Internal medicine
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Objective High-quality images can be obtained with 320-slice computed tomography (CT) with model-based iterative reconstruction (MBIR). We therefore investigated the diagnostic accuracy of 320-slice CT with MBIR for detecting significant coronary artery stenosis. Methods This was a retrospective study of 160 patients who underwent coronary CT and invasive coronary angiography (ICA). ⋯ No significant differences were observed between the two groups in the patient- and segment-based analyses. However, among cases with a severe coronary artery calcium score >400 (31 cases in Group 1 and 28 in Group 2), the specificity and overall accuracy were significantly higher (all p<0.01) in Group 2 than in Group 1 according to the segment-based analysis. Conclusion The diagnostic accuracy of the detection of coronary artery stenosis on CT was improved using 320-slice CT with MBIR.
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A 74-year-old woman presented with left lateral abdominal pain. Abdominal echography revealed left hydronephrosis and a pelvic mass. ⋯ The most common histological types of ovarian lymphoma are diffuse large B-cell lymphoma and Burkitt lymphoma, with FL being an extremely rare variant. We herein report a case of ovarian FL diagnosed as hydronephrosis.
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A 67-year-old woman who had undergone bone marrow transplantation 2 years previously for acute myeloid leukemia (AML) developed complications of chronic graft-versus-host disease (cGVHD). She thereafter also developed nephrotic syndrome, and membranous nephropathy (MN) was diagnosed by a renal biopsy. ⋯ Rituximab treatment was initiated, and her nephrotic syndrome gradually improved without relapse of AML. Our present case suggests that rituximab is a safe and effective therapeutic option for cGVHD-associated MN.
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Objectives Numerous people have died from coronavirus disease 2019 (COVID-19) infection. Identifying crucial predictive biomarkers of disease mortality is critical to support decision-making and logistic planning in healthcare systems. This study investigated the association between mortality and medical factors and prescription records in 2020 in Japan, where COVID-19 prevalence and mortality remain relatively low. ⋯ A machine learning analysis identified an older age, male sex (mortality), pneumonia, drugs for acid-related disorders, analgesics, anesthesia, upper respiratory tract disease, drugs for functional gastrointestinal disorders, drugs for obstructive airway diseases, topical products for joint and muscular pain, diabetes, lipid-modifying agents, calcium channel blockers, drugs for diabetes, and agents acting on the renin-angiotensin system as risk factors for a severe status. Conclusions This COVID-19 mortality risk tool is a well-calibrated and accurate model for predicting mortality risk among hospitalized patients with COVID-19 in Japan, which is characterized by a relatively low COVID-19 prevalence, aging society, and high population density. This COVID-19 mortality prediction model can assist in resource utilization and patient and caregiver education and be useful as a risk stratification instrument for future research trials.