirin continuation (100 mg/day until operative day) and discontinuation (4 days before the operative day) groups. Platelet function was measured using the platelet activation markers CD62P, CD63, and PAC-1 by flow cytometry, and platelet aggregation was measured using the Multiplate® analyzer, after the induction of anesthesia (baseline), at the end of the operation, and 24 and 48 h postoperatively. Findings of conventional coagulation assays, thromboelastography by ROTEM® assays, and postoperative bleeding-related clinical outcomes were compared between groups. No significant change in CD62P, CD63, or PAC-1 was observed at the end of the operation or 24 or 48 h postoperatively compared with baseline in either group. The area under the curve for arachidonic acid-stimulated platelet aggregation, measured by the Multiplate® analyzer, was significantly smaller in the aspirin continuation group (P < 0.01). However, chest tube drainage and intraoperative and postoperative transfusion requirements did not differ between groups. Our study showed that preoperative use of aspirin for OPCAB did not affect perioperative platelet activation, but it impaired platelet aggregation, which did not affect postoperative bleeding, by arachidonic acid.

The discrepancy between spatial orientations of an endoscopic image and a physician's working environment can make it difficult to interpret endoscopic images. In this study, we developed and evaluated a device that corrects the endoscopic image orientation using an accelerometer and gyrosensor. The acceleration of gravity and angular velocity were retrieved from the accelerometer and gyrosensor attached to the handle of the endoscope. The rotational angle of the endoscope handle was calculated using a Kalman filter with transmission delay compensation. Technical evaluation of the orientation correction system was performed using a camera by comparing the optical rotational angle from the captured image with the rotational angle calculated from the sensor outputs. For the clinical utility test, fifteen anesthesiology residents performed a video endoscopic examination of an airway model with and without using the orientation correction system. The participants reported numbers written on papers placed at the left main, right main, and right upper bronchi of the airway model. The correctness and the total time it took participants to report the numbers were recorded. During the technical evaluation, errors in the calculated rotational angle were less than 5 degrees. In the clinical utility test, there was a significant time reduction when using the orientation correction system compared with not using the system (median, 52 vs. 76 seconds; P = .012). In this study, we developed a real-time endoscopic image orientation correction system, which significantly improved physician performance during a video endoscopic exam.

Prolonged air leak (PAL), defined as air leak more than 5 days after lung resection, has been associated with various adverse outcomes. However, studies on intraoperative risk factors for PAL are not sufficient. We investigated whether the intraoperative ventilatory leak (VL) can predict PAL. A retrospective study of 1060 patients with chest tubes after lung resection was conducted. Tidal volume data were retrieved from the electronic anesthesia records. Ventilatory leak (%) was calculated as [(inspiratory tidal volume-expiratory tidal volume)/ inspiratory tidal volume × 100] and was measured after restart of two-lung ventilation. Cox proportional hazards regression analysis was performed using VL as a predictor, and PAL as the dependent outcome. The odds ratio of the VL was then adjusted by adding possible risk factors including patient characteristics, pulmonary function and surgical factors. The incidence of PAL was 18.7%. VL >9.5% was a significant predictor of PAL in univariable analysis. VL remained significant as a predictor of PAL (1.59, 95% CI, 1.37-1.85, P 60 years, body mass index 2.1 hours. C-statistic of the prediction model was 0.80 (95% CI, 0.77-0.82). In conclusion, VL was a quantitative measure of intraoperative air leakage and an independent predictor of postoperative PAL. Monitoring VL during lung resection may be uselful in recommending additional surgical repair or use of adjuncts and thus, help reduce postoperative PAL.

Acute kidney injury (AKI) after liver transplantation has been reported to be associated with increased mortality. Recently, machine learning approaches were reported to have better predictive ability than the classic statistical analysis. We compared the performance of machine learning approaches with that of logistic regression analysis to predict AKI after liver transplantation. We reviewed 1211 patients and preoperative and intraoperative anesthesia and surgery-related variables were obtained. The primary outcome was postoperative AKI defined by acute kidney injury network criteria. The following machine learning techniques were used: decision tree, random forest, gradient boosting machine, support vector machine, naïve Bayes, multilayer perceptron, and deep belief networks. These techniques were compared with logistic regression analysis regarding the area under the receiver-operating characteristic curve (AUROC). AKI developed in 365 patients (30.1%). The performance in terms of AUROC was best in gradient boosting machine among all analyses to predict AKI of all stages (0.90, 95% confidence interval [CI] 0.86–0.93) or stage 2 or 3 AKI. The AUROC of logistic regression analysis was 0.61 (95% CI 0.56–0.66). Decision tree and random forest techniques showed moderate performance (AUROC 0.86 and 0.85, respectively). The AUROC of support the vector machine, naïve Bayes, neural network, and deep belief network was smaller than that of the other models. In our comparison of seven machine learning approaches with logistic regression analysis, the gradient boosting machine showed the best performance with the highest AUROC. An internet-based risk estimator was developed based on our model of gradient boosting. However, prospective studies are required to validate our results.

BackgroundPatients showed a different response following intravenous midazolam injection. Some children showed irritability or were not sedated by midazolam. We hypothesized that there may be genetic variations of the MDR1 gene, based on the response to midazolam.MethodsOne hundred and ninety-three pediatric patients were recruited in this study. Midazolam (0.1 mg/kg) was injected intravenously before surgery. Anxiety score (activity, vocalizations, emotional expressivity, state of apparent arousal) was checked before and 5 minutes after midazolam injection. In addition, other manifestations after midazolam injection were recorded. After anesthesia, 2 ml of blood was sampled. Children were genotyped MDR1. Haplotype was analyzed using the software package PHASE, version 2.0.ResultsThe observed frequencies of MDR1 haplotype of TTT, TGC, CAC, CGC were 0.334, 0.205, 0.182 and 0.225, respectively. There was no significant correlation between the response of midazolam and the MDR1 haplotype of TTT, TGC, CAC or CGC (P = 0.98).ConclusionsGenotyping of MDR1 may not be related to the response of midazolam in children.

BackgroundStraight raising of the legs in the supine position or Trendelenburg positioning has been used to treat hypotension or shock, but the advantages of these positions are not clear and under debate. We performed a crossover study to evaluate the circulatory effect of full flexion of the hips and knees in the supine position (exaggerated lithotomy), and compare it with straight leg raising.MethodsThis study was a prospective randomized crossover study from the tertiary care unit at our university hospital. Twenty-two patients scheduled for off-pump coronary artery bypass surgery were enrolled. Induction and maintenance of anesthesia were standardized. Exaggerated lithotomy position or straight leg raising were randomly selected in the supine position. Hemodynamic variables were measured in the following sequence: 10 min after induction, 1, 5, and 10 min following the designated position, and 1 and 5 min after returning to the supine position. Ten min later, the other position was applied to measure the same hemodynamic variables.ResultsDuring the exaggerated lithotomy position, cerebral and coronary perfusion pressure increased significantly (P < 0.01) without a change in cardiac output. During straight leg raising, cardiac output increased at 5 min (P < 0.05) and cerebral and coronary perfusion pressures did not increase except for cerebral perfusion pressure at 1 min. However, the difference between the two groups at each time point in terms of cerebral perfusion pressure was clinically insignificant.ConclusionsFull flexion of the hips and knees in the supine position did not increase cardiac output but may be more beneficial than straight leg raising in terms of coronary perfusion pressure.

BackgroundAnesthesia induction with desflurane is troublesome because of the frequent sympathetic hyperactivity during desflurane administration. We thought that a low concentration of desflurane combined with a target-controlled infusion (TCI) of remifentanil would eliminate the desflurane-related complications and provide hemodynamic stability during desflurane induction. An up-and-down study was planned to find the target effect-site concentration of remifentanil to block the hemodynamic response to endotracheal intubation, the highest level of stimulus, during anesthesia induction with administering desflurane at 1 MAC.MethodsRemifentanil TCI was initiated before desflurane administration. When the preset target was achieved, spontaneous inhalation of desflurane 1 MAC was performed until the patients became unconscious. Laryngoscopic tracheal intubation was facilitated with rocuronium injection. The starting concentration of remifentanil and the test space were 5 and 1 ng/ml, respectively. The criteria for up-and-down was a 20% increase of the mean arterial pressure or heart rate after intubation. The median effective concentration (EC50) of remifentanil was calculated from 6 independent pairs. The complications related with remifentanil and desflurane were assessed during the study.ResultsWe studied 20 patients using 2-5 ng/ml of the effect-site concentrations of remifentanil. The EC50 of remifentanil was 3.7 ng/ml. Loss of consciousness was achieved at 125 ± 22 s after desflurane inhalation and this was irrespective of the combined remifentanil concentrations. Any remifentanil-related complication was not observed. Transient cough was seen in one patient who received 2 ng/ml of remifentanil.ConclusionsWe demonstrated that uncomplicated induction with desflurane was possible by the use of target-controlled remifentanil. The EC50 of remifentanil to block the hemodynamic response to tracheal intubation was 3.7 ng/ml during inhalational induction with 1 MAC desflurane.

Background: Post-reperfusion syndrome (PRS) results in sudden hemodynamic instability following graft reperfusion. Although PRS is known to influence outcomes following liver transplantation, little is known regarding the effects of anesthetics on PRS. This study investigated the association between the type of anesthetic agent and PRS in liver transplantation. Methods: This single-center retrospective cohort study included patients who underwent liver transplantation between June 2016 and December 2019. Patients were divided into sevoflurane and propofol groups according to the anesthetic agent used. Stabilized inverse probability of treatment weighting (IPTW) analysis was performed to investigate the association between PRS identified based on blood pressure recordings and the type of anesthesia. Associations between the anesthetic agent and the duration of hypotension as well as early postoperative outcomes were also investigated. Results: Data were analyzed for 398 patients, 304 (76.4%) and 94 (23.6%) of whom were anesthetized with propofol and sevoflurane, respectively. PRS developed in 40.7% of the 398 patients. Following stabilized IPTW analysis, the association with PRS was lower in the sevoflurane group than in the propofol group (odds ratio, 0.47; P = 0.018). However, there was no association between the type of anesthetic used and early postoperative outcomes. Conclusions: The association of PRS was lower in the sevoflurane group than in the propofol group. However, there was no association between the type of anesthetic and the early postoperative outcomes. Further studies are required to determine the optimal anesthetic for liver transplantation. [ABSTRACT FROM AUTHOR]