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Hemorrhagic astroblastoma: atypical presentation of a rare tumor. Illustrative case.
J Neurosurg Case Lessons
January 2025
Neurosurgery Department, Palmetto General Hospital, Hialeah, Florida.
Background: Astroblastoma is an extremely rare tumor of the central nervous system, and its origin and validity as a different entity are still being debated. Because of its rarity and similarities to other glial neoplasms, it is often misdiagnosed, impacting treatment and outcomes.
Observations: Astroblastoma is very rare and mainly affects children and young adults.
Effect of targeted education of patients with atrial fibrillation on unplanned cardiovascular outcomes: results of the multicentre randomized AF-EduCare trial.
Europace
December 2024
Research Group Cardiovascular Diseases, University of Antwerp, Prinsstraat 13, Antwerp 2000, Belgium.
Aims: Trials on integrated care for atrial fibrillation (AF) showed mixed results in different AF populations using various approaches. The multicentre, randomized AF-EduCare trial evaluated the effect of targeted patient education on unplanned cardiovascular outcomes.
Methods And Results: Patients willing to participate were randomly assigned to in-person education, online education, or standard care (SC) and followed for minimum 18 months.
Machine learning models for predicting postoperative peritoneal metastasis after hepatocellular carcinoma rupture: a multicenter cohort study in China.
Oncologist
January 2025
Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Background: Peritoneal metastasis (PM) after the rupture of hepatocellular carcinoma (HCC) is a critical issue that negatively affects patient prognosis. Machine learning models have shown great potential in predicting clinical outcomes; however, the optimal model for this specific problem remains unclear.
Methods: Clinical data were collected and analyzed from 522 patients with ruptured HCC who underwent surgery at 7 different medical centers.
Perfusion estimation from dynamic non-contrast computed tomography using self-supervised learning and a physics-inspired U-net transformer architecture.
Int J Comput Assist Radiol Surg
January 2025
Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
Purpose: Pulmonary perfusion imaging is a key lung health indicator with clinical utility as a diagnostic and treatment planning tool. However, current nuclear medicine modalities face challenges like low spatial resolution and long acquisition times which limit clinical utility to non-emergency settings and often placing extra financial burden on the patient. This study introduces a novel deep learning approach to predict perfusion imaging from non-contrast inhale and exhale computed tomography scans (IE-CT).
View Article and Find Full Text PDFA rare case of colonic ulcer.
Rev Esp Enferm Dig
January 2025
Emergency, Suzhou Ninth People's Hospital. Soochow University.
A 72-year-old woman presented to our outpatient department due to diarrhea that began 10 days ago without a known trigger. The patient presented with frequent (four to five times a day), loose yellow stool, containing significant mucus. She reported no obvious symptoms such as abdominal distension, pain, chills or fever, and her medical history included diabetes and hypertension.
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