Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study.

BACKGROUND: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. METHODS: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO2/FIO2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine). The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley's additive explanations (SHAP). RESULTS: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756-0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626-0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. CONCLUSION: Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

A Deep Learning-Based Approach for Prediction of Vancomycin Treatment Monitoring: Retrospective Study Among Patients With Critical Illness.

BACKGROUND: Vancomycin pharmacokinetics are highly variable in patients with critical illnesses, and clinicians commonly use population pharmacokinetic (PPK) models based on a Bayesian approach to dose. However, these models are population-dependent, may only sometimes meet the needs of individual patients, and are only used by experienced clinicians as a reference for making treatment decisions. To assist real-world clinicians, we developed a deep learning-based decision-making system that predicts vancomycin therapeutic drug monitoring (TDM) levels in patients in intensive care unit. OBJECTIVE: This study aimed to establish joint multilayer perceptron (JointMLP), a new deep-learning model for predicting vancomycin TDM levels, and compare its performance with the PPK models, extreme gradient boosting (XGBoost), and TabNet. METHODS: We used a 977-case data set split into training and testing groups in a 9:1 ratio. We performed external validation of the model using 1429 cases from Kangwon National University Hospital and 2394 cases from the Medical Information Mart for Intensive Care-IV (MIMIC-IV). In addition, we performed 10-fold cross-validation on the internal training data set and calculated the 95% CIs using the metric. Finally, we evaluated the generalization ability of the JointMLP model using the MIMIC-IV data set. RESULTS: Our JointMLP model outperformed other models in predicting vancomycin TDM levels in internal and external data sets. Compared to PPK, the JointMLP model improved predictive power by up to 31% (mean absolute error [MAE] 6.68 vs 5.11) on the internal data set and 81% (MAE 11.87 vs 6.56) on the external data set. In addition, the JointMLP model significantly outperforms XGBoost and TabNet, with a 13% (MAE 5.75 vs 5.11) and 14% (MAE 5.85 vs 5.11) improvement in predictive accuracy on the inner data set, respectively. On both the internal and external data sets, our JointMLP model performed well compared to XGBoost and TabNet, achieving prediction accuracy improvements of 34% and 14%, respectively. Additionally, our JointMLP model showed higher robustness to outlier data than the other models, as evidenced by its higher root mean squared error performance across all data sets. The mean errors and variances of the JointMLP model were close to zero and smaller than those of the PPK model in internal and external data sets. CONCLUSIONS: Our JointMLP approach can help optimize treatment outcomes in patients with critical illnesses in an intensive care unit setting, reducing side effects associated with suboptimal vancomycin administration. These include increased risk of bacterial resistance, extended hospital stays, and increased health care costs. In addition, the superior performance of our model compared to existing models highlights its potential to help real-world clinicians.

Study Protocol for a Hospital-to-Home Transitional Care for Older Adults Hospitalized with Chronic Obstructive Pulmonary Disease in South Korea: A Randomized Controlled Trial.

Chronic obstructive pulmonary disease (COPD) is a progressive respiratory condition characterized by persistent inflammation in the airways, resulting in narrowing and obstruction of the air passages. The development of COPD is primarily attributed to long-term exposure to irritants, such as cigarette smoke and environmental pollutants. Among individuals hospitalized for exacerbations of COPD, approximately one in five is readmitted within 30 days of discharge or encounters immediate post-discharge complications, highlighting a lack of adequate preparedness for self-management. To address this inadequate preparedness, transitional care services (TCS) have emerged as a promising approach. Therefore, this study primarily aims to present a detailed protocol for a multi-site, single-blind, randomized, controlled trial (RCT) aimed at enhancing self-management competency and overall quality of life for patients with COPD through the provision of TCS, facilitated by a proficient Clinical Research Coordinator. The RCT intervention commenced in September 2022 and is set to conclude in December 2024, with a total of 362 COPD patients anticipated to be enrolled in the study. The intervention program encompasses various components, including an initial assessment during hospitalization, comprehensive self-management education, facilitation of social welfare connections, post-discharge home visits, and regular telephone monitoring. Furthermore, follow-up evaluations are conducted at both one month and three months after discharge to assess the effectiveness of the intervention in terms of preventing re-hospitalization, reducing acute exacerbations, and enhancing disease awareness among participants. The results of this study are expected to provide a basis for the development of TCS fee payment policies for future health insurance.

In-Advance Prediction of Pressure Ulcers via Deep-Learning-Based Robust Missing Value Imputation on Real-Time Intensive Care Variables.

Pressure ulcers (PUs) are a prevalent skin disease affecting patients with impaired mobility and in high-risk groups. These ulcers increase patients' suffering, medical expenses, and burden on medical staff. This study introduces a clinical decision support system and verifies it for predicting real-time PU occurrences within the intensive care unit (ICU) by using MIMIC-IV and in-house ICU data. We develop various machine learning (ML) and deep learning (DL) models for predicting PU occurrences in real time using the MIMIC-IV and validate using the MIMIC-IV and Kangwon National University Hospital (KNUH) dataset. To address the challenge of missing values in time series, we propose a novel recurrent neural network model, GRU-D++. This model outperformed other experimental models by achieving the area under the receiver operating characteristic curve (AUROC) of 0.945 for the on-time prediction and AUROC of 0.912 for 48h in-advance prediction. Furthermore, in the external validation with the KNUH dataset, the fine-tuned GRU-D++ model demonstrated superior performances, achieving an AUROC of 0.898 for on-time prediction and an AUROC of 0.897 for 48h in-advance prediction. The proposed GRU-D++, designed to consider temporal information and missing values, stands out for its predictive accuracy. Our findings suggest that this model can significantly alleviate the workload of medical staff and prevent the worsening of patient conditions by enabling timely interventions for PUs in the ICU.

Glyoxalase 1 as a Therapeutic Target in Cancer and Cancer Stem Cells.

Methylglyoxal (MG) is a dicarbonyl compound formed in cells mainly by the spontaneous degradation of the triose phosphate intermediates of glycolysis. MG is a powerful precursor of advanced glycation end products, which lead to strong dicarbonyl and oxidative stress. Although divergent functions of MG have been observed depending on its concentration, MG is considered to be a potential anti-tumor factor due to its cytotoxic effects within the oncologic domain. MG detoxification is carried out by the glyoxalase system. Glyoxalase 1 (Glo1), the ubiquitous glutathione-dependent enzyme responsible for MG degradation, is considered to be a tumor promoting factor due to it catalyzing the removal of cytotoxic MG. Indeed, various cancer types exhibit increased expression and activity of Glo1 that closely correlate with tumor cell growth and metastasis. Furthermore, mounting evidence suggests that Glo1 contributes to cancer stem cell survival. In this review, we discuss the role of Glo1 in the malignant progression of cancer and its possible use as a promising therapeutic target for tumor therapy. We also summarize therapeutic outcomes of Glo1 inhibitors as prospective treatments for the prevention of cancer.

Difference of copy number variation in blood of patients with lung cancer.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths worldwide. Copy number variation (CNV) in several genetic regions correlate with cancer susceptibility. Hence, this study evaluated the association between CNV and non-small cell lung cancer (NSCLC) in the peripheral blood. METHODS: Blood samples of 150 patients with NSCLC and 150 normal controls were obtained from a bioresource center (Seoul, Korea). Through an epigenome-wide analysis using the MethylationEPIC BeadChip method, we extracted CNVs by using an SVS8 software-supplied multivariate method. We compared CNV frequencies between the NSCLC and controls, and then performed stratification analyses according to smoking status. RESULTS: We acquired 979 CNVs, with 582 and 967 copy-number gains and losses, respectively. We identified five nominally significant associations (ACOT1, NAA60, GSDMD, HLA-DPA1, and SLC35B3 genes). Among the current smokers, the NSCLC group had more CNV losses and gains at the GSDMD gene in chromosome 8 (P=0.02) and at the ACOT1 gene in chromosome 14 (P=0.03) than the control group. It also had more CNV losses at the NAA60 gene in chromosome 16 (P=0.03) among non-smokers. In the NSCLC group, current smokers had more CNV gains and losses at the ACOT1 gene in chromosome 14 (P=0.003) and at HLA-DPA1 gene in chromosome 6 (P=0.02), respectively, than non-smokers. CONCLUSION: Five nominally significant associations were found between the NSCLC and CNVs. CNVs are associated with the mechanism of lung cancer development. However, the role of CNVs in lung cancer development needs further investigation.

Effects of age on the association between pulmonary tuberculosis and lung cancer in a South Korean cohort.

BACKGROUND: Various studies have investigated the association between pulmonary tuberculosis (TB) and lung cancer However, how the relationship between TB and lung cancer may differ by age is not yet clear. This study investigated how risk for lung cancer after pulmonary TB may differ by age. METHODS: This study used the National Health Insurance Service-National Sample Cohort in South Korea. We compared 3,776 pulmonary TB patients with 18,880 controls matched for sex and age during the period from 2003 to 2013. We analyzed the incidence of lung cancer after diagnosis of active pulmonary TB. A multivariate Cox proportional hazard model was used to calculate the adjusted hazard ratio (HR) of lung cancer after adjusting for sex, age, house income, and smoking status. RESULTS: Among 3,776 pulmonary TB patients, 86 had lung cancer diagnoses, whereas there were 108 lung cancer patients among 18,880 controls. The incidence rate ratio in the pulmonary TB group was 12.26 within 1 year and 3.33 at 1-3.9 years after TB infection, compared to the control group. There was increased risk for lung cancer in pulmonary TB patients compared to controls (HR, 4.18; 95% CI, 3.15-5.56). Compared to patients <50 years of age, the risks for lung cancer were HR 9.85, 7.1, 3.32, and 2.57 in patients aged 50-59, 60-69, and ≥70 years, respectively. CONCLUSIONS: Pulmonary TB is a risk factor for lung cancer. Patients with pulmonary TB should be monitored for subsequent development of lung cancer, particularly in younger patients.

Computed tomography-derived area and density of pectoralis muscle associated disease severity and longitudinal changes in chronic obstructive pulmonary disease: a case control study.

BACKGROUND: Muscle wasting is associated with prognosis in patients with chronic obstructive pulmonary disease (COPD). The cross-sectional area of skeletal muscles on computed tomography (CT) could serve as a method to evaluate body composition. The present study aimed to determine the ability of CT-derived pectoralis muscle area (PMA) and pectoralis muscle density (PMD) to determine the severity of COPD and change in longitudinal pulmonary function in patients with COPD. METHODS: A total of 293 participants were enrolled in this study, a whom 222 had undergone at least two spirometry measurements within 3 years after baseline data acquisition. PMA and PMD were measured from a single axial slice of chest CT above the aortic arch at baseline. The emphysema index and bronchial wall thickness were quantitatively assessed in all scans. The generalized linear model was used to determine the correlation between PMA and PMD measurements and pulmonary function. RESULTS: PMA and PMD were significantly associated with baseline lung function and the severity of emphysema (P < 0.05). Patients with the lowest PMA and PMD exhibited significantly more severe airflow obstruction (ß = - 0.06; 95% confidence interval: - 0.09 to - 0.03]. PMA was statistically associated with COPD assessment test (CAT) score (P = 0.033). However, PMD did not exhibit statistically significant correlation with either CAT scores or modified Medical Research Council scores (P > 0.05). Furthermore, neither PMA nor PMD were associated with changes in forced expiratory volume in 1 s over a 3-year periods. CONCLUSIONS: CT-derived features of the pectoralis muscle may be helpful in predicting disease severity in patients with COPD, but are not necessarily associated with longitudinal changes in lung function.

Evaluation and treatment of latent tuberculosis infection among healthcare workers in Korea: A multicentre cohort analysis.

OBJECTIVE: Healthcare workers (HCWs) are one of the target groups for systematic testing and treatment of latent tuberculosis infection (LTBI) in a setting of low TB incidence. We performed this study to describe the testing of HCWs for LTBI and analyse the acceptance and completion of treatment of LTBI. METHODS: This retrospective cohort study was conducted in four university-affiliated hospitals between January 1 and December 31, 2018. HCWs with positive interferon-gamma release assay (IGRA) during LTBI screening were analysed. We assessed the acceptance and completion of LTBI treatment. RESULTS: Overall, 893 HCWs were IGRA positive. Among them, 609 HCWs visited the clinic for evaluation of LTBI. Of 609 HCWs who were evaluated, 302 (49.6%) were offered treatment for LTBI. The proportion of acceptance for treatment was 64.5% (195 of 302 HCWs). The treatment course was completed by 143 of 195 HCWs (73.3%). Three months of isoniazid and rifampin (3HR) was used in 137 HCWs (70.3%) and 4 months of rifampin (4R) in 58 (29.7%). 72 HCWs (36.9%) experienced at least one adverse drug events, but there was no different characteristics between completer and non-completer. CONCLUSION: The acceptance and completion of LTBI treatment were unsatisfactory. Subjective perspective regarding obstacles to treatment of LTBI needs to be explored to increase compliance to LTBI treatment.

Levels of vitamin D-associated cytokines distinguish between active and latent tuberculosis following a tuberculosis outbreak.

BACKGROUND: Vitamin D levels are associated with the extent of mycobactericidal activity. Interleukin (IL)-15 and IL-32 play roles in the vitamin D-mediated tuberculosis (TB) defense mechanism. Vitamin D induces IL-1ß, which plays an important role in terms of resistance to TB. We evaluated whether the levels of vitamin D-related cytokines distinguished between those with active TB and latent TB infection (LTBI). METHODS: In total, 50 TB-infected patients (25 with active TB and 25 with LTBI following a TB outbreak in a high school) were enrolled. Plasma 25-hydroxyvitamin D (25[OH]D), IL-15, IL-32, and IL-1ß levels were measured via enzyme-linked immunosorbent assays. Mycobacterium tuberculosis-specific antigen-induced and unstimulated cytokine levels were measured in the supernatants of the QuantiFERON TB Gold-In-Tube (QFT-GIT) assay. RESULTS: Plasma 25(OH)D and plasma IL-15 levels were lower in patients with active TB than in LTBI subjects (25(OH)D: 16.64 ng/mL vs. 21.6 ng/mL, P = 0.031; IL-15: 148.9 pg/mL vs. 189.8 pg/mL, P = 0.013). Plasma 25(OH)D levels correlated with the plasma levels of IL-15 and IL-1ß in TB-infected patients. In addition, the plasma 25(OH)D levels correlated positively with the level of unstimulated IL-15 (IL-15nil) and negatively with that of TB antigen-stimulated IL-32 (IL-32TB) in QFT-GIT supernatants. Although the IL-15nil and IL-15TB levels were higher in LTBI subjects than patients with active TB, the IL-32nil and IL-32TB levels were higher in the latter patients. A combination of the IL-15nil and IL-32TB levels accurately predicted 91.3% of active TB patients and latent subjects, with an area under the curve of 0.964. CONCLUSIONS: Our preliminary data showed that the levels of the vitamin D-related cytokines IL-15 and IL-32 differed between active TB patients and LTBI subjects. This result might be used as a basic data for developing biomarkers distinguishing between active TB and LTBI.

Human pluripotent stem cell-derived alveolar epithelial cells are alternatives for in vitro pulmotoxicity assessment.

Human pluripotent stem cell (hPSC)-derived alveolar epithelial cells (AECs) provide new opportunities for understanding lung development and the treatment of pulmonary diseases. However, toxicity assessments using hPSC-AECs have not been undertaken. In this study, we generated functional AECs from hPSCs and evaluated their inflammatory and apoptotic responses to cadmium (Cd) exposure (1, 5, and 10 µM) for 24 h compared with the human bronchial epithelial cell line (BEAS-2B) and primary AECs as controls. Our data showed that Cd (10 µM) treatment induced substantial inflammatory responses and apoptosis in BEAS-2B cells, but not in both hPSC-AECs and primary AECs. Interestingly, conditioned medium from AEC cultures significantly alleviated apoptotic and inflammatory responses to Cd exposure in BEAS-2B cells. Using cytokine arrays, several potential factors secreted from hPSC-AECs and primary AECs were detected and may be involved in reducing Cd-induced cytotoxicity. We also observed higher expression of surfactant proteins B and C in both hPSC-AECs and primary AECs, which may contribute to protection against Cd-induced cytotoxicity. These results suggested that hPSC-AECs phenotypically and functionally resemble primary AECs and could be more biologically relevant alternatives for evaluating the pathological contribution of confirmed or potential pulmotoxic materials included in smoking and microdust.

Inhaled Corticosteroid-Related Tuberculosis in the Real World Among Patients with Asthma and COPD: A 10-Year Nationwide Population-Based Study.

BACKGROUND: There have been concerns about the risk of inhaled corticosteroid (ICS)-related tuberculosis (TB) development. OBJECTIVE: We investigated the occurrence of TB among ICS users according to underlying respiratory diseases and type of ICS. METHODS: A 12-year population cohort comprising approximately 1 million subjects collected from the Korean claims database were used. Adult ICS users (budesonide or fluticasone) were enrolled. The temporal relationship between TB development and the last ICS prescription before TB development was evaluated. A nested case-control study was performed with 1:4 matching for age, sex, and the initiation date of the ICS. RESULTS: There were 17,991 ICS users, and 175 developed TB during the study period. Approximately 80% (140/175) of patients who developed TB were diagnosed within 3 years after the last ICS prescription. In the nested case-control study, the occurrence of TB was not related to the type of ICS, but was related to a higher annual admission rate and a higher comorbidity score. The risk of TB was higher in patients with chronic obstructive pulmonary disease (COPD) than in those with asthma (odds ratio: 2.31; CI 95%: 1.39-3.38; P = .0011) after adjusting for covariates. The subgroup analysis revealed no difference between budesonide and fluticasone with respect to the risk of developing TB in patients with asthma, COPD, or asthma-COPD overlap syndrome. CONCLUSION: An increased risk of TB development may persist for 3 years after stopping the ICS and the risk is higher in patients with COPD regardless of the type of ICS used.

Airway Epithelial Cell-Derived Colony Stimulating Factor-1 Promotes Allergen Sensitization.

Airway epithelial cells (AECs) secrete innate immune cytokines that regulate adaptive immune effector cells. In allergen-sensitized humans and mice, the airway and alveolar microenvironment is enriched with colony stimulating factor-1 (CSF1) in response to allergen exposure. In this study we found that AEC-derived CSF1 had a critical role in the production of allergen reactive-IgE production. Furthermore, spatiotemporally secreted CSF1 regulated the recruitment of alveolar dendritic cells (DCs) and enhanced the migration of conventional DC2s (cDC2s) to the draining lymph node in an interferon regulatory factor 4 (IRF4)-dependent manner. CSF1 selectively upregulated the expression of the chemokine receptor CCR7 on the CSF1R+ cDC2, but not the cDC1, population in response to allergen stimuli. Our data describe the functional specification of CSF1-dependent DC subsets that link the innate and adaptive immune responses in T helper 2 (Th2) cell-mediated allergic lung inflammation.

Plasma CRABP2 as a Novel Biomarker in Patients with Non-Small Cell Lung Cancer.

BACKGROUND: Lung cancer is the most common cause of cancer-related mortality worldwide. We previously reported the identification of a new genetic marker, cellular retinoic acid binding protein 2 (CRABP2), in lung cancer tissues. The aim of this study was to assess plasma levels of CRABP2 from patients with non-small cell lung cancer (NSCLC). METHODS: Blood samples that were collected from 122 patients with NSCLC between September 2009 and September 2013 were selected for the analysis, along with samples from age- (± 5 years), sex-, and cigarette smoking history (± 10 pack-years [PY])-matched controls from the Korea Biobank Network. The control specimens were from patients who were without malignancies or pulmonary diseases. We measured plasma levels of CRABP2 using commercially available enzyme-linked immunosorbent assay kits. RESULTS: The mean age of the NSCLC patients was 71.8 ± 8.9 years, and the median cigarette smoking history was 32 PY (range, 0-150 PY). Plasma CRABP2 levels were significantly higher in patients with NSCLC than in the matched controls (37.63 ± 28.71 ng/mL vs. 24.09 ± 21.09 ng/mL, P < 0.001). Higher plasma CRABP2 levels were also correlated with lower survival rates in NSCLC patients (P = 0.014). CONCLUSION: Plasma CRABP2 levels might be a novel diagnostic and prognostic marker in NSCLC.

Differences in chronic obstructive pulmonary disease phenotypes between non-smokers and smokers.

INTRODUCTION AND OBJECTIVES: Although tobacco smoking is a major risk factor for chronic obstructive pulmonary disease (COPD), more than one-fourth of COPD patients are non-smokers. In this cross-sectional study, the differences in COPD phenotypes between non-smokers and smokers in male subjects were investigated and were focused on structural lung changes using a quantitative assessment of computed tomography (CT) images. METHODS: They divided male participants with COPD, from a Korean cohort near a cement plant, into non-smokers and smokers by a cutoff of a 5 pack-year smoking history. Clinical characteristics, including age, body mass index (BMI), spirometry results, history of biomass smoke exposure, and CT measurements, were compared between the two groups. Emphysema index (EI) and mean wall area percentage (MWA %) were used to evaluate the structural lung changes on volumetric CT scans. RESULTS: The non-smoker group (n = 49) had younger patients and had a greater BMI than the smoker group (n = 113) (P < .05). Spirometry results, including post-bronchodilator forced expiratory volume in 1 s, were comparable between the two groups. More smokers had emphysema than non-smokers (EI 10.0 vs. 6.5, P < .001), but after accounting the potential confounders in model analysis, the difference was borderline significance (P = .051). In the subgroup of biomass smoke-exposed subjects, MWA% was significantly greater in smokers than in non-smokers (MWA 69.1 vs. 65.3, P = .03), while EI was not statistically different (EI 7.1 vs. 10.4, P = .52). CONCLUSIONS: Non-smoker males with COPD were younger and had a greater BMI than the smokers. Tobacco smoke exposure seemed to be associated with an emphysema-predominant phenotype, while biomass smoke exposure exhibited a significant interaction with tobacco smoking in an airway-predominant phenotype.

Changes in the Characteristics and Long-term Mortality Rates of Intensive Care Unit Patients from 2003 to 2010: A Nationwide Population-Based Cohort Study Performed in the Republic of Korea.

BACKGROUND: There are few studies on intensive care unit (ICU) patients in the Republic of Korea. We analyzed the characteristics and mortality changes of all ICU patients over the last 8 years. METHODS: This study used the cohort of the National Health Insurance Corporation, which provides medical care to all residents of the Republic of Korea. The cohort consists of patients aged 20 years or older between 2003 and 2010 with a history of ICU admission. We analyzed changes in sex, age, household income, number of hospital beds, emergency admissions, and reasons for admission using the Cochran-Armitage trend test. The adjusted hazard ratios (HRs) of mortality according to these variables and year of admission were calculated by Cox proportional hazards regression. RESULTS: The proportion of patients aged ≥70 years increased over that period, as did their average age (by 3.6 years). During the 8-year study period, the 3-year mortality rate was 32.91%-35.83%. The overall mortality was higher in males and older patients, in those with a lower household income and higher Charlson Comorbidity Index (CCI) score, those admitted to a hospital with a smaller number of beds, and those admitted via the emergency room. There was no significant change in crude mortality rate over the 8-year study period; however, the adjusted HR showed a decreasing trend. CONCLUSIONS: Patients admitted to the ICU were older and had higher CCI score. Nevertheless, there was a temporal trend toward a decrease in the HR of long-term mortality.

A cluster analysis of chronic obstructive pulmonary disease in dusty areas cohort identified three subgroups.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with variable clinical manifestations, structural changes, and treatment responses. In a cohort study, we performed a baseline cluster analysis to identify the subgroups of COPD and to assess the clinical outcomes of each subgroup during a 1-year follow-up. METHODS: We analyzed dusty areas cohort comprising 272 patients with COPD. The main factors with the highest loading in 15 variables were selected using principal component analysis (PCA) at baseline. The COPD patients were classified by hierarchical cluster analysis using clinical, physiological, and imaging data based on PCA-transformed data. The clinical parameters and outcomes during the 1-year follow-up were evaluated among the subgroups. RESULTS: PCA revealed that six independent components accounted for 77.3% of variance. Three distinct subgroups were identified through the cluster analysis. Subgroup 1 included younger subjects with fewer symptoms and mild airflow obstruction, and they had fewer exacerbations during the 1-year follow-up. Subgroup 2 comprised subjects with additional symptoms and moderate airflow obstruction, and they most frequently experienced exacerbations requiring hospitalization during the 1-year follow-up. Subgroup 3 included subjects with additional symptoms and mild airflow obstruction; this group had more female patients and a modest frequency of exacerbations requiring hospitalization. CONCLUSIONS: Cluster analysis using the baseline data of a COPD cohort identified three distinct subgroups with different clinical parameters and outcomes. These findings suggest that the identified subgroups represent clinically meaningful subtypes of COPD.

Cadmium-induced ER stress and inflammation are mediated through C/EBP-DDIT3 signaling in human bronchial epithelial cells.

Cadmium (Cd), a major component of cigarette smoke, disrupts the normal functions of airway cells and can lead to the development of various pulmonary diseases such as chronic obstructive pulmonary disease (COPD). However, the molecular mechanisms involved in Cd-induced pulmonary diseases are poorly understood. Here, we identified a cluster of genes that are altered in response to Cd exposure in human bronchial epithelial cells (BEAS-2B) and demonstrated that Cd-induced ER stress and inflammation are mediated via CCAAT-enhancer-binding proteins (C/EBP)-DNA-damaged-inducible transcript 3 (DDIT3) signaling in BEAS-2B cells. Cd treatment led to marked upregulation and downregulation of genes associated with the cell cycle, apoptosis, oxidative stress and inflammation as well as various signal transduction pathways. Gene set enrichment analysis revealed that Cd treatment stimulated the C/EBP signaling pathway and induced transcriptional activation of its downstream target genes, including DDIT3. Suppression of DDIT3 expression using specific small interfering RNA effectively alleviated Cd-induced ER stress and inflammatory responses in both BEAS-2B and normal primary normal human bronchial epithelial cells. Taken together, these data suggest that C/EBP signaling may have a pivotal role in the early induction of ER stress and inflammatory responses by Cd exposure and could be a molecular target for Cd-induced pulmonary disease.

ACN9 Regulates the Inflammatory Responses in Human Bronchial Epithelial Cells.

BACKGROUND: Airway epithelial cells are the first line of defense, against pathogens and environmental pollutants, in the lungs. Cellular stress by cadmium (Cd), resulting in airway inflammation, is assumed to be directly involved in tissue injury, linked to the development of lung cancer, and chronic obstructive pulmonary disease (COPD). We had earlier shown that ACN9 (chromosome 7q21), is a potential candidate gene for COPD, and identified significant interaction with smoking, based on genetic studies. However, the role of ACN9 in the inflammatory response, in the airway cells, has not yet been reported. METHODS: We first checked the anatomical distribution of ACN9 in lung tissues, using mRNA in situ hybridization, and immunohistochemistry. Gene expression profiling in bronchial epithelial cells (BEAS-2B), was performed, after silencing ACN9. We further tested the roles of ACN9, in the intracellular mechanism, leading to Cd-induced production, of proinflammatory cytokines in BEAS-2B. RESULTS: ACN9 was localized in lymphoid, and epithelial cells, of human lung tissues. ACN9 silencing, led to differential expression of 216 genes. Pathways of sensory perception to chemical stimuli, and cell surface receptor-linked signal transduction, were significantly enriched. ACN9 silencing, further increased the expression of proinflammatory cytokines, in BEAS-2B after Cd exposure. CONCLUSION: Our findings suggest, that ACN9 may have a role, in the inflammatory response in the airway.