Effects of Remote Ischemic Conditioning on Flap Oxygenation in Patients Undergoing Head and Neck Reconstruction and Preoperative Radiotherapy: A Randomized Clinical Trial.

Background: Preoperative radiotherapy and ischemia/reperfusion (I/R) injury during free tissue transfer may impair tissue oxygenation and increase flap complications. Ischemic conditioning, which involves brief cycles of ischemia and reperfusion, mitigates I/R-induced tissue damage. It has demonstrated organ-protective effects in various clinical settings.

Effects of preoperative binaural beats on the propofol dose for induction of general anesthesia: a randomized controlled trial.

Purpose: Brainwave entrainment with low-frequency binaural beats has shown sedative-sparing and anxiolytic effects. We sought to investigate whether the preoperative use of binaural beats could reduce the propofol dose for the induction of general anesthesia.

Methods: We enrolled patients scheduled for elective surgery under general anesthesia in a randomized controlled trial.

Electroencephalography and Anesthetic Depth in Children Under 2 Years of Age: A Prospective Observational Study.

Background: Processed electroencephalogram (EEG) indices are widely used to monitor anesthetic depth. However, their reliability in children under 2 years of age remains questionable. During anesthesia maintenance in this age group, processed EEG indices frequently exhibit unexpectedly elevated values that exceed the intended target range.

Comparison of NLP machine learning models with human physicians for ASA Physical Status classification.

The American Society of Anesthesiologist's Physical Status (ASA-PS) classification system assesses comorbidities before sedation and analgesia, but inconsistencies among raters have hindered its objective use. This study aimed to develop natural language processing (NLP) models to classify ASA-PS using pre-anesthesia evaluation summaries, comparing their performance to human physicians. Data from 717,389 surgical cases in a tertiary hospital (October 2004-May 2023) was split into training, tuning, and test datasets.

Machine-learning model to predict the tacrolimus concentration and suggest optimal dose in liver transplantation recipients: a multicenter retrospective cohort study.

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.

Hydrogel with Immobilized Mn-Porphyrin for Reactive Oxygen Species Scavenging, Oxygen Generation, and Risedronate Delivery in Bone Defect Treatment.

We propose a hydrogel immobilized with manganese porphyrin (MnP), a biomimetic superoxide dismutase (SOD), and catalase (CAT) to modulate reactive oxygen species (ROS) and hypoxia that impede the repair of large bone defects. Our hydrogel synthesis involved thiolated chitosan and polyethylene glycol-maleimide conjugated with MnPs (MnP-PEG-MAL), which enabled gelation via a click reaction. Through optimization, a hydrogel with mechanical properties and catalytic effects favorable for bone repair was selected.

Fe-Porphyrin Cross-Linked Hydrogel for Reactive Oxygen Species Scavenging and Oxygen Generation in Diabetic Wounds.

Healing chronic diabetic wounds is challenging because of excessive reactive oxygen species (ROS) and hypoxia in the wound microenvironment. To address this issue, we propose a hydrogel wound dressing composed of polyethylene glycol (PEG) cross-linked with a biomimetic catalase, Fe-containing porphyrin (FeP) (i.e.

Effect of hyperbilirubinemia on the accuracy of continuous non-invasive hemoglobin measurements in liver transplantation recipients.

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 (< 1.

Real-time machine learning model to predict in-hospital cardiac arrest using heart rate variability in ICU.

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.

Continuous cardiac output estimation using a new modified Fick method during off-pump coronary artery bypass graft surgery: a retrospective observational study.

Purpose: Several technical aspects of the Fick method limit its use intraoperatively. A data-driven modification of the Fick method may enable its use in intraoperative settings.

Methods: This two-center retrospective observational study included 57 (28 and 29 in each center) patients who underwent off-pump coronary artery bypass graft (OPCAB) surgery.

Microneedles coated with composites of phenylboronic acid-containing polymer and carbon nanotubes for glucose measurements in interstitial fluids.

A microneedle (MN) sensor coated with a sensing composite material was proposed for measuring glucose concentrations in interstitial fluid (ISF). The sensing composite material was prepared by blending a polymer containing glucose-responsive phenylboronic acid (PBA) moieties (i.e.

VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients.

In modern anesthesia, multiple medical devices are used simultaneously to comprehensively monitor real-time vital signs to optimize patient care and improve surgical outcomes. However, interpreting the dynamic changes of time-series biosignals and their correlations is a difficult task even for experienced anesthesiologists. Recent advanced machine learning technologies have shown promising results in biosignal analysis, however, research and development in this area is relatively slow due to the lack of biosignal datasets for machine learning.

Perioperative hemodynamic instability in pheochromocytoma and sympathetic paraganglioma patients.

For pheochromocytoma and sympathetic paraganglioma (PPGL), surgery can be used as a curative treatment; however, the life-threatening risk of perioperative hemodynamic instability (HI) presents challenges. This study aimed to analyze the incidence and predictive factors of perioperative HI. The electronic medical records of 114 consecutive patients who underwent surgery for PPGLs at our institution were retrospectively reviewed.

Comparison of bispectral index-guided and fixed-gas concentration techniques in desflurane and remifentanil anesthesia: A randomized controlled trial.

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.

Effects of prone positioning with neck extension on intracranial pressure according to optic nerve sheath diameter measured using ultrasound in children.

Purpose: Optic nerve sheath diameter has been used for measure of intracranial pressure. The aim of this study was to evaluate the effect of prone positioning with neck extension on intracranial pressure in infants undergoing craniosynostosis surgery and to determine precautions using optic nerve sheath diameter measurement.

Methods: We enrolled 30 infants who were scheduled for correction of craniosynostosis in which planning included the prone position with neck extension.

Data Driven Investigation of Bispectral Index Algorithm.

Bispectral index (BIS), a useful marker of anaesthetic depth, is calculated by a statistical multivariate model using nonlinear functions of electroencephalography-based subparameters. However, only a portion of the proprietary algorithm has been identified. We investigated the BIS algorithm using clinical big data and machine learning techniques.

Excessive remifentanil during total intravenous anesthesia is associated with increased risk of pain after robotic thyroid surgery.

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.

Prediction of Acute Kidney Injury after Liver Transplantation: Machine Learning Approaches vs. Logistic Regression Model.

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.