Antituberculosis drug-induced liver injury (ATLI) is a major adverse effect during antituberculosis treatment. Early detection or prediction is essential to prevent ATLI in antituberculosis treatment patients. The purpose of this work is to explore the relationship between alanine aminotransferase (ALT) trajectories within 15 days of initial treatment and the risk of ATLI. Based on a historical cohort of patients hospitalized for antituberculosis treatment and group-based trajectory modeling analysis, ALT trajectories within 15 days of initial treatment were determined. Conditional logistic regression model was used to estimate the association between different ALT trajectories and the risk of ATLI, and the corresponding odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated with covariates. Based on the ALT levels within 15 days of initial treatment, a total of 853 patients were divided into four ALT trajectories. The incidence of ATLI significantly increased with the increase of ALT trajectories (2.33%, 4.38%, 5.90%, and 2.44%, respectively). Compared with trajectory 1, the adjusted OR for ATLI in trajectory 2, trajectory 3, and trajectory 4 were 2.448 (95% CI: 0.302-19.856, P = 0.402), 5.373 (95% CI: 0.636-45.411, P = 0.123), 11.010 (95% CI: 0.720-168.330, P = 0.085), respectively, and there was an increasing trend of ATLI risk (P = 0.015). Different ALT trajectories within 15 days of initial treatment were associated with different risk of ATLI, and it is necessary to pay attention to the ALT trajectory within 15 days of initial treatment to predict the occurrence of ATLI.
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http://dx.doi.org/10.1002/jcph.2422 | DOI Listing |
Ann Med
December 2025
Institute of Clinical Virology, Department of Infectious Diseases, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Objective: We aimed at identifying acute phase biomarkers in Severe Fever with Thrombocytopenia Syndrome (SFTS), and to establish a model to predict mortality outcomes.
Methods: A retrospective analysis was conducted on multicenter clinical data. Group-based trajectory modeling (GBTM) was utilized to demonstrate the overall trend of laboratory indicators and their correlation with mortality.
Heliyon
November 2024
Centre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 10029, China.
Soc Sci Med
December 2024
Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Guangzhou, 510631, PR China. Electronic address:
This study examined three models (relationship-driven model, symptom-driven model and transactional model) testing the across-time bidirectional relations between psychological maltreatment by teachers and early adolescents' psychosocial adjustment (i.e., internalizing problems, externalizing problems, and academic achievement) during early adolescence.
View Article and Find Full Text PDFAnn Hematol
December 2024
Pediatric Intensive Care Unit, Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan Children's Hospital), Changsha, China.
Understanding the early features and characteristics of hemophagocytic lymphohistiocytosis (HLH) is essential for identifying high-risk individuals and also providing valuable pathological insights. This study aims to investigate the characteristics and trends of blood and hepatic parameters before an HLH diagnosis was established. Longitudinal hematological and hepatic test results from pediatric patients with HLH and an age- and sex-matched control group were analyzed.
View Article and Find Full Text PDFAliment Pharmacol Ther
December 2024
Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA.
Background And Aims: Machine learning (ML) can identify the hidden patterns without hypothesis in heterogeneous diseases like acute-on-chronic live failure (ACLF). We employed ML to describe and predict yet unknown clusters in ACLF.
Methods: Clinical data of 1568 patients with ACLF from a tertiary care centre (2015-2023) were subjected to distance-, density- and model-based clustering algorithms.
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