Purpose And Design: This study aimed to evaluate the risk of drug-related dry eye using real-world data, underscoring the significance of tracing pharmacological etiology for distinct clinical types of dry eye.
Methods: Analyzing adverse event reports in the Food and Drug Administration Adverse Event Reporting System (FAERS) from January 2004 to September 2023, we employed disproportionality analysis and the Bayesian confidence propagation neural network algorithm. The analysis involved categorizing drugs causing dry eye, assessing risk levels, and conducting segmental assessments based on the time of onset of drug-related dry eye adverse reactions.
Transl Vis Sci Technol
September 2024
Purpose: This study aimed to assess the drug risk of drug-related keratitis and track the epidemiological characteristics of drug-related keratitis.
Methods: This study analyzed data from the U.S.
Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor prognosis. Despite this, there is a dearth of research utilizing big data to predict UM distant metastasis. This study leveraged machine learning methods on the Surveillance, Epidemiology, and End Results (SEER) database to forecast the risk probability of distant metastasis.
View Article and Find Full Text PDFInt J Ophthalmol
April 2022
Dry eye disease (DED) is one of the most common chronic multifactorial ocular surface diseases with high prevalence and complex pathogenesis. DED results in several ocular discomforts, vision fluctuation, and even potential damage of the ocular surface, bringing heavy burdens both on individuals and the society. The pathology of DED consists of tear film hyperosmolarity and immune responses on the ocular surface.
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