Internal medicine
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Objective Azacitidine (AZA) has been the standard of care for elderly patients with high-risk myelodysplastic syndromes (MDS). However, reliable clinical predictors of outcome have yet to be identified. The prognostic value of fetal hemoglobin (HbF) levels has been reported for decitabine therapy. ⋯ Results The median follow-up duration was 13.0 (range 1.5-93.5) months. The HbF-elevated group was associated with a significantly higher hematologic improvement rate (76.9% vs. 25%, p=0.009) and better overall survival (median, 21.0 vs. 13.0 months, p=0.048) than the HbF-normal group. Conclusion These results suggest that elevated pretreatment HbF levels can predict better outcomes in patients with MDS/AML treated with AZA.
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A 90-year-old man presented with a 3-day history of general malaise. He was febrile (39.3°C) but the initial evaluation did not reveal the cause of the fever. After admission, Bacillus subtilis and Fusobacterium nucleatum were grown from multiple sets of blood cultures. ⋯ After receiving antimicrobial treatment and anticoagulation, the patient was cured. Pylephlebitis is a rare condition and may be the cause of unknown fevers. This is the first reported case of pylephlebitis caused by Bacillus subtilis.
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Objective Contrast agents used for radiological examinations are an important cause of acute kidney injury (AKI). We developed and validated a machine learning and clinical scoring prediction model to stratify the risk of contrast-induced nephropathy, considering the limitations of current classical and machine learning models. Methods This retrospective study included 38,481 percutaneous coronary intervention cases from 23,703 patients in a tertiary hospital. ⋯ The seven precatheterization variables selected for the simple model were age, known chronic kidney disease, hematocrit, troponin I, blood urea nitrogen, base excess, and N-terminal pro-brain natriuretic peptide. The simple model is available at http://52.78.230.235:8081/Conclusions We developed an AKI prediction machine learning model with reliable performance. This can aid in bedside clinical decision making.