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Electroconvulsive therapy (ECT) is underused, logistically challenging for those who are justice-involved, and laced with ethical problems for those on death row. Herein we describe a case of a man without history of long-standing psychiatric illness who, after more than 15 years on death row, was hospitalized for altered mental status. After medical stabilization, the altered mental status persisted.

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Background: Metastatic spine tumor surgery (MSTS) is often complex and extensive leading to significant blood loss. Allogeneic blood transfusion (ABT) is the mainstay of blood replenishment but with immune-mediated postoperative complications. Alternative blood management techniques (salvaged blood transfusion [SBT]) allow us to overcome such complications.

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Motion-Compensated Multishot Pancreatic Diffusion-Weighted Imaging With Deep Learning-Based Denoising.

Invest Radiol

January 2025

From the Department of Radiology, Stanford University, Stanford, CA (K.W., M.J.M., A.M.L., A.B.S., A.J.H., D.B.E., R.L.B.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA (K.W.); GE HealthCare, Houston, TX (X.W.); GE HealthCare, Boston, MA (A.G.); and GE HealthCare, Menlo Park, CA (P.L.).

Objectives: Pancreatic diffusion-weighted imaging (DWI) has numerous clinical applications, but conventional single-shot methods suffer from off resonance-induced artifacts like distortion and blurring while cardiovascular motion-induced phase inconsistency leads to quantitative errors and signal loss, limiting its utility. Multishot DWI (msDWI) offers reduced image distortion and blurring relative to single-shot methods but increases sensitivity to motion artifacts. Motion-compensated diffusion-encoding gradients (MCGs) reduce motion artifacts and could improve motion robustness of msDWI but come with the cost of extended echo time, further reducing signal.

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Introduction: Language barriers within clinical settings pose a threat to patient safety. As a potential impediment to understanding, they hinder the process of obtaining informed consent and uptake of critical medical information. This study investigates the impact of the current use of interpreters, with a particular focus on of engaging laypersons as interpreters, rather than professional interpreters potentially affecting patient safety.

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Importance: Use of the publicly available Large Language Model, Chat Generative Pre-trained Transformer (ChatGPT 3.5; OpenAI, 2022), is growing in health care despite varying accuracies.

Objective: The aim of this study was to assess the accuracy and readability of ChatGPT's responses to questions encompassing surgical informed consent in urogynecology.

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