Background: The Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines for chronic obstructive pulmonary disease (COPD) recommend considering patient preference when choosing an inhaler device. However, few studies have assessed both inhaler satisfaction and factors associated with high inhaler satisfaction. Therefore, we assessed inhaler satisfaction and determinants of high satisfaction in Korean COPD patients. Methods: COPD patients were prospectively enrolled from January 2018 to November 2019. The 308 inhalers used by the 261 participants in this study included dry powder inhalers (Turbuhaler, Breezhaler, Ellipta, Diskus, and Genuair), a soft mist inhaler (Respimat), and pressurized metered dose inhalers (pMDIs). Inhaler satisfaction was assessed by the Feeling of Satisfaction with Inhaler (FSI-10) questionnaire. High inhaler satisfaction was defined as an FSI-10 ≥ 43. Results: Among 261 COPD patients, 163 (62.5%) were highly satisfied with their inhaler device. The rates of high inhaler satisfaction for Turbuhaler, Breezhaler, Ellipta, Diskus, Genuair, Respimat, and pMDI usage were 40.0%, 67.2%, 66.7%, 50.0%, 55.6%, 63.4%, and 45.0%, respectively (P = 0.215). In univariate analyses, higher body mass index, non-current smoker, GOLD grades I and II, a modified Medical Research Council (mMRC) score < 2, lower inhaler puff burden, once daily usage of inhaler, and good inhaler adherence were associated with high inhaler satisfaction. In multivariate analyses, an mMRC score < 2, and good inhaler adherence were independently associated with high inhaler satisfaction. Conclusion High inhaler satisfaction was associated with dyspnea symptom and good inhaler adherence in COPD patients. Effective strategies are needed including appropriate inhaler device selection, consideration of patient preference, and repeated inhaler education to improve patient satisfaction of inhalers.

Background: Radial probe endobronchial ultrasound-guided transbronchial lung biopsy (RP-EBUS-TBLB) has improved the diagnostic yield of bronchoscopic biopsy of peripheral pulmonary lesions (PPLs). The diagnostic yield and complications of RP-EBUS-TBLB for PPLs vary depending on the technique, such as using a guide sheath (GS) or fluoroscopy. In this study, we investigated the utility of RP-EBUS-TBLB using a GS without fluoroscopy for diagnosing PPLs. Methods: We retrospectively reviewed data from 607 patients who underwent RP-EBUS of PPLs from January 2019 to July 2020. TBLB was performed using RP-EBUS with a GS without fluoroscopy. The diagnostic yield and complications were assessed. Multivariable logistic regression analyses were used to identify factors affecting the diagnostic yields. Results: The overall diagnostic accuracy was 76.1% (462/607). In multivariable analyses, the size of the lesion (≥20 mm; odds ratio [OR], 2.06; 95% confidence interval [CI], 1.27–3.33; p=0.003), positive bronchus sign in chest computed tomography (OR, 2.30; 95% CI, 1.40–3.78; p=0.001), a solid lesion (OR, 2.40; 95% CI, 1.31–4.41; p=0.005), and an EBUS image with the probe within the lesion (OR, 6.98; 95% CI, 4.38–11.12; p<0.001) were associated with diagnostic success. Pneumothorax occurred in 2.0% (12/607) of cases and chest tube insertion was required in 0.5% (3/607) of patients. Conclusion RP-EBUS-TBLB using a GS without fluoroscopy is a highly accurate diagnostic method in diagnosing PPLs that does not involve radiation exposure and has acceptable complication rates.

Background: Radial probe endobronchial ultrasound-guided transbronchial lung biopsy (RP-EBUS-TBLB) has improved the diagnostic yield of bronchoscopic biopsy of peripheral pulmonary lesions (PPLs). The diagnostic yield and complications of RP-EBUS-TBLB for PPLs vary depending on the technique, such as using a guide sheath (GS) or fluoroscopy. In this study, we investigated the utility of RP-EBUS-TBLB using a GS without fluoroscopy for diagnosing PPLs. Methods: We retrospectively reviewed data from 607 patients who underwent RP-EBUS of PPLs from January 2019 to July 2020. TBLB was performed using RP-EBUS with a GS without fluoroscopy. The diagnostic yield and complications were assessed. Multivariable logistic regression analyses were used to identify factors affecting the diagnostic yields. Results: The overall diagnostic accuracy was 76.1% (462/607). In multivariable analyses, the size of the lesion (≥20 mm; odds ratio [OR], 2.06; 95% confidence interval [CI], 1.27–3.33; p=0.003), positive bronchus sign in chest computed tomography (OR, 2.30; 95% CI, 1.40–3.78; p=0.001), a solid lesion (OR, 2.40; 95% CI, 1.31–4.41; p=0.005), and an EBUS image with the probe within the lesion (OR, 6.98; 95% CI, 4.38–11.12; p<0.001) were associated with diagnostic success. Pneumothorax occurred in 2.0% (12/607) of cases and chest tube insertion was required in 0.5% (3/607) of patients. Conclusion RP-EBUS-TBLB using a GS without fluoroscopy is a highly accurate diagnostic method in diagnosing PPLs that does not involve radiation exposure and has acceptable complication rates.

Background: It is difficult to distinguish subtle differences shown in computed tomography (CT) images of coronavirus disease 2019 (COVID-19) and bacterial pneumonia patients, which often leads to an inaccurate diagnosis. It is desirable to design and evaluate interpretable feature extraction techniques to describe the patient's condition. Methods: This is a retrospective cohort study of 170 confirmed patients with COVID-19 or bacterial pneumonia acquired at Yeungnam University Hospital in Daegu, Korea. The lung and lesion regions were segmented to crop the lesion into 2D patches to train a classifier model that could differentiate between COVID-19 and bacterial pneumonia. The K-means algorithm was used to cluster deep features extracted by the trained model into 20 groups.Each lesion patch cluster was described by a characteristic imaging term for comparison.For each CT image containing multiple lesions, a histogram of lesion types was constructed using the cluster information. Finally, a Support Vector Machine classifier was trained with the histogram and radiomics features to distinguish diseases and severity. Results: The 20 clusters constructed from 170 patients were reviewed based on common radiographic appearance types. Two clusters showed typical findings of COVID-19, with two other clusters showing typical findings related to bacterial pneumonia. Notably, there is one cluster that showed bilateral diffuse ground-glass opacities (GGOs) in the central and peripheral lungs and was considered to be a key factor for severity classification. The proposed method achieved an accuracy of 91.2% for classifying COVID-19 and bacterial pneumonia patients with 95% reported for severity classification. The CT quantitative parameters represented by the values of cluster 8 were correlated with existing laboratory data and clinical parameters. Conclusion Deep chest CT analysis with constructed lesion clusters revealed well-known COVID-19 CT manifestations comparable to manual CT analysis. The constructed histogram features improved accuracy for both diseases and severity classification, and showedcorrelations with laboratory data and clinical parameters. The constructed histogram features can provide guidance for improved analysis and treatment of COVID-19.

Background: The presence of the bronchus sign on chest computed tomography is associated with an increased diagnostic yield of radial probe endobronchial ultrasound– guided transbronchial lung biopsy (RP-EBUS-TBLB). However, the utility of RP-EBUS-TBLB for bronchus sign negative peripheral pulmonary lesions (PPLs) remains unknown. We investigated the utility of RP-EBUS-TBLB in bronchus sign negative PPLs. Methods: We retrospectively reviewed data from 109 patients who underwent RP-EBUS for bronchus sign negative PPLs from January 2019 to August 2020. TBLB was performed using RP-EBUS with a guide sheath and without fluoroscopy. The EBUS visualization and TBLB diagnostic yields were assessed. Multivariable logistic regression analyses were used to identify factors affecting the EBUS visualization and diagnostic yields. Results: The EBUS visualization yield was 74.1% (68/109). Of the 109 lung lesions, 92 were definitively diagnosed. The overall diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 50.5% (55/109), 34.9% (29/83), 100% (26/26), 100% (29/29), and 32.5% (26/80), respectively. In multivariable analyses, the size of the lesion (≥ 20 mm; odds ratio [OR], 2.62; 95% confidence interval [CI], 1.16–5.93; P = 0.021) and the distance from the pleura (> 10 mm; OR, 2.37; 95% CI, 1.02–5.52; P = 0.045) were associated with EBUS visualization. Regarding diagnostic yield, having the probe within the lesion (OR, 28.50; 95% CI, 6.26–129.85; P < 0.001) and a solid lesion (OR, 14.58; 95% CI, 2.64–80.38; P = 0.002) were associated with diagnostic success. Pneumothorax and hemoptysis occurred in 3.7% (4/109) and 0.9% (1/109), respectively, of the patients. Conclusion RP-EBUS-TBLB using a GS can be considered a diagnostic method in bronchus sign negative solid PPLs. Having the probe within the lesion and a solid lesion were important for diagnostic success. Complication rates were acceptable.

Background: It is difficult to distinguish subtle differences shown in computed tomography (CT) images of coronavirus disease 2019 (COVID-19) and bacterial pneumonia patients, which often leads to an inaccurate diagnosis. It is desirable to design and evaluate interpretable feature extraction techniques to describe the patient's condition. Methods: This is a retrospective cohort study of 170 confirmed patients with COVID-19 or bacterial pneumonia acquired at Yeungnam University Hospital in Daegu, Korea. The lung and lesion regions were segmented to crop the lesion into 2D patches to train a classifier model that could differentiate between COVID-19 and bacterial pneumonia. The K-means algorithm was used to cluster deep features extracted by the trained model into 20 groups.Each lesion patch cluster was described by a characteristic imaging term for comparison.For each CT image containing multiple lesions, a histogram of lesion types was constructed using the cluster information. Finally, a Support Vector Machine classifier was trained with the histogram and radiomics features to distinguish diseases and severity. Results: The 20 clusters constructed from 170 patients were reviewed based on common radiographic appearance types. Two clusters showed typical findings of COVID-19, with two other clusters showing typical findings related to bacterial pneumonia. Notably, there is one cluster that showed bilateral diffuse ground-glass opacities (GGOs) in the central and peripheral lungs and was considered to be a key factor for severity classification. The proposed method achieved an accuracy of 91.2% for classifying COVID-19 and bacterial pneumonia patients with 95% reported for severity classification. The CT quantitative parameters represented by the values of cluster 8 were correlated with existing laboratory data and clinical parameters. Conclusion Deep chest CT analysis with constructed lesion clusters revealed well-known COVID-19 CT manifestations comparable to manual CT analysis. The constructed histogram features improved accuracy for both diseases and severity classification, and showedcorrelations with laboratory data and clinical parameters. The constructed histogram features can provide guidance for improved analysis and treatment of COVID-19.

Background: The presence of the bronchus sign on chest computed tomography is associated with an increased diagnostic yield of radial probe endobronchial ultrasound– guided transbronchial lung biopsy (RP-EBUS-TBLB). However, the utility of RP-EBUS-TBLB for bronchus sign negative peripheral pulmonary lesions (PPLs) remains unknown. We investigated the utility of RP-EBUS-TBLB in bronchus sign negative PPLs. Methods: We retrospectively reviewed data from 109 patients who underwent RP-EBUS for bronchus sign negative PPLs from January 2019 to August 2020. TBLB was performed using RP-EBUS with a guide sheath and without fluoroscopy. The EBUS visualization and TBLB diagnostic yields were assessed. Multivariable logistic regression analyses were used to identify factors affecting the EBUS visualization and diagnostic yields. Results: The EBUS visualization yield was 74.1% (68/109). Of the 109 lung lesions, 92 were definitively diagnosed. The overall diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 50.5% (55/109), 34.9% (29/83), 100% (26/26), 100% (29/29), and 32.5% (26/80), respectively. In multivariable analyses, the size of the lesion (≥ 20 mm; odds ratio [OR], 2.62; 95% confidence interval [CI], 1.16–5.93; P = 0.021) and the distance from the pleura (> 10 mm; OR, 2.37; 95% CI, 1.02–5.52; P = 0.045) were associated with EBUS visualization. Regarding diagnostic yield, having the probe within the lesion (OR, 28.50; 95% CI, 6.26–129.85; P < 0.001) and a solid lesion (OR, 14.58; 95% CI, 2.64–80.38; P = 0.002) were associated with diagnostic success. Pneumothorax and hemoptysis occurred in 3.7% (4/109) and 0.9% (1/109), respectively, of the patients. Conclusion RP-EBUS-TBLB using a GS can be considered a diagnostic method in bronchus sign negative solid PPLs. Having the probe within the lesion and a solid lesion were important for diagnostic success. Complication rates were acceptable.

Although some information on the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and a few selectedcases has been reported, data on the clinical characteristics and outcomes of patients hospitalized therewith in South Koreaare lacking. We conducted a retrospective single-center study of 98 consecutive hospitalized patients with confirmed SARS-CoV-2infection at Yeungnam University Medical Center in Daegu, South Korea. Sixty patients were women (61.2%), and the mean agewas 55.4±17.1 years. Thirteen patients (13.3%) were treated in the intensive care unit (ICU). The mean interval from symptom onsetto hospitalization was 7.7±4.5 days. Patients who received ICU care were significantly older and were more likely to have diabetesmellitus. The National Early Warning Score on the day of admission was significantly higher in patients requiring ICU care. Acuterespiratory distress syndrome (13/13 patients; 100%), septic shock (9/13; 69.2%), acute cardiac injury (9/13; 69.2%), and acute kidneyinjury (8/13; 61.5%) were more common in patients who received ICU care. All patients received antibiotic therapy, and most(97/98 patients; 99.0%) received antiviral therapy (lopinavir/ritonavir). Hydroxychloroquine was used in 79 patients (80.6%), andglucocorticoid therapy was used in 18 patients (18.4%). In complete blood counts, lymphopenia was the most common finding(40/98 patients; 40.8%). Levels of all proinflammatory cytokines were significantly higher in ICU patients. As of March 29, 2020, themortality rate was 5.1%. Here, we report the clinical characteristics and laboratory findings of SARS-CoV-2 patients in South Koreaup to March 29, 2020.

To determine the role of diabetes mellitus (DM) in the coronavirus disease 2019 (COVID-19), we explored the clinical characteristics of patients with DM and compared risk factors such as age, glycemic control, and medications to those without DM.

BACKGROUND: Psoriasis is an immune-mediated, chronic inflammatory disease affecting multiple aspects of patients' lives. Its epidemiology varies regionally; however, nationwide epidemiologic data on psoriasis depicting profile of Korean patients has not been available to date. OBJECTIVE: To understand nationwide epidemiologic characteristics and clinical features of adult patients with psoriasis visited university hospitals in Korea. METHODS: This multicenter, non-interventional, cross-sectional study recruited 1,278 adult patients with psoriasis across 25 centers in Korea in 2013. Various clinical data including PASI, BSA, DLQI, SF-36 and PASE were collected. RESULTS: A total of 1,260 patients completed the study (male:female=1.47:1). The mean age was 47.0 years with a distribution mostly in the 50s (24.9%). Early onset (<40 years) of psoriasis accounted for 53.9% of patients. The mean disease duration was 109.2 months; mean body mass index was 23.9 kg/m²; and 12.7% of patients had a family history of psoriasis. Plaque and guttate types of psoriasis accounted for 85.8% and 8.4%, respectively. Patients with PASI ≥10 accounted for 24.9%; patients with body surface area ≥10 were 45.9%. Patients with DLQI ≥6 accounted for 78.8%. Between PASI <10 and PASI ≥10 groups, significant difference was noted in age at diagnosis, disease duration, blood pressure, waist circumference of female, and treatment experiences with phototherapy, systemic agents, and biologics. CONCLUSION: This was the first nationwide epidemiologic study of patients with psoriasis in Korea and provides an overview of the epidemiologic characteristics and clinical profiles of this patient population.
Adult ; Biological Products ; Blood Pressure ; Body Mass Index ; Body Surface Area ; Cross-Sectional Studies* ; Diagnosis ; Epidemiologic Studies ; Epidemiology ; Female ; Hospitals, University ; Humans ; Korea* ; Phototherapy ; Psoriasis* ; Waist Circumference