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Background/Aims The prognosis of patients with idiopathic pulmonary fibrosis (IPF) and respiratory failure requiring mechanical ventilation is poor. Therefore, mechanical ventilation is not recommended. Recently, outcomes of mechanical ventilation, including those for patients with IPF, have improved. The aim of this study was to investigate changes in the use of mechanical ventilation in patients with IPF and their outcomes over time. Methods This retrospective, observational cohort study used data from the National Health Insurance Service database. Patients diagnosed with IPF between January 2011 and December 2019 who were placed on mechanical ventilation were included. We analyzed changes in the use of mechanical ventilation in patients with IPF and their mortality using the Cochran-Armitage trend test. Results Between 2011 and 2019, 1,227 patients with IPF were placed on mechanical ventilation. The annual number of patients with IPF with and without mechanical ventilation increased over time. However, the ratio was relatively stable at approximately 3.5%. The overall hospital mortality rate was 69.4%. There was no improvement in annual hospital mortality rate. The overall 30-day mortality rate was 68.7%, which did not change significantly. The overall 90-day mortality rate was 85.3%. The annual 90-day mortality rate was decreased from 90.9% in 2011 to 83.1% in 2019 (p = 0.028). Conclusions Despite improvements in intensive care and ventilator management, the prognosis of patients with IPF receiving mechanical ventilation has not improved significantly.

IntroductionEngaging diverse participants is vital to precision medicine (PM) but has been limited by low knowledge and concerns about various issues related to PM research. News media is an important channel of information that can shape public understanding and perception of PM. However, how PM is represented in news media has not been sufficiently understood.MethodsThe study used quantitative content analysis to evaluate the portrayal of PM in US print news media between 2015 and 2021 (N = 198). Three domains of factors related to PM portrayed in news articles were coded: (1) characteristics of PM, (2) target diseases of PM and their related characteristics, and (3) non-scientific news frames.ResultsThere was considerable news coverage of the treatment benefits of PM, especially for cancer. Potential risks or concerns, non-cancer diseases, and non-treatment issues that could be important to diverse populations were less covered. News articles frequently cited scientists, patients, and government officials with different focuses on PM.DiscussionThe study highlighted the need for accurate and complete information about PM in news media for diverse participants. News media should actively explore social, ethical, and legal issues to support the engagement of diverse populations.

Respiratory diseases significantly affect respiratory function, making them a considerable contributor to global mortality. The respiratory muscles play an important role in disease prognosis; as such, quantitative analysis of the respiratory muscles is crucial to assess the status of the respiratory system and the quality of life in patients. In this study, we aimed to develop an automated approach for the segmentation and classification of three types of respiratory muscles from computed tomography (CT) images using artificial intelligence. With a dataset of approximately 600,000 thoracic CT images from 3,200 individuals, we trained the model using the Attention U-Net architecture, optimized for detailed and focused segmentation. Subsequently, we calculated the volumes and densities from the muscle masks segmented by our model and performed correlation analysis with pulmonary function test (PFT) parameters. The segmentation models for muscle tissue and respiratory muscles obtained dice scores of 0.9823 and 0.9688, respectively. The classification model, achieving a generalized dice score of 0.9900, also demonstrated high accuracy in classifying thoracic region muscle types, as evidenced by its F1 scores: 0.9793 for the pectoralis muscle, 0.9975 for the erector spinae muscle, and 0.9839 for the intercostal muscle. In the correlation analysis, the volume of the respiratory muscles showed a strong correlation with PFT parameters, suggesting that respiratory muscle volume may serve as a potential novel biomarker for respiratory function. Although muscle density showed a weaker correlation with the PFT parameters, it has a potential significance in medical research.