Jiyoung Lee, Minwoo Kim, Seungho Kim, Junghwan Kim, Seunghyun Won, Hwaran Lee, Edward Choi. Findings of the Association for Computational Linguistics ACL 2024. 2024.

Bacterial pneumonia occurring after respiratory viral infection is common. However, the predominant bacterial species causing pneumonia secondary to respiratory viral infections other than influenza remain unknown. The purpose of this study was to know whether the pathogens causing post-viral bacterial pneumonia vary according to the type of respiratory virus. Study subjects were 5,298 patients, who underwent multiplex real-time polymerase chain reaction for simultaneous detection of respiratory viruses, among who visited the emergency department or outpatient clinic with respiratory symptoms at Ulsan University Hospital between April 2013 and March 2016. The patients' medical records were retrospectively reviewed. A total of 251 clinically significant bacteria were identified in 233 patients with post-viral bacterial pneumonia. Mycoplasma pneumoniae was the most frequent bacterium in patients aged <16 years, regardless of the preceding virus type (p=0.630). In patients aged ≥16 years, the isolated bacteria varied according to the preceding virus type. The major results were as follows (p<0.001): pneumonia in patients with influenza virus (type A/B), rhinovirus, and human metapneumovirus infections was caused by similar bacteria, and the findings indicated that Staphylococcus aureus pneumonia was very common in these patients. In contrast, coronavirus, parainfluenza virus, and respiratory syncytial virus infections were associated with pneumonia caused by gram-negative bacteria. The pathogens causing post-viral bacterial pneumonia vary according to the type of preceding respiratory virus. This information could help in selecting empirical antibiotics in patients with post-viral pneumonia.

Jae Hyup Jung, Seung Hyun Won, Kwangrok Jung, Jun Suh Lee, Jong-Chan Lee, Jin Won Kim, Yoo‑Seok Yoon, Jin-Hyeok Hwang, Ho‑Seong Han, Jaihwan Kim. Gut and Liver 2024;18:737-46. https://doi.org/10.5009/gnl230303

Sun-A Lee, Yang-Jin Yi, Seunghyun Won, Na-Hee Chang, Jong-Hee Kim. JKAOMS 2025;51:17-25. https://doi.org/10.5125/jkaoms.2025.51.1.17

Evaluation of sustainability after quality improvement (QI) projects in healthcare settings is an essential part of monitoring and future QI planning. With limitations in adopting quasi-experimental study design in real-world practice, healthcare professionals find it challenging to present the sustained effect of QI changes effectively. To provide quantitative methodological approaches for demonstrating the sustainability of QI projects for healthcare professionals, we conducted data analyses based on a QI project to improve the computerized provider order entry system to reduce patients’ dosing frequencies in Korea. Data were collected for 5 years: 24-month pre-intervention, 12-month intervention, and 24-month post-intervention. Then, analytic approaches including control chart, Analysis of Variance (ANOVA), and segmented regression were performed. The control chart intuitively displayed how the outcomes changed over the entire period, and ANOVA was used to test whether the outcomes differed between groups. Last, segmented regression analysis was conducted to evaluate longitudinal effects of interventions over time. We found that the impact of QI projects in healthcare settings should be initiated following the Plan–Do–Study–Act cycle and evaluated long-term effects while widening the scope of QI evaluation with sustainability. This study can serve as a guide for healthcare professionals to use a number of statistical methodologies in their QI evaluations.

The dietary carbohydrate-to-fiber ratio (CFR) provides a comprehensive measure of carbohydrate quality; however, its association with cognitive outcomes re