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INTRODUCTION: Measuring elevated post-void residual volume is important for diagnosing urinary outflow tract obstruction and cauda equina syndrome. Catheter placement is exact but painful, invasive, and may cause infection, whereas an ultrasound is accurate, painless, and safe. AIM: The purpose of this single-center study is to evaluate the accuracy of a module for artificial-intelligence (AI)-based fully automated bladder volume (BV) prospective measurement using two-dimensional ultrasound images, as compared with manual measurement by expert sonographers. METHODS: Pairs of transverse and longitudinal bladder images were obtained from patients evaluated in an urgent care clinic. The scans were prospectively analyzed by the automated module using the prolate ellipsoid method. The same examinations were manually measured by a blinded expert sonographer. The two methods were compared using the Pearson correlation, kappa coefficients, and the Bland-Altman method. RESULTS: A total of 111 pairs of transverse and longitudinal views were included. A very strong correlation was found between the manual BV measurements and the AI-based module with r = 0.97 [95% CI: 0.96-0.98]. The specificity and sensitivity for the diagnosis of an elevated post-void residual volume using a threshold ≥200 mL were 1.00 and 0.82, respectively. An almost-perfect agreement between manual and automated methods was obtained (kappa = 0.85). Perfect reproducibility was found for both inter- and intra-observer agreements. CONCLUSION: This AI-based module provides an accurate automated measurement of the BV based on ultrasound images. This novel method demonstrates a very strong correlation with the gold standard, making it a potentially valuable decision-support tool for non-experts in acute settings.
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Emergency medical teams (EMTs) encounter chaos upon arriving at the scene of a disaster. Rescue efforts are utilitarian and focus on providing the technical aspects of medical care in order to save the most lives at the expense of the individual. This often neglects the basic healthcare rights of the patient. The Sphere Project was initiated to develop universal humanitarian standards for disaster response. The increase in the number of EMTs led the World Health Organization (WHO) to organize standards for disaster response. In 2016, the WHO certified the Israel Defense Forces Field Hospital (IDF-FH) as the first to be awarded the highest level of accreditation (EMT-3). This paper presents the IDF-FH's efforts to protect the patient's healthcare rights in a disaster zone based on the Sphere Principles. These core Sphere Principles include the right to professional medical treatment; the right to dignity, privacy, and confidentiality; the right for information in an understandable language; the right to informed consent; the obligation to maintain private medical records; the obligation to adhere to universal ethical standards, to respect culture and custom and to care for vulnerable populations; the right to protection from sexual exploitation and violence; and the right to continued treatment.