Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Background: Gestational diabetes mellitus (GDM) is the most common metabolic complication of pregnancy. To define the altered pathway in GDM placenta, we investigated the transcriptomic profiles from human placenta between GDM and controls. Methods: Clinical parameters and postpartum complications were reviewed in all participants.Differentially expressed canonical pathways were analyzed between the GDM and control groups based on transcriptomic analysis. CD4 + T, CD8 + T, and senescent T cell subsets were determined by flow cytometry based on staining for specific intracellular cytokines. Results: Gene ontology analysis revealed that the placenta of GDM revealed upregulation of diverse mitochondria or DNA replication related pathways and downregulation of T-cell immunity related pathways. The maternal placenta of the GDM group had a higher proportion of CD4 + T and CD8 + T cells than the control group. Interestingly, senescent CD4 + T cells tended to increase and CD8 + T cells were significantly increased in GDM compared to controls, along with increased programmed cell death-1 (CD274 + ) expression. Programmed death-ligand 1 expression in syncytotrophoblasts was also significantly increased in patients with GDM. Conclusion This study demonstrated increased proinflammatory T cells, senescent T cells and immune-check point molecules in GDM placentas, suggesting that changes in senescent T cells and immune-escape signaling might be related to the pathophysiology of GDM.

Background: This study compared the treatment outcomes of patients with multidrug-resistant tuberculosis (MDR-TB) before and after the implementation of public–private mix (PPM). Factors affecting treatment success were also investigated. Methods: Data from culture-confirmed pulmonary MDR-TB patients who commenced MDR-TB treatment at Pusan National University Hospital between January 2003 and December 2017 were retrospectively reviewed. Patients were divided into two groups in terms of PPM status: pre-PPM period, patients who commenced MDR-TB treatment between 2003 and 2010; and post-PPM period, patients treated between 2011 and 2017. Results: A total of 176 patients were included (64 and 112 in the pre- and post-PPM periods, respectively). 36.9% of the patients were resistant to a fluoroquinolone or a second-line injectable drug, or both. The overall treatment success rate was 72.7%. The success rate of post-PPM patients was higher than that of pre-PPM patients (79.5% vs. 60.9%, p=0.008). Also, loss to follow-up was lower in the post-PPM period (5.4% vs. 15.6%, p=0.023). In multivariate regression analysis, age ≥65 years, body mass index ≤18.5 kg/m2, previous TB treatment, bilateral lung involvement, and extensively drug-resistant (XDR)- or pre-XDR-TB were associated with poorer treatment outcomes. However, the use of bedaquiline or delamanid for ≥1 month increased the treatment success. Conclusion The treatment success rate in MDR-TB patients was higher in the post-PPM period than in the pre-PPM period, particularly because of the low rate of loss to follow-up. To ensure comprehensive patient-centered PPM in South Korea, investment and other support must be adequate.

BACKGROUND: The purpose of this study was to investigate the effect of early tracheostomy on clinical outcomes in patients requiring prolonged acute mechanical ventilation (≥96 hours).METHODS: Data from 575 patients (69.4% male; median age, 68 years), hospitalized in the medical intensive care unit (ICU) of a university-affiliated tertiary care hospital March 2008–February 2017, were retrospectively evaluated. Early and late tracheostomy were designated as 2–10 days and >10 days after translaryngeal intubation, respectively.RESULTS: The 90-day cumulative mortality rate was 47.5% (n=273) and 258 patients (44.9%) underwent tracheostomy. In comparison with the late group (n=115), the early group (n=125) had lower 90-day mortality (31.2% vs. 47.8%, p=0.012), shorter stays in hospital and ICU, shorter ventilator length of stay (median, 43 vs. 54; 24 vs. 33; 23 vs. 28 days; all p<0.001), and a higher rate of transfer to secondary care hospitals with post-intensive care settings (67.2% vs. 43.5% p<0.001). Also, the total medical costs of the early group were lower during hospital stays than those of the late group (26,609 vs. 36,973 USD, p<0.001).CONCLUSION: Early tracheostomy was associated with lower 90-day mortality, shorter ventilator length of stay and shorter lengths of stays in hospital and ICU, as well as lower hospital costs than late tracheostomy.

PURPOSE: The incidence of drug-induced liver injury (DILI) has been increasing; however, few algorithms are available to identify DILI in electronic health records (EHRs). We aimed to identify and evaluate DILI with an appropriate screening algorithm.METHODS: We collected data from 3 university hospitals between June 2015 and May 2016 using our newly developed algorithm for identifying DILI. Among patients with alanine transferase (ALT) ≤ 120 IU/L and total bilirubin (TB) ≤ 2.4 mg/dL in blood test results within 48 hours of admission, those who either had 1) ALT > 120 IU/L and TB > 2.4 mg/dL or 2) ALT > 200 IU/L at least once during hospitalization were identified. After excluding patients with liver disease-related diagnosis at discharge, medical records were retrospectively reviewed to evaluate epidemiological characteristics of DILI.RESULTS: The total number of inpatients was 256,598, of whom 1,100 (0.43%) were selected by the algorithm as suspected DILI. Subsequently, 365 cases (0.14% of total inpatients, 95% confidence interval, 0.13–0.16) were identified as DILI, yielding a positive predictive value of 33.1%. Antibiotics (n = 214, 47.2%) were the major class of causative drug followed by chemotherapeutic agents (n = 87, 19.2%). The most common causative drug was piperacillin-tazobactam (n = 38, 8.4%); the incidence of DILI by individual agent was highest for methotrexate (19.4 cases/1,000 patients administered the drug). Common reasons for excluding suspected DILI cases were ischemic hepatitis and postoperative liver dysfunction.CONCLUSIONS: Using our EHR-based algorithm, we identified that approximately 0.14% of patients developed DILI during hospitalization. Further studies are needed to modify criteria for more accurate identification of DILI.
Alanine ; Anti-Bacterial Agents ; Bilirubin ; Diagnosis ; Drug-Induced Liver Injury ; Drug-Related Side Effects and Adverse Reactions ; Electronic Health Records ; Hematologic Tests ; Hepatitis ; Hospitalization ; Hospitals, University ; Humans ; Incidence ; Inpatients ; Liver ; Liver Diseases ; Mass Screening ; Medical Records ; Methotrexate ; Pharmacoepidemiology ; Retrospective Studies ; Transferases