In recent decades, video techniques have been employed in the majority of endoscopic procedures because of several distinct advantages provided. These include the following: The displayed anatomy is magnified. Recognition of the anatomical structures and anomalies is easier, and manipulation of airway devices is facilitated. When assistance is required, the operator and assistant can coordinate their movements because each sees exactly the same image on the video monitor. As a result, video techniques have become the method of choice in teaching. The Video Macintosh Intubating Laryngoscope System (VMS) was designed employing a standard Macintosh blade and laryngoscope handle. A camera was incorporated into the handle with a short image and light bundle. The magnified anatomy is displayed on an 8-inch monitor, which is attached to a swivel arm on a small cart. Observation and manipulation can be performed in one axis.A total of 235 patients were studied and were divided into two groups: Group A (n = 217), in whom intubation was thought unlikely to be difficult, and Group B (n = 18), in whom difficulty with intubation was anticipated. External laryngeal manipulation (ELM) was required in 22 of the 217 Group A patients (10%). All intubations but one in this group were successful. In the second group (B) of 18 patients who had anatomical conditions that suggested that direct laryngoscopy might be challenging, all 18 cases required ELM but all were successfully intubated using the VMS. The improved coordination afforded by an image on a video monitor seen by both the assistant providing laryngeal manipulation and the anesthesiologist handling the laryngoscope results in a significant advantage over the conventional laryngoscope technique. As a consequence, the learning curve is short. In our view, video laryngoscopy will become the method of choice in teaching.
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http://dx.doi.org/10.1016/s0952-8180(02)00457-9 | DOI Listing |
Ann Emerg Med
January 2025
Department of Emergency Medicine Massachusetts General Hospital, Boston, MA. Electronic address:
Study Objective: We use national emergency department (ED) data to identify the proportion of "telehealth-able" ED visits, defined as potentially conductible by Video Only or Video Plus (with limited outpatient testing).
Methods: We used ED visits by patients 4 years of age and older from the 2019 National Hospital Ambulatory Medical Care Survey and applied survey weighting for national representativeness. Two raters categorized patient-described Reasons for Visit (RFV) as telehealth-able (yes, no, uncertain) for both Video Only and Video Plus visits.
J Nutr Educ Behav
January 2025
Suvida Healthcare, Houston, TX.
Objective: Assess if a virtual culinary medicine program improves healthy eating, glycosylated hemoglobin (HbA1c), and associated variables among adults with type 2 diabetes.
Design: Mixed-methods, intervention-only pilot study.
Setting: Classes via video conferencing from the teaching kitchen, with participants cooking from their homes.
Comput Biol Med
January 2025
Institute of Biomedical Engineering, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK.
Fetal echocardiography (ultrasound of the fetal heart) plays a vital role in identifying heart defects, allowing clinicians to establish prenatal and postnatal management plans. Machine learning-based methods are emerging to support the automation of fetal echocardiographic analysis; this review presents the findings from a literature review in this area. Searches were queried at leading indexing platforms ACM, IEEE Xplore, PubMed, Scopus, and Web of Science, including papers published until July 2023.
View Article and Find Full Text PDFNeural Netw
January 2025
Tsinghua University, Beijing, China. Electronic address:
Artificial neural networks (ANNs) can help camera-based remote photoplethysmography (rPPG) in measuring cardiac activity and physiological signals from facial videos, such as pulse wave, heart rate and respiration rate with better accuracy. However, most existing ANN-based methods require substantial computing resources, which poses challenges for effective deployment on mobile devices. Spiking neural networks (SNNs), on the other hand, hold immense potential for energy-efficient deep learning owing to their binary and event-driven architecture.
View Article and Find Full Text PDFInt J Med Inform
January 2025
University of Coimbra, Faculty of Medicine, Coimbra, Portugal; Department of Gastroenterology, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal. Electronic address:
Background: The wireless capsule endoscope (CE) is a valuable diagnostic tool in gastroenterology, offering a safe and minimally invasive visualization of the gastrointestinal tract. One of the few drawbacks identified by the gastroenterology community is the time-consuming task of analyzing CE videos.
Objectives: This article investigates the feasibility of a computer-aided diagnostic method to speed up CE video analysis.
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