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Early weaning from invasive mechanical ventilation via high-flow nasal oxygen versus conventional weaning in patients with hypoxemic respiratory failure: a prospective randomized controlled study.
Crit Care Sci
January 2025
Anaesthesiology and Critical Care, All India Institute of Medical Sciences - Jodhpur, India.
Objective: Although the efficacy of high-flow nasal oxygen therapy in delaying or avoiding intubation in patients with hypoxemic respiratory failure has been studied, its potential for facilitating early weaning from invasive mechanical ventilation remains unexplored.
Methods: In this randomized controlled trial, 80 adults with acute hypoxemic respiratory failure requiring invasive mechanical ventilation for > 48 hours were enrolled and divided into two groups: conventional weaning and early weaning via high-flow nasal oxygen. In the conventional weaning group, the spontaneous breathing trial was performed after the PaO2/FiO2 ratio was ≥ 200, whereas in the high-flow nasal oxygen group, the spontaneous breathing trial was conducted earlier when the PaO2/FiO2 ratio was 150 - 200.
Monitoring wetland cover changes and land surface temperatures using remote sensing and GIS in Göksu Delta.
Integr Environ Assess Manag
January 2025
Faculty of Fine Arts, Design and Architecture Department of Landscape Architecture, Tekirdağ Namık Kemal University, Tekirdağ, Türkiye.
Wetlands provide necessary ecosystem services, such as climate regulation and contribution to biodiversity at global and local scales, and they face spatial changes due to natural and anthropogenic factors. The degradation of the characteristic structure signals potential severe threats to biodiversity. This study aimed to monitor the long-term spatial changes of the Göksu Delta, a critical Ramsar site, using remote sensing techniques.
View Article and Find Full Text PDFImproving Diagnostic Efficiency for Knee Osteoarthritis with the Knee Intake Patient Survey (KIPS).
R I Med J (2013)
February 2025
Department of Orthopedics, Brown University, Providence, RI.
Objectives: Knee Osteoarthritis (OA) is one of the most frequently encountered conditions in orthopedic practice. This study aimed to validate the Knee Intake Patient Survey (KIPS), a short-form questionnaire designed to assist in the initial diagnosis and treatment stratification for knee OA.
Methods: Patient intake survey results from a single adult reconstruction clinic were retrospectively analyzed alongside clinical diagnoses and treatment recommendations.
Artificial intelligence-enhanced magnetic resonance imaging-based pre-operative staging in patients with endometrial cancer.
Int J Gynecol Cancer
January 2025
Institute of Image-Guided Surgery, IHU Strasbourg, France; University of Strasbourg, ICube, Laboratory of Engineering, Computer Science and Imaging, Department of Robotics, Imaging, Teledetection and Healthcare Technologies, CNRS, UMR, Strasbourg, France.
Objective: Evaluation of prognostic factors is crucial in patients with endometrial cancer for optimal treatment planning and prognosis assessment. This study proposes a deep learning pipeline for tumor and uterus segmentation from magnetic resonance imaging (MRI) images to predict deep myometrial invasion and cervical stroma invasion and thus assist clinicians in pre-operative workups.
Methods: Two experts consensually reviewed the MRIs and assessed myometrial invasion and cervical stromal invasion as per the International Federation of Gynecology and Obstetrics staging classification, to compare the diagnostic performance of the model with the radiologic consensus.
Construction of an Artificially Intelligent Model for Accurate Detection of HCC by Integrating Clinical, Radiological, and Peripheral Immunological Features.
Int J Surg
January 2025
Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Background: Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to improve its early detection. We aimed to develop a model with multi-modal features (MMF) using artificial intelligence (AI) approaches to enhance the performance of HCC detection.
Materials And Methods: A total of 1,092 participants were enrolled from 16 centers.
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