Anesthesiology

Consistent analgesic effect of intravenous dexamethasone on rebound pain after brachial plexus block: a causal machine learning approach.

BACKGROUND: Rebound pain, a sudden increase in pain intensity after resolution of regional anesthesia, remains a major challenge in postoperative patient care. Intravenous (IV) dexamethasone has been proposed as a preventive strategy, but whether its effectiveness varies across patient characteristics remains unclear. METHODS: This retrospective study included patients who underwent upper extremit...

Radiation scatter at fluoroscopy-guided endoscopic procedures: Building towards further optimization.

INTRODUCTION: Exposure to ionizing radiation by endoscopy personnel during fluoroscopy-guided procedures remains a health hazard. We aimed to evaluate a novel lead flap-enhanced artificial intelligence-enabled fluoroscopy (LE-AIF) system to minimize radiation scatter. METHODS: We conducted prospective study of 218 patients who underwent fluoroscopy-guided endoscopic procedures using conventional A...

Risk prediction models based on machine learning for emergence delirium in elderly patients undergoing spine surgery: development and validation study.

BACKGROUND: Emergence delirium (ED) is a common complication in elderly patients undergoing surgery for degenerative spinal disease (DSD) and is assoc...

A S.C.O.R.E. framework for evaluating open-ended responses from large language models in healthcare.

Domain-specific evaluation is essential for clinical validation. We propose S.C.O.R.E. (Safety, Consensus & Context, Objectivity, Reproducibility, Exp...

An explainable machine learning framework for computable physiologic risk representation in preanesthetic assessment: Development and external validation.

BACKGROUND: Preanesthetic evaluation requires clinicians to synthesize heterogeneous clinical information, yet perioperative risk communication often ...

[A two-stage model for predicting postoperative pulmonary infection in esophageal cancer patients].

Postoperative pulmonary infection (PPI) after esophageal cancer surgery occurs frequently and severely impairs patients' prognosis. Most existing pred...

Predicting Risk Factors of Pressure Injury for Perioperative Patients Through Machine Learning With SHapley Additive exPlanations Based on Hospital Information System.

OBJECTIVE: Perioperative pressure injuries (PIs) are a common complication of surgical hospitalization that can lead to serious health problems, compr...

A perioperative multi-modal fusion and deep learning-based prognostic system for upper tract urothelial carcinoma: a multi-institutional study.

OBJECTIVES: Precise perioperative risk stratification for upper tract urothelial carcinoma (UTUC) is essential. We developed a multimodal prognostic m...

Traditional learning meets adaptive learning: the present and future of education in nonoperating room anesthesia.

PURPOSE OF REVIEW: Nonoperating room anesthesia (NORA) and continuing education in this setting are both in a state of change. Procedures performed ou...

Preoperative considerations for nonoperating room anesthesia.

PURPOSE OF THE REVIEW: This review aims to address the unique challenges in nonoperating room anesthesia (NORA) locations, emphasizing the importance ...

Detection, localization, and measurement of endotracheal tube positioning on adults' chest X-ray: developing a prediction model.

Accurate placement of the endotracheal tube (ETT) is critical for ensuring optimal care for patients requiring mechanical ventilation and preventing p...

An interpretable machine learning model for predicting postoperative hypotension in type 2 diabetes mellitus undergoing non‑cardiac surgery.

BACKGROUND: Postoperative hypotension (POH) is a common and serious complication in patients with type 2 diabetes mellitus (T2DM) undergoing non‑cardi...

Precision neuroprotection in cardiac surgery: a structured narrative review of multimodal, data-driven perioperative care.

Neurological injury remains a major contributor to morbidity, mortality, and long-term cognitive decline in patients undergoing cardiac surgery, despi...

Rethinking health technology assessment in robotic surgery: an EFISDS-TROGSS position paper. Official position paper of the European Federation - International Society for Digestive Surgery (EFISDS) and The Robotic Global Surgical Society (TROGSS).

Robotic-assisted surgery (RAS) has evolved from a procedural innovation into an increasingly integrated component of contemporary digital surgical eco...

AI for prognosis and treatment stratification in glioblastoma neurosurgery: a systematic review.

BACKGROUND: Glioblastoma (GBM) remains one of the most lethal adult primary brain tumors, and neurosurgical decision-making increasingly depends on in...

Novel technologies and innovations in postoperative follow-up after regional anesthesia.

PURPOSE OF REVIEW: Postoperative follow-up after regional anesthesia is essential for identifying complications, distinguishing expected block effects...

Airway coach project: development of a machine learning-based model using clinical and ultrasound parameters to support videolaryngoscopy strategy.

BACKGROUND: Videolaryngoscopy (VL) is recommended as a first-line technique for tracheal intubation; however, existing airway assessment tools-largely...

Automated extraction of colonoscopy quality indicators from free-text reports using a prompt-based large language model pipeline.

BACKGROUND AND AIMS: Artificial intelligence has increasingly enabled large-scale analysis of clinical documentation, offering new opportunities to im...

Evaluation of Five Large Language Models for Parental Education in Pediatric Anesthesia: Reliability and Readability Study.

BACKGROUND: Although large language models (LLMs) show potential for patient education, their accuracy, usability, and comprehensibility lack validati...

Challenges for implementation of "Enhanced Recovery After Surgery" (ERAS) protocols and artificial intelligence support tools in resource-limited countries.

Surgical patient safety remains a major challenge in resource-limited settings, where preventable harm may be increased by delayed assessment, limited...