Background: Cough is a prominent symptom of chronic respiratory diseases, including asthma, idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD), and bronchiectasis (BE). Some patients develop chronic cough (CC), defined as lasting more than 8 weeks, yet its characteristics remain poorly understood. This study aimed to characterize CC across various chronic respiratory diseases using validated cough assessment tools. Methods: The Cough Assessment in Chronic Respiratory Diseases (COASESS) study, a multicenter, prospective cross-sectional study, was conducted at 10 university hospitals. CC was evaluated in terms of intensity (numeric rating scale [NRS]), frequency (cough symptom score [CSS]), and quality of life (using the cough assessment test [COAT] and Leicester cough questionnaire [LCQ]). Cough hypersensitivity was assessed with the cough hypersensitivity questionnaire (CHQ). Data on age, sex, and smoking status were also collected. Results: Among the 303 enrolled patients, 266 with chronic respiratory diseases were included in the analysis. Patients with asthma were younger, predominantly female, and non-smokers, whereas those with COPD and IPF were older males who had previously smoked (p<0.001). Scores for COAT, LCQ, NRS, and CSS showed significant differences across the diseases, with asthma and IPF patients experiencing a greater symptom burden and lower quality of life compared to those with COPD or BE (p<0.001). Although CHQ total scores were similar across groups, asthma patients more frequently reported triggers such as talking and post-nasal drip. Conclusion This study revealed distinct characteristics of CC across different chronic respiratory diseases. Asthma and IPF were associated with a higher symptom burden, and cough hypersensitivity varied depending on the underlying condition. These findings highlight the necessity for disease-specific assessments and management strategies for CC.

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: 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: 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: 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: 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: Chronic cough is a common symptom encountered by healthcare practitioners.The global prevalence of chronic cough is 9.6%, with a female predominance. The aim of our study is to reveal the sex differences in prevalence and severity of chronic cough in South Korea, stratified by age and etiology. Methods: This study included adult patients with chronic cough who were recruited from 19 respiratory centers in South Korea. Patients completed the cough numeric rating scale (NRS) and COugh Assessment Test (COAT) questionnaire to assess the severity and multidimensional impact of cough. Results: Among the 625 patients, 419 (67.0%) were females, with a male-to-female ratio of 1:2.03. The mean age was 49.4 years, and the median duration of cough was 12 weeks. The mean NRS and COAT scores were 5.5 ± 1.8 and 9.5 ± 3.6, respectively. Female patients were older (45.3 ± 15.4 vs. 51.6 ± 15.2, P < 0.001) and more likely to have asthma/cough variant asthma (CVA) (26.7% vs. 40.8%, P = 0.001) than male patients. There was no difference in the duration or severity of cough between sexes, regardless of the cause. The male-tofemale ratio was lower for upper airway cough syndrome (UACS), asthma/CVA, and gastroesophageal reflux disease (GERD), but not for eosinophilic bronchitis (EB) or unexplained cough. The mean age of female patients was higher in UACS and asthma/CVA, but not in EB, GERD, or unexplained cough. The majority (24.2%) fell within the age category of 50s. The proportion of females with cough increased with age, with a significant rise in the 50s, 60s, and 70–89 age groups. The severity of cough decreased in the 50s, 60s, and 70–89 age groups, with no significant sex differences within the same age group. Conclusion The sex disparities in prevalence and severity of cough varied significantly depending on the age category and etiology. Understanding the specific sex-based difference could enhance comprehension of cough-related pathophysiology and treatment strategies.

Cough is the most common respiratory symptom that can have various causes. It is a major clinical problem that can reduce a patient’s quality of life. Thus, clinical guidelines for the treatment of cough were established in 2014 by the cough guideline committee under the Korean Academy of Tuberculosis and Respiratory Diseases. From October 2018 to July 2020, cough guidelines were revised by members of the committee based on the first guidelines. The purpose of these guidelines is to help clinicians efficiently diagnose and treat patients with cough. This article highlights the recommendations and summary of the revised Korean cough guidelines. It includes a revised algorithm for the evaluation of acute, subacute, and chronic cough. For a chronic cough, upper airway cough syndrome (UACS), cough variant asthma (CVA), and gastroesophageal reflux disease (GERD) should be considered in differential diagnoses. If UACS is suspected, first-generation antihistamines and nasal decongestants can be used empirically. In cases with CVA, inhaled corticosteroids are recommended to improve cough. In patients with suspected chronic cough due to symptomatic GERD, proton pump inhibitors are recommended. Chronic bronchitis, bronchiectasis, bronchiolitis, lung cancer, aspiration, intake of angiotensin-converting enzyme inhibitor, intake of dipeptidyl peptidase-4 inhibitor, habitual cough, psychogenic cough, interstitial lung disease, environmental and occupational factors, tuberculosis, obstructive sleep apnea, peritoneal dialysis, and unexplained cough can also be considered as causes of a chronic cough. Chronic cough due to laryngeal dysfunction syndrome has been newly added to the guidelines.

Cough is the most common respiratory symptom that can have various causes. It is a major clinical problem that can reduce a patient’s quality of life. Thus, clinical guidelines for the treatment of cough were established in 2014 by the cough guideline committee under the Korean Academy of Tuberculosis and Respiratory Diseases. From October 2018 to July 2020, cough guidelines were revised by members of the committee based on the first guidelines. The purpose of these guidelines is to help clinicians efficiently diagnose and treat patients with cough. This article highlights the recommendations and summary of the revised Korean cough guidelines. It includes a revised algorithm for the evaluation of acute, subacute, and chronic cough. For a chronic cough, upper airway cough syndrome (UACS), cough variant asthma (CVA), and gastroesophageal reflux disease (GERD) should be considered in differential diagnoses. If UACS is suspected, first-generation antihistamines and nasal decongestants can be used empirically. In cases with CVA, inhaled corticosteroids are recommended to improve cough. In patients with suspected chronic cough due to symptomatic GERD, proton pump inhibitors are recommended. Chronic bronchitis, bronchiectasis, bronchiolitis, lung cancer, aspiration, intake of angiotensin-converting enzyme inhibitor, intake of dipeptidyl peptidase-4 inhibitor, habitual cough, psychogenic cough, interstitial lung disease, environmental and occupational factors, tuberculosis, obstructive sleep apnea, peritoneal dialysis, and unexplained cough can also be considered as causes of a chronic cough. Chronic cough due to laryngeal dysfunction syndrome has been newly added to the guidelines.

Asthma ; Bronchitis ; Cohort Studies ; Cough ; Diagnosis ; Disease Management ; Eosinophils ; Epidemiology ; Female ; Gastroesophageal Reflux ; Humans ; Korea ; Lung Diseases ; Multivariate Analysis ; Observational Study ; Pregnant Women ; Retrospective Studies ; Tuberculosis