Comparison of time-series models for predicting physiological metrics under sedation.

This study presents a comprehensive comparison of multiple time-series models applied to physiological metric predictions. It aims to explore the effectiveness of both statistical prediction models and pharmacokinetic-pharmacodynamic prediction model and modern deep learning approaches. Specifically, the study focuses on predicting the bispectral index (BIS), a vital metric in anesthesia used to assess the depth of sedation during surgery, using datasets collected from real-life surgeries.

Comparative Analysis of Machine-Learning Model Performance in Image Analysis: The Impact of Dataset Diversity and Size.

Background: This study presents an analysis of machine-learning model performance in image analysis, with a specific focus on videolaryngoscopy procedures. The research aimed to explore how dataset diversity and size affect the performance of machine-learning models, an issue vital to the advancement of clinical artificial intelligence tools.

Methods: A total of 377 videolaryngoscopy videos from YouTube were used to create 6 varied datasets, each differing in patient diversity and image count.

Epidural Catheterization in Cardiac Surgery: A Systematic Review and Risk Assessment of Epidural Hematoma.

The potential benefits of epidural anesthesia on mortality, atrial fibrillation, and pulmonary complications must be weighed against the risk of epidural hematoma associated with intraoperative heparinization. This study aims to provide an updated assessment of the clinical risks of epidural anesthesia in cardiac surgery, focusing on the occurrence of epidural hematomas and subsequent paralysis. A systematic search of Embase, Medline, Ovid Central, Web of Science, and PubMed was conducted to identify relevant publications between 1966 and 2022.

Investigation into the clinical performance of rectus sheath block in reducing postoperative pain following surgical intervention: A systematic review and meta-analysis of randomised controlled trials.

Background And Aims: Rectus sheath block (RSB) is an effective postoperative pain control technique in abdominal surgical procedures. This systematic review evaluated the efficacy and outcome data of patients undergoing RSB compared to the standard of care in both laparoscopic and open surgical procedures.

Methods: This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO ID: CRD42022372596).

Beyond the Echo: The Evolution and Revolution of Ultrasound in Anesthesia.

This article explores the evolving role of ultrasound technology in anesthesia. Ultrasound emerged decades ago, offering clinicians noninvasive, economical, radiation-free, and real-time imaging capabilities. It might seem that such an old technology with apparent limitations might have had its day, but this review discusses both the current applications of ultrasound (in nerve blocks, vascular access, and airway management) and then, more speculatively, shows how integration of advanced ultrasound modalities such as contrast-enhanced imaging with virtual reality (VR), or nanotechnology can alter perioperative patient care.

Robotic Anesthesia: A Vision for 2050.

The last 2 decades have brought important developments in anesthetic technology, including robotic anesthesia. Anesthesiologists titrate the administration of pharmacological agents to the patients' physiology and the needs of surgery, using a variety of sophisticated equipment (we use the term "pilots of the human biosphere"). In anesthesia, increased safety seems coupled with increased technology and innovation.

Utilizing Deep Learning to Identify an Ultrasound-guided Nerve Block Target Zone.

Ultrasound guided nerve blocks are increasingly being used in perioperative care as a means of safely delivering analgesia. Unfortunately, identifying nerves in ultrasound images presents a challenging task for novice anesthesiologists. Drawing from online resources, here we attempted to address this issue by developing a deep learning algorithm capable of automatically identifying the transversus abdominis plane region in ultrasound images.

The ITAG Spinal Simulator (ISS): A New Simulator for Difficult Lumbar Punctures.

Lumbar punctures present a specific challenge in various medical specialties; appropriate simulators need to take into account the specific technical difficulties related to a realistic patient population, but currently fail to address the variety of anatomical differences seen in practice. We interviewed several leaders in the field of anesthesiology with extensive experience in lumbar puncture procedures, subsequently developing a more realistic training simulator. This novel simulator was built using silicone-based materials and advanced 3D-printing techniques, specifically tailored to be capable of mimicking a variety of patient populations without having to dispose of essential components after each use.

Pro-Con Debate: Should All General Anesthesia Be Done Using Target-Controlled Propofol Infusion Guided by Objective Monitoring of Depth of Anesthesia?

In this Pro-Con commentary article, we discuss whether all general anesthesia should be done using target-controlled propofol anesthesia guided by monitoring of depth of anesthesia. This is an ongoing debate since more than 25 years, representing a scientific, cultural as well as geographical divide in the anesthesia community. The Pro side argues that total intravenous anesthesia causes less postoperative nausea and higher patient satisfaction than anesthesia using volatile anesthetics.

Ultrasound Calculation of Fat Volume for Liposuction: A Clinical Software Validation.

Background: Fat manipulation procedures such as liposuction contain a degree of subjectivity primarily guided by the surgeon's visual or tactile perception of the underlying fat. Currently, there is no cost-effective, direct method to objectively measure fat depth and volume in real time.

Objectives: Utilizing innovative ultrasound-based software, the authors aimed to validate fat tissue volume and distribution measurements in the preoperative setting.

Clinical Performance of Decision Support Systems in Anesthesia, Intensive Care, and Emergency Medicine: A Systematic Review and Meta-Analysis.

Background: Medical technology is expanding at an alarming rate, with its integration into health care often reflected by the constant evolution of best practices. This rapid expansion of available treatment modalities, when coupled with progressively increasing amounts of consequential data for health care professionals to manage, creates an environment where complex and timely decision-making without the aid of technology is inconceivable. Decision support systems (DSSs) were, therefore, developed as a means of supporting the clinical duties of health care professionals through immediate point-of-care referencing.

Description of a Novel Web-Based Liposuction System to Estimate Fat Volume and Distribution.

Background: Preoperative planning for liposuction is vital to ensure safe practice and patient satisfaction. However, current standards of fat assessment before surgery are guided by subjective methods such as visual inspection, skin-pinch tests, and waist circumference measurements.

Objectives: This study aimed to develop an inexpensive software-based tool that utilizes ultrasound (US) imaging and an online platform to accurately simulate regional subcutaneous adipose tissue (SAT) distribution and safe volume estimation for liposuction procedures.

The Development of a Novel Bariatric Laparoscopic Simulator.

Bariatric surgery presents a specific challenge in surgical education; simulators need to take into account the specific technical difficulties related to the patient population but also to various types of surgery. We interviewed several leaders in the fields of bariatric and general surgery with experience in laparoscopic surgery and developed a bariatric-specific laparoscopic simulator. This novel simulator was constructed using a variety of silicone-based materials and 3D printing techniques to be reusable and adjustable for a variety of procedures, with no essential components being disposed of following each use.

Technologies to Optimize the Care of Severe COVID-19 Patients for Health Care Providers Challenged by Limited Resources.

Health care systems are belligerently responding to the new coronavirus disease 2019 (COVID-19). The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a specific condition, whose distinctive features are severe hypoxemia associated with (>50% of cases) normal respiratory system compliance. When a patient requires intubation and invasive ventilation, the outcome is poor, and the length of stay in the intensive care unit (ICU) is usually 2 or 3 weeks.