Background/Aims: Chronic obstructive pulmonary disease (COPD) management guidelines have increasingly emphasised the importance of exacerbation prevention, and the role of blood eosinophil count (BEC) as a biomarker for inhaled corticosteroids (ICS) response. This study aimed to describe the distribution and stability of BEC and understand real-world treatment patterns among COPD patients in South Korea. Methods: This was a retrospective database analysis using data obtained from the KOrea COPD Subgroup Study (KOCOSS) registry between January 2012 and August 2018. KOCOSS is an ongoing, longitudinal, prospective, multi-centre, non-interventional study investigating early COPD amongst South Korean patients. BEC stability was assessed by calculating the intra-class correlation (ICC) coefficient. “Exacerbators” were patients who had a record of ≥ 1 exacerbation in the 12 months prior to the visit. Results: The study included 2,661 patients with a mean age of 68.6 years. Most patients were male (92.0%). Mean BEC was significantly higher in exacerbators compared to non-exacerbators. Patients with ≥ 2 exacerbations at baseline had a less stable BEC over time (ICC = 0.44) compared to non-exacerbators (ICC = 0.57). Patients with BEC ≥ 300 cells/μL at baseline predominantly received triple therapy (43.8%). Conclusions This study may further develop current understanding on BEC profiles amongst COPD patients in South Korea. BEC measurements are stable and reproducible among COPD patients, which supports its use as a potential biomarker.

Background: Respiratory infections play a major role in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study assessed the prevalence of bacterial and viral pathogens and their clinical impact on patients with AECOPD. Methods: This retrospective study included 1,186 patients diagnosed with AECOPD at 28 hospitals in South Korea between 2015 and 2018. We evaluated the identification rates of pathogens, basic patient characteristics, clinical features, and the factors associated with infections by potentially drug-resistant (PDR) pathogens using various microbiological tests. Results: Bacteria, viruses, and both were detected in 262 (22.1%), 265 (22.5%), and 129 (10.9%) of patients, respectively. The most common pathogens included Pseudomonas aeruginosa (17.8%), Mycoplasma pneumoniae (11.2%), Streptococcus pneumoniae (9.0%), influenza A virus (19.0%), rhinovirus (15.8%), and respiratory syncytial virus (6.4%). Notably, a history of pulmonary tuberculosis (odds ratio [OR], 1.66; p=0.046), bronchiectasis (OR, 1.99; p=0.032), and the use of a triple inhaler regimen within the past 6 months (OR, 2.04; p=0.005) were identified as significant factors associated with infection by PDR pathogens. Moreover, patients infected with PDR pathogens exhibited extended hospital stays (15.9 days vs. 12.4 days, p=0.018) and higher intensive care unit admission rates (15.9% vs. 9.5%, p=0.030). Conclusion This study demonstrates that a variety of pathogens are involved in episodes of AECOPD. Nevertheless, additional research is required to confirm their role in the onset and progression of AECOPD.

Background: Computed tomography (CT) scans are utilized to assess emphysema, a prominent phenotype of chronic obstructive pulmonary disease (COPD). Variability in CT protocols and equipment across hospitals can impact accuracy. This study aims to implement kernel conversion across different CT settings and evaluate changes in the correlation between the emphysema index pre- and post-kernel conversion, along with clinical measures in COPD patients. Methods: Data were extracted from the Korea COPD Subgroup Study database, which included CT scan images from 484 COPD patients. These images underwent kernel conversion. Emphysema extent was quantified using the percentage of low-attenuation areas (%LAA-950) determined by a deep learning-based program. The correlation between %LAA-950 and clinical parameters, including lung function tests, the modified Medical Research Council (mMRC), 6-minute walking distance (6MWD), COPD assessment test (CAT), and the St. George’s Respiratory Questionnaire for COPD (SGRQ-c), was analyzed. Subsequently, these values were compared across various CT settings. Results: A total of 484 participants were included. Kernel conversion significantly reduced the variance in %LAA-950 values (before vs. after: 12.6±11.0 vs. 8.8±11.9). Post-kernel conversion, %LAA-950 demonstrated moderate correlations with forced expiratory volume in 1 second (r=–0.41), residual volume/total lung capacity (r=0.42), mMRC (r=0.25), CAT score (r=0.12), SGRQ-c (r=0.21), and 6MWD (r=0.15), all of which were improved compared to the unconverted dataset (all p<0.01). Conclusion CT images processed through kernel conversion enhance the correlation between the extent of emphysema and clinical parameters in COPD.

Background/Aims: Chronic obstructive pulmonary disease (COPD) management guidelines have increasingly emphasised the importance of exacerbation prevention, and the role of blood eosinophil count (BEC) as a biomarker for inhaled corticosteroids (ICS) response. This study aimed to describe the distribution and stability of BEC and understand real-world treatment patterns among COPD patients in South Korea. Methods: This was a retrospective database analysis using data obtained from the KOrea COPD Subgroup Study (KOCOSS) registry between January 2012 and August 2018. KOCOSS is an ongoing, longitudinal, prospective, multi-centre, non-interventional study investigating early COPD amongst South Korean patients. BEC stability was assessed by calculating the intra-class correlation (ICC) coefficient. “Exacerbators” were patients who had a record of ≥ 1 exacerbation in the 12 months prior to the visit. Results: The study included 2,661 patients with a mean age of 68.6 years. Most patients were male (92.0%). Mean BEC was significantly higher in exacerbators compared to non-exacerbators. Patients with ≥ 2 exacerbations at baseline had a less stable BEC over time (ICC = 0.44) compared to non-exacerbators (ICC = 0.57). Patients with BEC ≥ 300 cells/μL at baseline predominantly received triple therapy (43.8%). Conclusions This study may further develop current understanding on BEC profiles amongst COPD patients in South Korea. BEC measurements are stable and reproducible among COPD patients, which supports its use as a potential biomarker.

Background: Respiratory infections play a major role in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study assessed the prevalence of bacterial and viral pathogens and their clinical impact on patients with AECOPD. Methods: This retrospective study included 1,186 patients diagnosed with AECOPD at 28 hospitals in South Korea between 2015 and 2018. We evaluated the identification rates of pathogens, basic patient characteristics, clinical features, and the factors associated with infections by potentially drug-resistant (PDR) pathogens using various microbiological tests. Results: Bacteria, viruses, and both were detected in 262 (22.1%), 265 (22.5%), and 129 (10.9%) of patients, respectively. The most common pathogens included Pseudomonas aeruginosa (17.8%), Mycoplasma pneumoniae (11.2%), Streptococcus pneumoniae (9.0%), influenza A virus (19.0%), rhinovirus (15.8%), and respiratory syncytial virus (6.4%). Notably, a history of pulmonary tuberculosis (odds ratio [OR], 1.66; p=0.046), bronchiectasis (OR, 1.99; p=0.032), and the use of a triple inhaler regimen within the past 6 months (OR, 2.04; p=0.005) were identified as significant factors associated with infection by PDR pathogens. Moreover, patients infected with PDR pathogens exhibited extended hospital stays (15.9 days vs. 12.4 days, p=0.018) and higher intensive care unit admission rates (15.9% vs. 9.5%, p=0.030). Conclusion This study demonstrates that a variety of pathogens are involved in episodes of AECOPD. Nevertheless, additional research is required to confirm their role in the onset and progression of AECOPD.

Background: Computed tomography (CT) scans are utilized to assess emphysema, a prominent phenotype of chronic obstructive pulmonary disease (COPD). Variability in CT protocols and equipment across hospitals can impact accuracy. This study aims to implement kernel conversion across different CT settings and evaluate changes in the correlation between the emphysema index pre- and post-kernel conversion, along with clinical measures in COPD patients. Methods: Data were extracted from the Korea COPD Subgroup Study database, which included CT scan images from 484 COPD patients. These images underwent kernel conversion. Emphysema extent was quantified using the percentage of low-attenuation areas (%LAA-950) determined by a deep learning-based program. The correlation between %LAA-950 and clinical parameters, including lung function tests, the modified Medical Research Council (mMRC), 6-minute walking distance (6MWD), COPD assessment test (CAT), and the St. George’s Respiratory Questionnaire for COPD (SGRQ-c), was analyzed. Subsequently, these values were compared across various CT settings. Results: A total of 484 participants were included. Kernel conversion significantly reduced the variance in %LAA-950 values (before vs. after: 12.6±11.0 vs. 8.8±11.9). Post-kernel conversion, %LAA-950 demonstrated moderate correlations with forced expiratory volume in 1 second (r=–0.41), residual volume/total lung capacity (r=0.42), mMRC (r=0.25), CAT score (r=0.12), SGRQ-c (r=0.21), and 6MWD (r=0.15), all of which were improved compared to the unconverted dataset (all p<0.01). Conclusion CT images processed through kernel conversion enhance the correlation between the extent of emphysema and clinical parameters in COPD.

Background/Aims: Chronic obstructive pulmonary disease (COPD) management guidelines have increasingly emphasised the importance of exacerbation prevention, and the role of blood eosinophil count (BEC) as a biomarker for inhaled corticosteroids (ICS) response. This study aimed to describe the distribution and stability of BEC and understand real-world treatment patterns among COPD patients in South Korea. Methods: This was a retrospective database analysis using data obtained from the KOrea COPD Subgroup Study (KOCOSS) registry between January 2012 and August 2018. KOCOSS is an ongoing, longitudinal, prospective, multi-centre, non-interventional study investigating early COPD amongst South Korean patients. BEC stability was assessed by calculating the intra-class correlation (ICC) coefficient. “Exacerbators” were patients who had a record of ≥ 1 exacerbation in the 12 months prior to the visit. Results: The study included 2,661 patients with a mean age of 68.6 years. Most patients were male (92.0%). Mean BEC was significantly higher in exacerbators compared to non-exacerbators. Patients with ≥ 2 exacerbations at baseline had a less stable BEC over time (ICC = 0.44) compared to non-exacerbators (ICC = 0.57). Patients with BEC ≥ 300 cells/μL at baseline predominantly received triple therapy (43.8%). Conclusions This study may further develop current understanding on BEC profiles amongst COPD patients in South Korea. BEC measurements are stable and reproducible among COPD patients, which supports its use as a potential biomarker.

Background: Respiratory infections play a major role in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study assessed the prevalence of bacterial and viral pathogens and their clinical impact on patients with AECOPD. Methods: This retrospective study included 1,186 patients diagnosed with AECOPD at 28 hospitals in South Korea between 2015 and 2018. We evaluated the identification rates of pathogens, basic patient characteristics, clinical features, and the factors associated with infections by potentially drug-resistant (PDR) pathogens using various microbiological tests. Results: Bacteria, viruses, and both were detected in 262 (22.1%), 265 (22.5%), and 129 (10.9%) of patients, respectively. The most common pathogens included Pseudomonas aeruginosa (17.8%), Mycoplasma pneumoniae (11.2%), Streptococcus pneumoniae (9.0%), influenza A virus (19.0%), rhinovirus (15.8%), and respiratory syncytial virus (6.4%). Notably, a history of pulmonary tuberculosis (odds ratio [OR], 1.66; p=0.046), bronchiectasis (OR, 1.99; p=0.032), and the use of a triple inhaler regimen within the past 6 months (OR, 2.04; p=0.005) were identified as significant factors associated with infection by PDR pathogens. Moreover, patients infected with PDR pathogens exhibited extended hospital stays (15.9 days vs. 12.4 days, p=0.018) and higher intensive care unit admission rates (15.9% vs. 9.5%, p=0.030). Conclusion This study demonstrates that a variety of pathogens are involved in episodes of AECOPD. Nevertheless, additional research is required to confirm their role in the onset and progression of AECOPD.

Background: Computed tomography (CT) scans are utilized to assess emphysema, a prominent phenotype of chronic obstructive pulmonary disease (COPD). Variability in CT protocols and equipment across hospitals can impact accuracy. This study aims to implement kernel conversion across different CT settings and evaluate changes in the correlation between the emphysema index pre- and post-kernel conversion, along with clinical measures in COPD patients. Methods: Data were extracted from the Korea COPD Subgroup Study database, which included CT scan images from 484 COPD patients. These images underwent kernel conversion. Emphysema extent was quantified using the percentage of low-attenuation areas (%LAA-950) determined by a deep learning-based program. The correlation between %LAA-950 and clinical parameters, including lung function tests, the modified Medical Research Council (mMRC), 6-minute walking distance (6MWD), COPD assessment test (CAT), and the St. George’s Respiratory Questionnaire for COPD (SGRQ-c), was analyzed. Subsequently, these values were compared across various CT settings. Results: A total of 484 participants were included. Kernel conversion significantly reduced the variance in %LAA-950 values (before vs. after: 12.6±11.0 vs. 8.8±11.9). Post-kernel conversion, %LAA-950 demonstrated moderate correlations with forced expiratory volume in 1 second (r=–0.41), residual volume/total lung capacity (r=0.42), mMRC (r=0.25), CAT score (r=0.12), SGRQ-c (r=0.21), and 6MWD (r=0.15), all of which were improved compared to the unconverted dataset (all p<0.01). Conclusion CT images processed through kernel conversion enhance the correlation between the extent of emphysema and clinical parameters in COPD.

Background: The diagnosis of tuberculous pleural effusion (TPE) often relies on pleural fluid adenosine deaminase (ADA) levels. The diagnostic utility of ADA, however, is influenced by the prevalence of tuberculosis (TB) in local populations. Malignant pleural effusion (MPE) cases can exhibit moderately elevated ADA levels comparable to those seen in TPE. As population aging potentially impacts ADA levels, global TB incidence is decreasing whereas the burden of malignancy is on the rise. Consequently, epidemiological shifts and temporal changes in ADA distribution complicate the differential diagnosis between TPE and MPE when ADA levels are within the 40–70 IU/L range. Nonetheless, data specific to this subset are scarce. Methods: This retrospective study included consecutive patients aged > 18 years with confirmed TPE and MPE, spanning from 2012 to 2023. ADA levels in pleural fluid were categorized into three groups: < 40 IU/L, 40–70 IU/L, and > 70 IU/L. The study examined annual trends in the frequency of new cases and ADA level distributions over time and identified discriminating factors between TPE and MPE in cases with ADA levels of 40–70 IU/L. Results: In total, 297 TPE and 369 MPE cases were included in this study. Over the study period, the frequency of TPE progressively declined, while that of MPE increased. In the most recent four-year period, new TPE and MPE cases with ADA levels of 40–70 IU/L occurred at comparable numbers. Multivariable analysis identified pleural fluid carcinoembryonic antigen (CEA) levels and the number of focal pleural nodules as independent predictors for MPE. Specifically, the presence of either CEA levels > 15.7 ng/mL or more than eight pleural nodules yielded the highest diagnostic accuracy with a sensitivity of 88%, specificity of 100%, and an area under the curve of 0.95. Conclusion The differential diagnosis between TPE and MPE with pleural ADA levels of 40–70 IU/L has become increasingly critical due to evolving epidemiological patterns and ADA distribution changes over time. Pleural fluid CEA levels and the characteristics of pleural nodules may offer valuable guidance in distinguishing between TPE and MPE within this diagnostic gray zone.