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Clinical characteristics and cause analysis of false-positive results in treponemal testing among patients.
Ann Med
December 2025
Department of Blood Transfusion, Medicine School of Medicine Jinling Hospital Nanjing University, Nanjing, China.
Background: Currently, there is a dearth of systematic research data on the phenomenon of false-positive reactions in treponemal tests. The aim of this study is to analyze the clinical characteristics and influencing factors associated with false-positive treponemal tests in patients, so as to enhance the diagnostic accuracy of syphilis and mitigate misdiagnosis-induced incorrect treatment.
Methods: From January 2017 to December 2023, a total of 759 cases with false-positive results for treponema were screened for blood transfusion, surgery, or other medical interventions at Jinling hospital.
A reproducible framework for monitoring the impact of randomized clinical trials on clinical practice using large-scale real-world data: application to gynaecological surgical trials using the French national healthcare database.
EClinicalMedicine
February 2025
Department of Breast and Gynaecological Surgery, Institut Curie, Paris, France.
Background: Randomized clinical trials (RCTs) are fundamental to evidence-based medicine, but their real-world impact on clinical practice often remains unmonitored. Leveraging large-scale real-world data can enable systematic monitoring of RCT effects. We aimed to develop a reproducible framework using real-world data to assess how major RCTs influence medical practice, using two pivotal surgical RCTs in gynaecologic oncology as an example-the LACC (Laparoscopic Approach to Cervical Cancer) and LION (Lymphadenectomy in Ovarian Neoplasms) trials.
View Article and Find Full Text PDFGlobal, regional, national burden of asthma from 1990 to 2021, with projections of incidence to 2050: a systematic analysis of the global burden of disease study 2021.
EClinicalMedicine
February 2025
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Background: Asthma is the second leading cause of mortality among chronic respiratory illnesses. This study provided a comprehensive analysis of the burden of asthma.
Methods: Data on asthma were extracted from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021.
AI-assisted exposure-response data analysis: Quantifying heterogeneous causal effects of exposures on survival times.
Glob Epidemiol
June 2025
Business Analytics (BANA) Program, Business School, University of Colorado, 1475 Lawrence St. Denver, CO 80217-3364, USA.
AI-assisted data analysis can help risk analysts better understand exposure-response relationships by making it relatively easy to apply advanced statistical and machine learning methods, check their assumptions, and interpret their results. This paper demonstrates the potential of large language models (LLMs), such as ChatGPT, to facilitate statistical analyses, including survival data analyses, for health risk assessments. Through AI-guided analyses using relatively recent and advanced methods such as Individual Conditional Expectation (ICE) plots using Random Survival Forests and Heterogeneous Treatment Effects (HTEs) estimated using Causal Survival Forests, population-level exposure-response functions can be disaggregated into individual-level exposure-response functions.
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