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Background And Aims: Hepatotoxicity is a known risk of oral and intravenous methotrexate (MTX), but whether intrathecal (IT) administration causes hepatotoxicity remains unknown. We aimed to explore whether IT-MTX causes acute hepatoxicity.
Methods: Retrospective single-centre analysis of all patients treated with IT-MTX from 2000 to 2020. We compared liver enzymes (LE) at baseline (within 7 days before IT-MTX) to post-MTX (within 7 days after IT-MTX). LE elevation was defined as ≥ 50% increase in LE from baseline and greater than upper limit of normal. Drug-induced liver injury (DILI) was defined based on established criteria.
Results: A total of 270 patients (184 adults and 86 paediatric) received IT-MTX and had available LE data. Aminotransferase elevation was seen post-MTX in 107 (40%) patients, of whom 96 (36%) had ALT and 68 (25%) had AST elevation. DILI occurred in 16 (6%) patients. Aminotransferases peaked a median of 4 (3-5) days post-MTX, returning near baseline by day 7. Paediatric patients had higher incidence of aminotransferase elevations and DILI than adults (ALT 51% vs. 28%; AST 41% vs. 18%; DILI 11% vs. 3%; p < 0.01 for all). No significant predictors of LE elevation or DILI were identified, and no patient developed liver failure. The severity of ALT elevation after the first IT-MTX dose did not predict severity of a subsequent dose.
Conclusion: Acute transient aminotransferase elevation is common after IT-MTX, especially in paediatric patients. Only a fraction of patients developed DILI, which was self-limited with no sensitisation or liver failure.
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http://dx.doi.org/10.1111/liv.70022 | DOI Listing |
Microbiol Spectr
September 2025
The School of Clinical Medicine, Fujian Medical University, Fuzhou, China.
Hepatitis B virus (HBV) infection remains a major global health burden. While interferon-alpha (IFNα) therapy demonstrates antiviral and immunomodulatory effects, reliable prognostic markers for sustained response are needed. Transaminases, hematological parameters, and cytokines may serve as potential predictors, but their dynamic changes during IFNα therapy remain poorly characterized.
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September 2025
Department of Infectious Diseases, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Background: Mucormycosis is a rare, rapidly progressive fungal infection with a high mortality rate. However, clinical data of mucormycosis patients, especially those related to adverse outcomes in China, remain limited.
Objective: To enhance understanding of the clinical characteristics of different infection site mucormycosis and identify the factors associated with adverse outcomes.
Aquac Nutr
August 2025
Guangdong Provincial Key Laboratories of Marine Biotechnology, Shantou University, Shantou 515063, China.
In mammals, cholesterol accumulation in tissues often results in health damage, such as oxidative stress. In contrast, the adverse effects of cholesterol accumulation on the physiological health of fish remain largely unexplored. The present study investigated the impacts of cholesterol accumulation on oxidative stress and the potential mechanisms involved in Nile tilapia ().
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August 2025
Division of Infectious Diseases, Hyogo Prefectural Kobe Children's Hospital, Hyogo, JPN.
Tuberculous meningitis (TBM) is predominantly observed in developing countries but remains relatively rare in developed countries. Therefore, if a clinician does not suspect TBM, its diagnosis may be delayed. Furthermore, drug-induced hepatotoxicity is common and can become severe during TBM treatment.
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August 2025
Public Health Emergency Management Innovation Center, School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, State Key Laboratory of Respiratory Health and Multimorbidity, Key Laboratory of Pathogen Infection Prevention and Control (Pek
Progression of acute respiratory infection (ARI) to pneumonia increases severity and healthcare burden. Limited evidence exists on using machine learning to identify predictors from demographics, clinical, and pathogen detection data. This study aimed to identify pneumonia predictors in ARI patients using machine learning methods.
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