Anesthesiology

Prediction of postoperative desaturation and bradycardia in neonates undergoing laparoscopic inguinal hernia repair: a retrospective cohort study.

BACKGROUND: Ex-premature infants have a high risk of postoperative apnea and bradycardia. This study aimed to develop a predictive model for postoperative desaturation and bradycardia in infants who underwent laparoscopic inguinal hernia repair (IHR) under general anesthesia based on identified risk factors. METHODS: The retrospective cohort included infants who underwent laparoscopic IHR under ge...

Real-Time Artificial Intelligence Assistance in Neuroendovascular Therapy: Comparative Analysis of Elective and Emergency Procedures.

BACKGROUND AND OBJECTIVES: Artificial intelligence (AI) has emerged as an adjunct in neuroendovascular interventions; however, its clinical utility remains insufficiently characterized. This study aimed to delineate the clinical impact of a real-time AI guidance system during neuroendovascular therapy and to compare elective and emergency interventions, using device repositioning as a quantitative...

Quantitative sensory testing and classical pain model dataset in 127 healthy volunteers.

Experimental pain models are integral to human pain research and the development of analgesic drugs. Of many options available, it is possible to iden...

Research landscape, knowledge structure, and emerging frontiers of robot-assisted surgery for urolithiasis: a bibliometric and visualization analysis.

Robot-assisted techniques have been increasingly explored in urolithiasis, particularly in selected complex settings such as concomitant reconstructio...

Structural imaging predictors of ketamine response in treatment-resistant depression: a machine learning approach.

Ketamine has demonstrated rapid antidepressant efficacy in treatment-resistant depression (TRD), but clinical decision-making is challenging due to va...

Propensity score-matched multicentric observational cohort study comparing robotic cholecystectomy with laparoscopic cholecystectomy.

BACKGROUND: With increasing penetration of robotic surgery, robotic cholecystectomies are becoming more popular. There are several benefits which may ...

Dynamic machine learning model integrating resting energy expenditure for predicting postoperative complications after gastrectomy for gastric cancer.

PURPOSE: To investigate whether perioperative resting energy expenditure (REE) dynamics improve prediction of postoperative complications after gastre...

Predicting atrial fibrillation recurrence after radiofrequency ablation using the AIFV system: a prospective observational study.

BACKGROUND: Pulmonary vein isolation (PVI) has become the cornerstone of atrial fibrillation (AF) treatment. Nevertheless, the efficacy of radiofreque...

Applications of artificial intelligence along the perioperative pathway in metabolic and bariatric surgery.

BACKGROUND: The use of artificial intelligence (AI) has rapidly increased in metabolic and bariatric surgery (MBS) in recent years, necessitating a co...

From decision support to clinical integration: A scoping review of artificial intelligence in prehospital airway management.

BACKGROUND: Airway management is a critical component of prehospital emergency care, where rapid decision-making and procedural accuracy are essential...

Ventral hernia repair in emergency settings. A machine learning model to predict post-operative complications.

BACKGROUND: Emergency ventral hernia repair remains a challenging procedure due to patient instability, contaminated surgical fields, and heterogeneit...

NeuroPred-GMC: a dual-branch deep learning architecture for neuropeptide prediction based on gated dilated convolutional network and multi-scale convolutional network.

Neuropeptides are multifunctional signaling molecules in the nervous system. By modulating synaptic transmission and integrating physiological systems...

The Ethics Committee of the Italian Society of Anesthesia, Analgesia, Resuscitation and Intensive Care (SIAARTI) - Artificial intelligence in end-of-life decision-making processes: ethical reflections.

Recent proposals to use artificial intelligence (AI) in end-of-life decision-making for incapacitated patients without advance directives have prompte...

End-of-surgery prediction of postoperative infectious complications from intraoperative vital-sign dynamics.

Infections after surgery remain a leading cause of morbidity and mortality, yet reliable risk stratification at the end of surgery is limited. Intraop...

Real-time artificial intelligence-based needle tracking for ultrasound-guided regional anesthesia training: a pilot prospective randomized controlled trial.

BACKGROUND: Proper needle visualization is a major technical challenge for novices learning ultrasound-guided regional anesthesia (UGRA). We developed...

Radiomics-enhanced machine learning for differentiating epidural and subdural hematomas on non-contrast CT.

BACKGROUND: Differentiating epidural hematoma (EDH) from subdural hematoma (SDH) on non-contrast CT (NCCT) is clinically important but can be challeng...

Prevalence of disability-free survival at 5 years after surgery: a prospective observational study.

PURPOSE: To determine the prevalence of disability-free survival (DFS) five years after elective non-cardiac surgery in older adults, and to identify ...

Positron emission tomography imaging of inflammation and infection in children: an update.

Positron emission tomography (PET) has been used in pediatric oncology since the modality gained traction 20 years ago but has been used more sparingl...

Beyond NIHSS and neuroimaging: an interpretable gradient boosting model for predicting in-hospital mortality in ICU patients with acute ischemic stroke.

This study aimed to develop an interpretable machine learning model for predicting in-hospital mortality among acute ischemic stroke (AIS) patients ad...

Predicting postoperative atrial fibrillation after cardiac surgery using machine learning.

BACKGROUND: Postoperative atrial fibrillation (POAF) is a frequent complication after cardiac surgery that is associated with increased morbidity. How...