Purpose: Asthma is characterized by chronic type 2/eosinophilic inflammation in the airway mucosa. This study aimed to explore the clinical value of 2 cutoffs of blood eosinophil counts (≥ 300/μL and ≥ 150/μL) in eosinophilic asthma, with relation to eosinophilderived neurotoxin (EDN), a surrogate marker of eosinophilic activity. Methods: To compare clinical features and eosinophil-related mediators according to 2 cutoffs of peripheral blood eosinophil counts (≥ 300/μL and ≥ 150/μL), 137 adult asthmatics who had maintained antiasthmatic medications, including inhaled corticosteroid and long-acting beta 2 agonist, without biologics, were enrolled. EDN levels in serum, urine and sputum were measured by enzymelinked immunosorbent assay. Results: Patients with asthma and higher blood eosinophil counts ( ≥ 300/μL) had a higher prevalence of severe asthma, chronic rhinosinusitis, partly controlled/uncontrolled status, and higher levels of sputum eosinophils and EDN in serum/sputum than those with lower blood eosinophil counts (< 300/μL). When compared between patients with asthma having higher blood eosinophils ( ≥ 150/μL) and those with lower eosinophils ( < 150/μL), there were no differences in symptom severity, control status or lung function parameters. Conclusion These findings suggest that blood eosinophil count ≥ 300/μL may identify asthma patients at higher risk for severity and heightened eosinophil activity, supporting its utility as a biomarker in a real clinical setting.

Background: Despite the increasing use of continuous glucose monitoring (CGM) systems, limited data exist on their perceived benefits and challenges among patients and healthcare providers. This study explored CGM-related experiences in South Korea. Methods: An anonymous online survey was conducted between January and December 2021 at four university hospitals. Respondents included patients with diabetes mellitus (DM), physicians, and DM education nurses. The survey assessed the use of CGM, its benefits, and barriers. Most devices were first-generation CGMs: FreeStyle Libre 1 (Abbott Diabetes Care), Dexcom G6 (Dexcom Inc.), and Medtronic Guardian 3 (Medtronic MiniMed). Results: Among 1,010 patients (33.4% with type 1 DM [T1DM], 63.6% with type 2 DM [T2DM], and 3.1% others; mean age, 51.4±14.6 years), 92.7% found CGM helpful. Although 59.6% reported discomfort, 81.9% intended to continue using CGM, indicating that perceived benefits outweighed barriers. The key advantages were glucose monitoring without finger pricks (T1DM, 57.9%; T2DM, 56.2%) and maintenance of target glucose levels. Discomfort was related to discomfort during activities (53.8%), skin problems (45.0%), and pain (43.0%). Healthcare provider recommendations were associated with reduced discomfort (adjusted odds ratio, 0.36; 95% confidence interval, 0.21–0.60). Physicians (n=29) cited high costs as the main barrier (T1DM, 58.9%; T2DM, 64.8%); only 51.9% and 14.5% prescribed CGM for T1DM and T2DM, respectively. Insulin adjustment and glucose control were the main reasons for prescription, while cost (89.3%) and limited consultation time (67.9%) were barriers. DM educators (n=9) reported heavy workloads, with training and follow-up times averaging 31.7±7.5 minutes and 21.7±9.7 minutes, respectively; 77.8% of DM educators identified frequent patient inquiries as their greatest burden. Conclusion CGM provides significant clinical benefits but is limited by discomfort, costs, and educational burden. Sustained adoption requires device improvements, insurance support, and workforce expansion.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Mechanical power (MP) has been reported to be associated with clinical outcomes. Because the original MP equation is derived from paralyzed patients under volume-controlled ventilation, its application in practice could be limited in patients receiving pressure-controlled ventilation (PCV). Recently, a simplified equation for patients under PCV was developed. We investigated the association between MP and intensive care unit (ICU) mortality. Methods: We conducted a retrospective analysis of Korean data from the Fourth International Study of Mechanical Ventilation. We extracted data of patients under PCV on day 1 and calculated MP using the following simplified equation: MPPCV = 0.098 ∙ respiratory rate ∙ tidal volume ∙ (ΔPinsp + positive end-expiratory pressure), where ΔPinsp is the change in airway pressure during inspiration. Patients were divided into survivors and non-survivors and then compared. Multivariable logistic regression was performed to determine association between MPPCV and ICU mortality. The interaction of MPPCV and use of neuromuscular blocking agent (NMBA) was also analyzed. Results: A total of 125 patients was eligible for final analysis, of whom 38 died in the ICU. MPPCV was higher in non-survivors (17.6 vs. 26.3 J/min, P<0.001). In logistic regression analysis, only MPPCV was significantly associated with ICU mortality (odds ratio, 1.090; 95% confidence interval, 1.029–1.155; P=0.003). There was no significant effect of the interaction between MPPCV and use of NMBA on ICU mortality (P=0.579). Conclusions: MPPCV is associated with ICU mortality in patients mechanically ventilated with PCV mode, regardless of NMBA use.

Purpose: Triple-negative breast cancer (TNBC) is a particularly challenging subtype of breast cancer, with a poorer prognosis compared to other subtypes. Unfortunately, unlike luminal-type cancers, there is no validated biomarker to predict the prognosis of patients with early-stage TNBC. Accurate biomarkers are needed to establish effective therapeutic strategies. Materials and Methods: In this study, we analyzed gene expression profiles of tumor samples from 184 TNBC patients (training cohort, n=76; validation cohort, n=108) using RNA sequencing. Results: By combining weighted gene expression, we identified a 10-gene signature (DGKH, GADD45B, KLF7, LYST, NR6A1, PYCARD, ROBO1, SLC22A20P, SLC24A3, and SLC45A4) that stratified patients by risk score with high sensitivity (92.31%), specificity (92.06%), and accuracy (92.11%) for invasive disease-free survival. The 10-gene signature was validated in a separate institution cohort and supported by meta-analysis for biological relevance to well-known driving pathways in TNBC. Furthermore, the 10-gene signature was the only independent factor for invasive disease-free survival in multivariate analysis when compared to other potential biomarkers of TNBC molecular subtypes and T-cell receptor β diversity. 10-gene signature also further categorized patients classified as molecular subtypes according to risk scores. Conclusion Our novel findings may help address the prognostic challenges in TNBC and the 10-gene signature could serve as a novel biomarker for risk-based patient care.

Background: The risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission during the endemic phase may vary from that during the previous pandemic phase. We evaluated the risk of infection in a general population with laboratory-confirmed coronavirus disease 2019 (COVID-19) in a community setting in Korea. Materials and Methods: This study included 1,286 individuals who had been in contact with an index COVID-19 case between January 24, 2020, and June 30, 2022. Variables such as age, sex, nationality, place of contact, level of contact, the status of exposed cases, period, and level of mask-wearing were assessed. Results: Among 1,286 participants, 132 (10.30%) were confirmed to have COVID-19. With increasing age, the risk of the exposed persons contracting COVID-19 from index cases tended to increase (P <0.001), especially for people in their 70s (odds ratio, 1.24; 95% confidence interval, 1.11–1.40; P <0.001). We found an increasing trend in the risk of a COVID-19 exposed case becoming a secondary infection case (P <0.001) in long-term care facilities where the attack rate was high. Conclusion The risk of COVID-19 transmission is high in long-term care facilities where many older adults reside. Intensive management of facilities at risk of infection and strict mask-wearing of confirmed COVID-19 cases are necessary to prevent the risk of COVID-19 infection.

Background: Although respiratory tract infection is one of the most important factors triggering acute exacerbation of chronic obstructive pulmonary disease (AE-COPD), limited data are available to suggest an epidemiologic pattern of microbiology in South Korea. Methods: A multicenter observational study was conducted between January 2015 and December 2018 across 28 hospitals in South Korea. Adult patients with moderate-to-severe acute exacerbations of COPD were eligible to participate in the present study. The participants underwent all conventional tests to identify etiology of microbial pathogenesis. The primary outcome was the percentage of different microbiological pathogens causing AE-COPD. A comparative microbiological analysis of the patients with overlapping asthma–COPD (ACO) and pure COPD was performed. Results: We included 1,186 patients with AE-COPD. Patients with pure COPD constituted 87.9% and those with ACO accounted for 12.1%. Nearly half of the patients used an inhaled corticosteroid-containing regimen and one-fifth used systemic corticosteroids. Respiratory pathogens were found in 55.3% of all such patients. Bacteria and viruses were detected in 33% and 33.2%, respectively. Bacterial and viral coinfections were found in 10.9%. The most frequently detected bacteria were Pseudomonas aeruginosa (9.8%), and the most frequently detected virus was influenza A (10.4%). Multiple bacterial infections were more likely to appear in ACO than in pure COPD (8.3% vs. 3.6%, p=0.016). Conclusion Distinct microbiological patterns were identified in patients with moderate-to-severe AE-COPD in South Korea. These findings may improve evidence-based management of patients with AE-COPD and represent the basis for further studies investigating infectious pathogens in patients with COPD.

Background/Aims: There are few studies describing contemporary status of mechanical ventilation in Korea. We investigated changes in management and outcome of mechanical ventilation in Korea. Methods: International, prospective observational cohort studies have been conducted every 6 years since 1998. Korean intensive care units (ICUs) participated in 2010 and 2016 cohorts. We compared 2016 and 2010 Korean data. Results: Two hundred and twenty-six patients from 18 ICUs and 275 patients from 12 ICUs enrolled in 2016 and 2010, respectively. In 2016 compared to 2010, use of non-invasive ventilation outside ICU increased (10.2% vs. 2.5%, p = 0.001). Pressure-control ventilation was the most common mode in both groups. Initial tidal volume (7.1 mL/kg vs. 7.4 mL/kg, p = 0.372) and positive end-expiratory pressure (6 cmH2O vs. 6 cmH2O, p = 0.141) were similar, but peak pressure (22 cmH2O vs. 24 cmH2O, p = 0.011) was lower in 2016. More patients received sedatives (70.7% vs. 57.0%, p = 0.002) and analgesics (86.5% vs. 51.1%, p < 0.001) in 2016. The awakening (48.4% vs. 31.0%, p = 0.002) was more frequently attempted in 2016. The accidental extubation rate decreased to one tenth of what it was in 2010 (1.1% vs. 10.2%, p < 0.001). The ICU mortality did not change (31.4% 35.6%, p = 0.343) but ICU length of stay showed a decreasing trend (9 days vs. 10 days, p = 0.054) in 2016. Conclusions There were temporal changes in care of patients on mechanical ventilation including better control of pain and agitation, and active attempt of awakening.