Clinical Characterization of Inpatients with Acute Conjunctivitis: A Retrospective Analysis by Natural Language Processing and Machine Learning
نویسندگان
چکیده
Background Acute bacterial conjunctivitis (ABC) is a relatively common medical condition caused by different pathogens. Although it rarely threatens vision, one of the most conditions that cause red eyes and may be accompanied discomfort discharge. The study aimed to identify characterize inpatients with ABC treated topical antibiotics. Methods EHRead® technology, based on natural language processing (NLP) machine learning, was used extract analyze clinical information in electronic health records (EHRs) antibiotic-treated patients admitted five hospitals Spain between January 2014 December 2018. Categorical variables were described frequency, whereas numerical included mean, standard deviation, median, quartiles. Results From source population 2,071,812 adult who attended participating period, 11,110 diagnosed acute identified. Six thousand hundred eighty-three antibiotics, comprising final population. Microbiology tested only 12.1% patients. Antibiotics, mainly tobramycin, corticosteroids, dexamethasone, usually prescribed. NSAIDs also about 50% patients, always combined Conclusions present provided realistic representation hospital practice concerning managing conjunctivitis. diagnosis ground, microbiology tested, few bacteria species are involved, local antibiotics frequently associated corticosteroids and/or NSAIDs. Moreover, this clinically relevant outcomes, new could applied practice.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2022
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app122312352