Daily Anesthesiology Research Analysis
Today's top anesthesiology-relevant studies span perioperative hemostasis, ICU physiological monitoring, and AI-driven neurocognitive risk prediction. A translational Critical Care study introduces creatinine production rate as an integrative indicator of skeletal muscle status linked to one-year survival, a JAMA Surgery analysis confirms tranexamic acid reduces bleeding without excess vascular risk in general surgery, and an explainable machine-learning model predicts perioperative neurocogniti
Summary
Today's top anesthesiology-relevant studies span perioperative hemostasis, ICU physiological monitoring, and AI-driven neurocognitive risk prediction. A translational Critical Care study introduces creatinine production rate as an integrative indicator of skeletal muscle status linked to one-year survival, a JAMA Surgery analysis confirms tranexamic acid reduces bleeding without excess vascular risk in general surgery, and an explainable machine-learning model predicts perioperative neurocognitive dysfunction after liver transplantation with external validation.
Research Themes
- Perioperative hemostasis and bleeding risk mitigation
- Integrative ICU monitoring of muscle status and outcomes
- Explainable AI for neurocognitive risk stratification in transplant anesthesia
Selected Articles
1. Creatinine production rate is an integrative indicator to monitor muscle status in critically ill patients.
Across animal and clinical studies (n=629 ICU patients), creatinine production rate (CPR) reflected both skeletal muscle quantity and quality, decreased with systemic inflammation, correlated with muscle cross-sectional area, and lower baseline CPR index independently predicted one-year mortality. CPR trajectories were multifactorial and not uniformly declining, indicating sensitivity to metabolic derangements beyond muscle loss.
Impact: Introduces a practical, repeatable indicator linking muscle biology to outcomes, with both mechanistic and clinical validation, addressing a major monitoring gap in critical care and perioperative medicine.
Clinical Implications: CPR could be incorporated into ICU workflows to risk-stratify patients, track anabolic/catabolic states, and guide nutrition and rehabilitation strategies beyond traditional creatinine-based assessments.
Key Findings
- In animals, CPR depended on muscle volume, creatine content, and metabolic status; systemic inflammation reduced CPR.
- In 629 ICU patients, admission CPR index strongly correlated with muscle cross-sectional area and independently predicted one-year mortality.
- Percent change in CPR weakly tracked muscle CSA changes, and acute CPR trajectories were nonuniform, indicating multifactorial influences beyond muscle loss.
Methodological Strengths
- Combined mechanistic animal experiments with a sizable clinical cohort (n=629) for translational validity
- Objective biomarker using urinary excretion and serum kinetics; outcome linkage to one-year survival
Limitations
- Observational clinical analyses susceptible to confounding and practice variability
- Renal function fluctuations and fluid shifts may affect CPR independent of muscle biology
Future Directions: Prospective interventional studies to test CPR-guided nutrition/rehabilitation protocols and to standardize measurement timing; validate in perioperative cohorts.
BACKGROUND: Both quantitative and qualitative aspects of muscle status significantly impact clinical outcomes in critically ill patients. Comprehensive monitoring of baseline muscle status and its changes is crucial for risk stratification and management optimization. However, repeatable and accessible indicators are lacking. We hypothesized that creatinine production rate (CPR) could serve as an integrative indicator of skeletal muscle status. METHODS: We conducted a series of animal and clinical studies. First, animal experiments were performed to determine whether CPR reflects not only muscle volume, but also qualitative muscle properties. We also evaluated the effects of acute systemi
2. Safety and Efficacy of Tranexamic Acid in General Surgery.
In 3,260 general surgery patients within POISE-3, prophylactic TXA reduced the composite bleeding outcome (HR 0.74; 95% CI, 0.59-0.93; P=0.01) without increasing the composite cardiovascular safety outcome (HR 0.95; 95% CI, 0.78-1.16). Benefits were consistent across general surgery subtypes, including hepatopancreaticobiliary and colorectal procedures.
Impact: Provides high-quality randomized evidence supporting TXA use in general surgery with reassuring safety, informing perioperative blood management protocols.
Clinical Implications: Anesthesiologists can consider routine prophylactic TXA in eligible general surgery patients to reduce major bleeding without increasing vascular events, with particular benefit in hepatopancreaticobiliary and colorectal procedures.
Key Findings
- TXA reduced life-threatening/major/critical organ bleeding composite vs placebo (HR 0.74; 95% CI 0.59-0.93).
- No increase in cardiovascular safety composite (myocardial injury after noncardiac surgery, nonhemorrhagic stroke, arterial thrombosis, symptomatic proximal VTE) with TXA (HR 0.95; 95% CI 0.78-1.16).
- Benefit observed across general surgery subtypes, notably hepatopancreaticobiliary (HR 0.55; 95% CI 0.34-0.91) and colorectal (HR 0.67; 95% CI 0.45-0.98) surgery.
Methodological Strengths
- Randomized, blinded, international multicenter design with prespecified subgroup analyses
- Adequate power within the subgroup and formal interaction testing to assess consistency
Limitations
- Subgroup analysis inherits limitations of secondary analyses and may be underpowered for rare harms
- Applicability limited to patients similar to POISE-3 eligibility (≥45 years, elevated cardiovascular risk)
Future Directions: Implementation studies to optimize TXA dosing/timing in specific general surgery pathways and evaluate real-world effectiveness and rare adverse events.
IMPORTANCE: Perioperative bleeding is common in general surgery. The POISE-3 (Perioperative Ischemic Evaluation-3) trial demonstrated efficacy of prophylactic tranexamic acid (TXA) compared with placebo in preventing major bleeding without increasing vascular outcomes in noncardiac surgery. OBJECTIVE: To determine the safety and efficacy of prophylactic TXA, specifically in general surgery. DESIGN, SETTING, AND PARTICIPANTS: Subgroup analyses were conducted that compared randomized treatment with TXA vs placebo according to whether patients underwent general surgery or nongeneral surgery in the POISE-3 blinded, international, multicenter randomized clinical trial. Participants
3. A Supervised Explainable Machine Learning Model for Perioperative Neurocognitive Disorder in Liver-Transplantation Patients and External Validation on the Medical Information Mart for Intensive Care IV Database: Retrospective Study.
Using 958 LT cases with internal, temporal external, and MIMIC-IV external validation, a parsimonious logistic regression model achieved AUCs of 0.799–0.826 internally/temporally and 0.72 on MIMIC-IV. Explainability (SHAP) highlighted preoperative overt hepatic encephalopathy, platelet count, and postoperative SOFA as leading predictors of PND.
Impact: Delivers an explainable, interoperable tool for PND risk stratification with external validation, facilitating early preventive strategies in high-risk LT recipients.
Clinical Implications: Perioperative teams can identify high-risk LT recipients preemptively (e.g., overt hepatic encephalopathy, low platelets, high postoperative SOFA) to target delirium/POD mitigation, cognitive monitoring, and tailored anesthetic/ICU strategies.
Key Findings
- Logistic regression outperformed other ML algorithms with internal AUC 0.799 and temporal external AUC 0.826.
- External validation on MIMIC-IV achieved AUC 0.72, demonstrating generalizability.
- Top predictors by SHAP were preoperative overt hepatic encephalopathy, platelet count, and postoperative SOFA score.
Methodological Strengths
- Multiple validation strategies (internal, temporal external, and cross-dataset external on MIMIC-IV)
- Explainability via SHAP enhances transparency and clinical interpretability
Limitations
- Retrospective design with potential selection and information biases
- PND definitions and perioperative practices may vary across institutions affecting transportability
Future Directions: Prospective multicenter validation, model updating with multimodal inputs (EEG, intraoperative physiology), and trials testing PND prevention guided by model-based risk.
BACKGROUND: Patients undergoing liver transplantation (LT) are at risk of perioperative neurocognitive dysfunction (PND), which significantly affects the patients' prognosis. OBJECTIVE: This study used machine learning (ML) algorithms with an aim to extract critical predictors and develop an ML model to predict PND among LT recipients. METHODS: In this retrospective study, data from 958 patients who underwent LT between January 2015 and January 2020 were extracted from the Third Affiliated Hospital of Sun Yat-sen University. Six ML algorithms were used to predict post-LT PND, and model performance was evaluated using area under the receiver operating curve (AUC), accuracy, sensitivity, specificity, and F RESULTS: In the development cohort, 201 out of 751 (33.5%) patients were diagnosed with PND. The logistic regression model achieved the highest AUC (0.799) in the internal validation set, with comparable AUC in the temporal external (0.826) and MIMIC-Ⅳ validation sets (0.72). The top 3 features contributing to post-LT PND diagnosis were the preoperative overt hepatic encephalopathy, platelet level, and postoperative sequential organ failure assessment score, as revealed by the Shapley additive explanations method. CONCLUSIONS: A real-time logistic regression model-based online predictor of post-LT PND was developed, providing a highly interoperable tool for use across medical institutions to support early risk stratification and decision making for the LT recipients.