PURPOSE: The objective of this study was to compare the clinical characteristics of influenza A and B infections and analyze the effect of oseltamivir in hospitalized children. METHODS: We investigated children under the age of 15, who were diagnosed with influenza A/H1N1, A/H3N2, or B from January to April 2014. The subjects were admitted to the Changwon Fatima Hospital and diagnosed using a rapid antigen test from nasopharyngeal swabs. The medical records of the patients were retrospectively reviewed. RESULTS: A total of 302 pediatric patients with influenza were enrolled. Influenza B infection was the most common type (n=187, 61.9%), followed by A/H3N2 (n=100, 33.1%) and A/H1N1 (n=15, 5.0%). Compared to patients diagnosed with influenza A, patients diagnosed with influenza B were older (P=0.005), and the duration of fever was significantly longer (P=0.001). A total of 161 patients (53.3%) had been vaccinated against influenza during the season, before admission. Among the patients infected with A/H3N2 and B, the duration of fever was shorter in oseltamivir recipients compared to oseltamivir non-recipients (P=0.026 and P=0.004, respectively). CONCLUSIONS: There were significant differences between influenza A and B groups in terms of age, demographics, and clinical course. Although the effectiveness of oseltamivir on influenza differs according to the type of influenza, our data provides evidence that oseltamivir is beneficial for both A and B infections.
Child ; Child, Hospitalized* ; Demography ; Fever ; Gyeongsangnam-do ; Herpesvirus 1, Cercopithecine* ; Humans ; Influenza, Human* ; Medical Records ; Oseltamivir ; Retrospective Studies ; Seasons

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.