Daily Anesthesiology Research Analysis

INTRODUCTION: Electroconvulsive therapy (ECT) is an established and effective treatment for patients with medication-resistant psychiatric disorders. However, the optimal choice of anesthetic agent for ECT induction remains a subject of ongoing debate. Remimazolam, a novel ultra-short-acting benzodiazepine, has yet to be systematically evaluated in the context of ECT anesthesia. METHOD: We conducted a prospective, double-blind, randomized, crossover trial in hospitalized patients scheduled for ECT. Participants were randomly assigned to different treatment sequences, receiving either remimazolam (0.2 mg/kg) or propofol (2 mg/kg) for anesthesia induction in a crossover manner. The primary outcome was EEG seizure duration. Secondary outcomes included seizure adequacy endpoint, anesthesia-related parameters and safety profiles. All analyses were performed using generalized linear mixed-effects models, with treatment condition, stimulus dose, and treatment sequence as fixed effects and participant-specific random intercepts. RESULTS: A total of 284 ECT sessions from 56 patients were included in the analysis. The remimazolam group demonstrated significantly longer EEG seizure duration (37.0 s vs. 18.5 s; p < 0.001) and EMG seizure duration (15.0 s vs. 9.0 s, p < 0.001), higher average seizure energy index (24,767.4 µV CONCLUSION: Remimazolam is an effective anesthetic induction agent for ECT, offering superior seizure quality metrics compared to propofol. However, clinicians should remain vigilant regarding the potential for post-ictal cardiovascular hyperdynamic states. TRIAL REGISTRATION: Chinese Clinical Trial Registry (number: ChiCTR2500114332; date: December 10, 2025).

INTRODUCTION: Preclinical and retrospective data indicated that albumin therapy may be associated with endothelial protection and lower net fluid balance in sepsis. However, endothelial protective effect of albumin has never been evaluated in a clinical trial. We therefore hypothesized that an infective, inflammatory condition like perforation peritonitis, which requires substantial fluid replacement, may benefit from albumin therapy. METHODS: Adult patients undergoing emergent/urgent abdominal surgery for perforation peritonitis were randomized to either group A or group P receiving 5% human albumin or Plasma-Lyte fluid therapy, respectively. Serum endothelial glycocalyx degradation products (syndecan-1, heparan sulfate) and inflammatory biomarkers (TNF-a, interleukins [IL]-1b, IL-10, and IL-6) were measured at the baseline, 6 h, and 24 h postoperatively. RESULTS: In this study, n = 50 patients were randomized, and complete outcome data for n = 48 patients were available. Median (interquartile range) values of syndecan-1, heparan sulfate, TNF-a, IL-1b, IL-6, and IL- 10 were statistically similar at all time points. Repeated measured two-way ANOVA reported a significant interaction in heparan sulfate (F [2, 88] = 3.60, P = 0.026), TNF-a (F [2, 88] = 3.75, P = 0.027), and IL-10 (F [2, 88] = 4.84, P = 0.02) between the time point of measurement and type of fluid therapy. Intraoperative vasopressor requirement was lower with albumin [P = 0.047]. CONCLUSIONS: Although 5% albumin-based fluid therapy failed to reduce syndecan-1 level, as compared to Plasma-Lyte, it possibly resulted in better perioperative hemodynamic stability and lesser fluid administration. This finding should be considered as 'hypothesis-generating' and need further validation.

BACKGROUND: Cardiac surgery is associated with significant mortality and complication risks. This study aims to develop an interpretable machine learning (ML) model to predict adverse outcomes (AOs) after cardiac surgery, and to explore the associations between relevant characteristics and predicted outcomes. METHODS: Patients who underwent cardiopulmonary bypass (CPB) cardiac surgery between January 2013 and December 2022 at a tertiary hospital were included. Perioperative data were collected, and a predictive model was constructed using the light gradient boosting machine (LightGBM) algorithm. To assess whether incorporating intraoperative and early postoperative data could improve risk prediction at the time of intensive care unit (ICU) admission, we compared the performance of this model with that of the preoperative European system for cardiac operative risk evaluation (EuroSCORE). The EuroSCORE was used as a baseline preoperative risk assessment tool, while the LightGBM model aimed to provide an updated risk estimate upon ICU admission. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC) on a validation dataset. Additionally, counterfactual explanations (CE), an explainable artificial intelligence technique, were employed to enhance the model's applicability and credibility in real-world clinical settings. RESULTS: A total of 3,270 patients who underwent cardiac surgery under CPB were included in this study, of which 203 experienced AOs postoperatively. The LightGBM model built on perioperative data demonstrated good predictive performance (AUROC = 0.807), outperforming the traditional EuroSCORE assessment system (AUROC = 0.722). The application of the CE method to the ML model indicated that characteristics such as initial B-type natriuretic peptide (BNP) levels upon intensive care unit (ICU) admission, aortic cross-clamp time, CPB duration, initial urea levels upon ICU admission, and operation duration were key predictors of postoperative AOs. CONCLUSION: The ML model shows potential in improving risk assessment for AOs after cardiac surgery in patients. The application of CE provides the model with more detailed and practical interpretability, enhancing the credibility of its predictions and promoting transparency and personalization in the clinical decision-making process.