Anesthesiology

AI Models for Surgical Decision Support in Spontaneous Intracerebral Hemorrhage: A Systematic Review in Relation to Trials and Guidelines.

Artificial intelligence (AI) applications for spontaneous intracerebral hemorrhage (ICH) are rapidly expanding, particularly in perioperative imaging analysis and surgical decision support. Because most predictive AI models are developed using independent clinical datasets, they are not expected to explicitly reproduce randomized trial protocols or guideline decision rules. We therefore conducted ...

Dynamic EEG spectral changes during acute alcohol intoxication and propofol exposure: Implications for machine-learning-based alcoholism detection.

Predicting Ketamine Exposure in Pediatric Status Epilepticus: A Pharmacokinetic-Machine Learning Approach.

BACKGROUND AND OBJECTIVE: Status epilepticus is a life-threatening neurological emergency. Ketamine combined with levetiracetam is a promising therapy...

Beyond block time: a head-to-head comparison of reinforcement learning, genetic algorithms, and predict-then-optimize scheduling for operating room workflow using discrete-event simulation.

BACKGROUND: Operating room (OR) inefficiency persists despite decades of process improvement, largely due to stochastic case durations, emergency disr...

Deep learning improves image quality in motion-robust and sedation-free pediatric brain MRI.

OBJECTIVES: Motion and limited compliance compromise diagnostic MR image quality, particularly in pediatric patients who frequently require sedation. ...

Physician Gestalt Compared With Artificial Intelligence Model to Predict Intubation in Critically Ill Patients.

IMPORTANCE: Accurate prediction of intubation in critically ill patients could enable interventions that improve patient outcomes. However, the perfor...

Benchmarking text encoding strategies in multimodal clinical data for surgical case duration prediction.

BACKGROUND: Operating rooms (ORs) are highly resource-intensive, yet surgical case duration is often estimated using heuristics that are prone to erro...

Deep learning approach for stroke volume variation estimation: retrospective modeling and prospective deployment in real-world practice.

Objective. We developed stroke volume variation (SVV) Net, a deep learning-based model for estimating SVV, and validated its performance and clinical ...

Risk Prediction Models for Post-Endoscopic Retrograde Cholangiopancreatography Pancreatitis: A Systematic Review and Meta-Analysis.

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) serves as an essential procedure for diagnosing and treating pancreaticobiliary diso...

Development and Internal Validation of a Gradient Boosting Model for Pressure Injury Risk in the ICU.

Pressure injury (PI) is common in the ICU and not well captured by single-risk tools such as the Braden scale. We aimed to develop and internally vali...

Predicting Post-Induction Hypotension in Diverse Surgical Populations: A Multiclass Classification Universal Model Using Machine Learning Techniques.

PURPOSE: Our study aims to develop a machine learning model that not only predicts the occurrence of post-induction hypotension (PIH) but also assesse...

Dynamic machine learning prediction of persistent AKI after cardiac surgery with modifiable perioperative risk factors.

Early identification and prevention of persistent acute kidney injury (pAKI) remain challenging due to delayed biochemical markers and limited tools t...

Predictive accuracy of a perioperative hemodynamic indices-based prediction model for moderate-to-severe acute kidney injury after orthotopic heart transplantation.

BACKGROUND: Acute kidney injury is a common complication after orthotopic heart transplantation. Previous models have failed to consider the impact of...

[Geriatric oncology patients at the center of nurse-led delirium management].

BACKGROUND: Postoperative delirium is an acute, fluctuating neurocognitive syndrome. It is among the most common perioperative complications in older ...

Automated hemodynamic management system for the prevention of hypotension and cardiac output reduction during general anesthesia: preclinical experimental validation.

PURPOSE: Intraoperative hypotension and cardiac output (CO) reduction adversely affect outcomes and require cause-specific treatment against vasodilat...

AI-assisted videolaryngoscopy improves intubation success: results from a randomized simulation trial.

Video laryngoscopy has become an integral part of today's airway management. Despite its advantages, loss of depth perception and increased cognitive ...

Practical Integration of Bedside Real-Time Lung Ultrasound and Electrical Impedance Tomography for Guiding Personalized Perioperative Lung Protective Ventilation in Cardiothoracic and Vascular Anesthesia.

Patients undergoing cardiothoracic and vascular surgery are at uniquely high risk for postoperative pulmonary complications due to the confluence of s...

Artificial Intelligence for Colorectal Surgeons - Part I: Foundations, Clinical and Educational Applications.

BACKGROUND: Artificial intelligence (AI) is rapidly transforming colorectal surgery through applications spanning screening to postoperative care. Thi...

Wearable Devices and Artificial Intelligence to Enhance Perioperative Care in Total Knee Arthroplasty.

Rapidly evolving wearable devices have the potential to transform health care delivery and enhance outcomes. Applications of wearable smart devices ra...

The Arc of Nurse Anesthesia: From Battlefield Origins to Future Innovation.

This article explores the evolution of the Certified Registered Nurse Anesthesiologist (CRNA) profession, from its origins during wartime medicine to ...