Association between exposure to specific PM2.5 constituents and environment, lifestyle, and clinical parameters in patients with COPD.

This study investigated the correlation between the individual chemical constituents of particulate matter 2.5 µm (PM2.5) and respiratory parameters as well as the living environment and daily behaviors in patients with chronic obstructive pulmonary disease (COPD). Data were obtained from prospective COPD panel conducted in South Korea. Following collection via a microPEM, 18 metallic elements were determined using energy-dispersive X-ray fluorescence spectroscopy. All participants completed detailed questionnaires on living environments and lifestyle practices. Eighty-nine stable COPD patients (mean age 68.1 years; 94.4% male) were analyzed. Several constituents (titanium, aluminum, bromine, and silicone) were significantly associated with respiratory outcomes. Copper and manganese concentrations were significantly associated with the living environment. Increased ventilation time and air purifier operation were associated with lower concentrations of copper, silicone, barium, and titanium. These findings suggest varying relationships between PM2.5 constituents and clinical parameters in COPD patients, providing a basis for personalized interventions and future research.

Long non-coding RNA SOX2OT in tamoxifen-resistant breast cancer.

Hormone receptor (HR)-positive breast cancer can become aggressive after developing hormone-treatment resistance. This study elucidated the role of long non-coding RNA (lncRNA) SOX2OT in tamoxifen-resistant (TAMR) breast cancer and its potential interplay with the tumor microenvironment (TME). TAMR breast cancer cell lines TAMR-V and TAMR-H were compared with the luminal type A cell line (MCF-7). LncRNA expression was assessed via next-generation sequencing, RNA extraction, lncRNA profiling, and quantitative RT-qPCR. SOX2OT overexpression effects on cell proliferation, migration, and invasion were evaluated using various assays. SOX2OT was consistently downregulated in TAMR cell lines and TAMR breast cancer tissue. Overexpression of SOX2OT in TAMR cells increased cell proliferation and cell invasion. However, SOX2OT overexpression did not significantly alter SOX2 levels, suggesting an independent interaction within TAMR cells. Kaplan-Meier plot analysis revealed an inverse relationship between SOX2OT expression and prognosis in luminal A and B breast cancers. Our findings highlight the potential role of SOX2OT in TAMR breast cancer progression. The downregulation of SOX2OT in TAMR breast cancer indicates its involvement in resistance mechanisms. Further studies should explore the intricate interactions between SOX2OT, SOX2, and TME in breast cancer subtypes.

Development of a formula for estimated glomerular filtration rate in pregnant women from physiological hyperfiltration of serum creatinine.

Increased body fluids during pregnancy complicates the application of estimated glomerular filtration rate (eGFR) formulas that are based on body surface area. Furthermore, gestational renal dysfunction cannot be identified if the serum creatinine (SCr) concentration is within the non-pregnant reference interval (RI) despite inadequate pregnancy-related renal hyperfiltration. 1484 SCr measurements from 957 healthy pregnant women were collected. The average SCr value of gestational week (GW) 0-3 was the representative SCr value of non-pregnant status. While the distribution of SCr measurements varied across GWs, it was transformed into a normal distribution using the bootstrap resampling method. A polynomial linear regression method was applied to achieve a continuous and smooth transformation of values. The normally distributed SCr values of each GW were compared to the non-pregnant status, leading to the calculation of SCr hyperfiltration. The final equation, (2 - SCr (µmol/L) / 55.25) × 103.1 × 55.25/(56.7 - 0.223 × GW - 0.113 × GW2 + 0.00545 × GW3 - 0.0000653 × GW4), and reference intervals for both SCr and eGFR for each GW were obtained. These RIs and novel equations can be effectively used to monitor renal dysfunction in pregnant women.

Estimating the prevalence and clinical significance of chronic obstructive pulmonary disease-obstructive sleep apnea overlap in South Korea.

INTRODUCTION: Concurrent obstructive sleep apnea (OSA) and chronic obstructive pulmonary disease (COPD) are referred to as COPD-OSA overlap. We investigated the prevalence and clinical significance of COPD-OSA overlap in the general population of South Korea. METHODS: Data were obtained from the 2019 Korea National Health and Nutrition Examination Survey. Participants ≥40 years of age with complete STOP-Bang questionnaire and spirometry data were included. OSA was presumed in individuals with a STOP-Bang score of ≥3. COPD was determined using forced expiratory volume at 1 s/forced vital capacity <0.7. Participants were classified on the basis of the STOP-Bang score and spirometry findings. Clinical characteristics, comorbidities, and quality of life (using the EuroQoL 5-dimension instrument) were compared between the overlap group and COPD-alone or OSA-alone groups. RESULTS: Among the 3157 participants, 6.9 % demonstrated COPD-OSA overlap. Individuals with OSA alone and COPD alone were 31.8 % and 5.2 %, respectively. The overlap group included more males, ever smokers, and frequent alcohol drinkers than the COPD- or OSA-alone groups. The overlap group had more diagnoses of hypertension, diabetes, and stroke than the COPD-alone group. The risk of anxiety/depression was approximately 2.5 times higher in the overlap group than in the COPD-alone group. COPD-OSA overlap was a significant risk factor for anxiety/depression after adjusting for age, sex, household income, and education levels. CONCLUSION: COPD-OSA overlap is not rare within the general population of South Korea. Patients with overlap showed more comorbidities and higher levels of anxiety/depression than those in the COPD-alone group.

Formulating Electron Beam-Induced Covalent Linkages for Stable and High-Energy-Density Silicon Microparticle Anode.

High-capacity silicon (Si) materials hold a position at the forefront of advanced lithium-ion batteries. The inherent potential offers considerable advantages for substantially increasing the energy density in batteries, capable of maximizing the benefit by changing the paradigm from nano- to micron-sized Si particles. Nevertheless, intrinsic structural instability remains a significant barrier to its practical application, especially for larger Si particles. Here, a covalently interconnected system is reported employing Si microparticles (5 µm) and a highly elastic gel polymer electrolyte (GPE) through electron beam irradiation. The integrated system mitigates the substantial volumetric expansion of pure Si, enhancing overall stability, while accelerating charge carrier kinetics due to the high ionic conductivity. Through the cost-effective but practical approach of electron beam technology, the resulting 500 mAh-pouch cell showed exceptional stability and high gravimetric/volumetric energy densities of 413 Wh kg-1, 1022 Wh L-1, highlighting the feasibility even in current battery production lines.

Exploration of MELK as a downstream of Del-1 and druggable targets in triple-negative breast cancer.

PURPOSE: In our previous study, Developmental endothelial locus-1 (Del-1) was a promising predictive marker for breast cancer. However, the downstream targets of Del-1 remain unknown. Here, we sought to discover a druggable target downstream of Del-1 and investigate the mechanism by which it regulates the course of breast cancer. METHODS: To investigate Del-1 downregulation effect on breast cancer, we performed transcriptome analysis using RNA sequencing of Del-1 knockdowned MDA-MB-231 cell line Plus, to investigate the expression of Del-1 and Maternal embryonic leucine zipper kinase (MELK), mRNA levels in eight different triple-Negative Breast Cancer (TNBC) cell lines were analyzed. High-throughput sequencing was performed on total RNA isolated. OTS167 was used for MELK inhibition. The effects of MELK on cell proliferation and invasion were determined using the MTT and Matrigel transwell assays. Furthermore, we examined MELK expression in breast cancer tissue. RESULTS: Del-1 and MELK mRNA expression levels were significantly higher in the TNBC cell lines, MDA-MB-468, HCC-1806, and MBA-MB-231. Knocking down Del-1 with siRNA in HCC-1806 and MBA-MB-231 cells significantly decreased MELK expression and thus suggested a possible relationship between Del-1 and MELK. In MDA-MB-468 cells, a basal-like 1 TNBC cell line, OTS167 significantly inhibited breast cancer cell proliferation and promoted cell apoptosis. To further investigate the relationship between Del-1 and MELK, dual inhibition of both Del-1 and MELK was performed, which significantly reduced the viability of MDA-MB-468 and MBA-MB-231 cells. CONCLUSION: We found that MELK acts downstream of Del-1 and is a promising druggable target, especially in basal-like and mesenchymal stem-like subtype.

Application of entire dental panorama image data in artificial intelligence model for age estimation.

BACKGROUND: Accurate age estimation is vital for clinical and forensic purposes. With the rapid advancement of artificial intelligence(AI) technologies, traditional methods relying on tooth development, while reliable, can be enhanced by leveraging deep learning, particularly neural networks. This study evaluated the efficiency of an AI model by applying the entire panoramic image for age estimation. The outcome performances were analyzed through supervised learning (SL) models. METHODS: Total of 27,877 dental panorama images from 5 to 90 years of age were classified by 2 types of grouping. In type 1 they were classified by each age and in type 2, applying heuristic grouping, the age over 20 years were classified by every 5 years. Wide ResNet (WRN) and DenseNet (DN) were used for supervised learning. In addition, the analysis with ± 3 years of deviation in both types were performed. RESULTS: For the DN model, while the type 1 grouping achieved an accuracy of 0.1016 and F1 score of 0.058, the type 2 achieved an accuracy of 0.3146 and F1 score of 0.2027. Incorporating ± 3years of deviation, the accuracy of type 1 and 2 were 0.281, 0.7323 respectively; and the F1 score were 0.1768, 0.6583 respectively. For the WRN model, while the type 1 grouping achieved an accuracy of 0.1041 and F1 score of 0.0599, the type 2 achieved an accuracy of 0.3182 and F1 score of 0.2071. Incorporating ± 3years of deviation, the accuracy of type 1 and 2 were 0.2716, 0.7323 respectively; and the F1 score were 0.1709, 0.6437 respectively. CONCLUSIONS: The application of entire panorama image data for supervised with classification by heuristics grouping with ± 3years of deviation for supervised learning models and demonstrated satisfactory outcome for the age estimation.

Risk adjustment model for tuberculosis compared to non-tuberculosis mycobacterium or latent tuberculosis infection: Center for Personalized Precision Medicine of Tuberculosis (cPMTb) cohort database.

BACKGROUND: The Center for Personalized Precision Medicine of Tuberculosis (cPMTb) was constructed to develop personalized pharmacotherapeutic systems for tuberculosis (TB). This study aimed to introduce the cPMTb cohort and compare the distinct characteristics of patients with TB, non-tuberculosis mycobacterium (NTM) infection, or latent TB infection (LTBI). We also determined the prevalence and specific traits of polymorphisms in N-acetyltransferase-2 (NAT2) and solute carrier organic anion transporter family member 1B1 (SLCO1B1) phenotypes using this prospective multinational cohort. METHODS: Until August 2021, 964, 167, and 95 patients with TB, NTM infection, and LTBI, respectively, were included. Clinical, laboratory, and radiographic data were collected. NAT2 and SLCO1B1 phenotypes were classified by genomic DNA analysis. RESULTS: Patients with TB were older, had lower body mass index (BMI), higher diabetes rate, and higher male proportion than patients with LTBI. Patients with NTM infection were older, had lower BMI, lower diabetes rate, higher previous TB history, and higher female proportion than patients with TB. Patients with TB had the lowest albumin levels, and the prevalence of the rapid, intermediate, and slow/ultra-slow acetylator phenotypes were 39.2%, 48.1%, and 12.7%, respectively. The prevalence of rapid, intermediate, and slow/ultra-slow acetylator phenotypes were 42.0%, 44.6%, and 13.3% for NTM infection, and 42.5%, 48.3%, and 9.1% for LTBI, respectively, which did not differ significantly from TB. The prevalence of the normal, intermediate, and lower transporter SLCO1B1 phenotypes in TB, NTM, and LTBI did not differ significantly; 74.9%, 22.7%, and 2.4% in TB; 72.0%, 26.1%, and 1.9% in NTM; and 80.7%, 19.3%, and 0% in LTBI, respectively. CONCLUSIONS: Understanding disease characteristics and identifying pharmacokinetic traits are fundamental steps in optimizing treatment. Further longitudinal data are required for personalized precision medicine. TRIAL REGISTRATION: This study registered ClinicalTrials.gov NO. NCT05280886.

Randomised controlled trial of a behavioural intervention to reduce exposure to PM2.5 in patients with COPD.

BACKGROUND: Fine particulate matter (PM2.5) is a well-known risk factor for worse outcomes of chronic obstructive pulmonary disease (COPD). However, evidence-based guidance on effective personal behavioural strategies to minimise the effects of PM2.5 is limited. This study aimed to assess the effectiveness of a behavioural intervention in reducing PM2.5 exposure and improving clinical outcomes in patients with COPD. MATERIALS AND METHODS: Participants were 1:1 randomised, and the intervention group received a behavioural intervention consisting of five activities, while the control group received usual care. The participants were followed up for 9 months. The primary outcomes were differences in the score of St. George's Respiratory Questionnaire for patients with COPD (SGRQ-C) and COPD assessment test (CAT) from baseline. RESULTS: A total of 106 participants were enrolled and 102 completed the study. At the end of the study, the intervention group showed significant improvements in the primary outcomes compared to the control group, with a group difference of -5.9 in the reduction of total SGRQ-C (-3.4 vs. 2.5; p = 0.049) and -3.8 in the CAT score (-1.2 vs. 2.7; p = 0.001). Participants with good adherence to the intervention demonstrated a greater extent of improvement in CAT score and lower PM2.5 levels compared to those who had poor adherence or were in the control group. Regular checking of air quality forecasts was significantly associated with a reduction in CAT scores among all the intervention activities. CONCLUSION: Individual-level behavioural interventions can be an effective strategy for mitigating the health hazards associated with PM2.5. CLINICALTRIALS: gov Identifier: NCT04878367.

Comparing counseling outcome for college students: Metaverse and in-person approaches.

ABSTRACTObjective This study compared metaverse counseling with in-person counseling, using in-person counseling as a comparison group. To achieve this, we assessed whether metaverse counseling, a novel treatment approach, is comparable to traditional in-person counseling. Method: A total of 60 participants voluntarily participated in the study. Among the participants, 28 preferred in-person counseling, whereas 32 selected metaverse counseling as their preferred treatment option. Results and Conclusion: The findings indicated no statistically significant differences in the psychological symptom change patterns between the two counseling modalities. Both metaverse and in-person counseling demonstrated a common pattern of reduced symptom levels from pre-to post-session (Metaverse counseling Cohen's d = 1.04, In-person counseling Cohen's d = .62), which remained stable from post-session to follow-up regardless of the chosen counseling modality. Furthermore, the study revealed that the metaverse counseling group exhibited a higher level of working alliances than the in-person counseling group. Additionally, there was a slight tendency toward higher levels of counseling satisfaction in the metaverse counseling group than in the in-person counseling group. The results of this study support the use of synchronous metaverse programs to treat college students. The implications and limitations of this study are discussed. (195 words).

Three-Dimensional Surface Treatment of MoS2 Using BCl3 Plasma-Derived Radicals.

The realization of next-generation gate-all-around field-effect transistors (FETs) using two-dimensional transition metal dichalcogenide (TMDC) semiconductors necessitates the exploration of a three-dimensional (3D) and damage-free surface treatment method to achieve uniform atomic layer-deposition (ALD) of a high-k dielectric film on the inert surface of a TMDC channel. This study developed a BCl3 plasma-derived radical treatment for MoS2 to functionalize MoS2 surfaces for the subsequent ALD of an ultrathin Al2O3 film. Microstructural verification demonstrated a complete coverage of an approximately 2 nm-thick Al2O3 film on a planar MoS2 surface, and the applicability of the technique to 3D structures was confirmed using a suspended MoS2 channel floating from the substrate. Density functional theory calculations supported by optical emission spectroscopy and X-ray photoelectron spectroscopy measurements revealed that BCl radicals, predominantly generated by the BCl3 plasma, adsorbed on MoS2 and facilitated the uniform nucleation of ultrathin ALD-Al2O3 films. Raman and photoluminescence measurements of monolayer MoS2 and electrical measurements of a bottom-gated FET confirmed negligible damage caused by the BCl3 plasma-derived radical treatment. Finally, the successful operation of a top-gated FET with an ultrathin ALD-Al2O3 (∼5 nm) gate dielectric film was demonstrated, indicating the effectiveness of the pretreatment.

Cough Characteristics and Their Association Patterns According to Cough Etiology: A Network Analysis.

Although cough is a common respiratory symptom, determining its cause is challenging. We aimed to explore how cough severity and characteristics vary with different etiologies, while investigating their interrelations with demographic features. Adult patients (n = 220) with chronic cough and completed diagnostic work-up and the COugh Assessment Test were enrolled. A correlation network analysis was used to examine the associations between the demographic features and cough severity/characteristics across various etiologies such as upper airway cough syndrome, asthma, eosinophilic bronchitis, gastroesophageal reflux disease (GERD), and idiopathic cough. Demographic features like age and sex showed complex associations with cough characteristics and severity. Cough severity decreased with age, especially in cases of eosinophilic bronchitis and GERD. Women with eosinophilic bronchitis reported more severe cough, while men with idiopathic cough reported more severe cough. Asthma was significantly linked to more sleep disturbance and fatigue, independent of age and sex, whereas GERD showed less sleep disturbance and fatigue. Network analysis revealed overall close associations between cough characteristics, though hypersensitivity in asthma and sleep disturbance in GERD were not linked with other cough traits. In conclusion, the demographic features and cough characteristics were interrelated, exhibiting distinct patterns based on the etiology.

Azacyclic Anchor-Enabled Cohesive Graphite Electrodes for Sustainable Anion Storage.

Advanced energy-storage devices are indispensable for expanding electric mobility applications. While anion intercalation-type redox chemistry in graphite cathodes has opened the path to high-energy-density batteries, surpassing the limited energy density of conventional lithium-ion batteries , a significant challenge remains: the large volume expansion of graphite upon anion intercalation. In this study, a novel polymeric binder and cohesive graphite cathode design for dual-ion batteries (DIBs) is presented, which exhibits remarkable stability even under high voltage conditions (>5 V). The innovative binder incorporates an acrylate moiety ensuring superior oxidative stability and self-healing features, along with an azide moiety, which allows for azacyclic covalent bonding with graphite and interchain crosslinking. A simple 1-h ultraviolet treatment is sufficient for binder fixation within the electrode, leading to the covalent bond formation with graphite and the creation of a robust three-dimensional network. This modification facilitates deeper and more reversible anion intercalation, leading to improved capacity, extended lifespan, and sustainable anion storage. The binder design, exhibiting exceptional adhesive properties and effective stress mitigation, enables the construction of ultrathick graphite cathodes. These findings provide valuable insights for the development of advanced binders, paving the way for high-performance DIBs.

Prediction Model for Pre-Eclampsia Using Gestational-Age-Specific Serum Creatinine Distribution.

Pre-eclampsia (PE) is a pregnancy-related disease, causing significant threats to both mothers and babies. Numerous studies have identified the association between PE and renal dysfunction. However, in clinical practice, kidney problems in pregnant women are often overlooked due to physiologic adaptations during pregnancy, including renal hyperfiltration. Recent studies have reported serum creatinine (SCr) level distribution based on gestational age (GA) and demonstrated that deviations from the expected patterns can predict adverse pregnancy outcomes, including PE. This study aimed to establish a PE prediction model using expert knowledge and by considering renal physiologic adaptation during pregnancy. This retrospective study included pregnant women who delivered at the Wonju Severance Christian Hospital. Input variables, such as age, gestational weeks, chronic diseases, and SCr levels, were used to establish the PE prediction model. By integrating SCr, GA, GA-specific SCr distribution, and quartile groups of GA-specific SCr (GAQ) were made. To provide generalized performance, a random sampling method was used. As a result, GAQ improved the predictive performance for any cases of PE and triple cases, including PE, preterm birth, and fetal growth restriction. We propose a prediction model for PE consolidating readily available clinical blood test information and pregnancy-related renal physiologic adaptations.

Nonporous Oxide-Terminated Multicomponent Bulk Anode Enabling Energy-Dense Sodium-Ion Batteries.

Sodium-ion batteries (SIBs) are emerging as power sources for large-scale storage owing to their abundant and inexpensive sodium (Na) source, but their limited energy density hinders their commercialization. High-capacity anode materials, such as antimony (Sb), which are potential energy boosters for SIBs, suffer from battery degradation owing to large-volume-changes and structural instability. The rational design of bulk Sb-based anodes to enhance the initial reversibility and electrode density inevitably requires atomic- and microscale-considered internal/external buffering or passivation layers. However, unsuitable buffer engineering causes electrode degradation and lowers energy density. Herein, the rationally designed intermetallic inner and outer oxide buffers for bulk Sb anodes are reported. The two chemistries in the synthesis process provide an atomic-scale aluminum (Al) buffer within the dense microparticles and an external mechanically stabilizing dual oxide layer. The prepared nonporous bulk Sb anode maintained excellent reversible capacity at a high current density and Na-ion full battery evaluations with Na3V2(PO4)3 (NVP) showing negligible capacity decay over 100 cycles. The demonstrated buffer designs for commercially favorable micro-sized Sb and intermetallic AlSb shed light on the stabilization of high-capacity or large-volume-change electrode materials for various metal-ion rechargeable batteries.

The efficacy of supervised learning and semi-supervised learning in diagnosis of impacted third molar on panoramic radiographs through artificial intelligence model.

OBJECTIVES: The aim of the study was to evaluate the efficacy of traditional supervised learning (SL) and semi-supervised learning (SSL) in the classification of mandibular third molars (Mn3s) on panoramic images. The simplicity of preprocessing step and the outcome of the performance of SL and SSL were analyzed. METHODS: Total 1625 Mn3s cropped images from 1000 panoramic images were labeled for classifications of the depth of impaction (D class), spatial relation with adjacent second molar (S class), and relationship with inferior alveolar nerve canal (N class). For the SL model, WideResNet (WRN) was applicated and for the SSL model, LaplaceNet (LN) was utilized. RESULTS: In the WRN model, 300 labeled images for D and S classes, and 360 labeled images for N class were used for training and validation. In the LN model, only 40 labeled images for D, S, and N classes were used for learning. The F1 score were 0.87, 0.87, and 0.83 in WRN model, 0.84, 0.94, and 0.80 for D class, S class, and N class in the LN model, respectively. CONCLUSIONS: These results confirmed that the LN model applied as SSL, even utilizing a small number of labeled images, demonstrated the satisfactory of the prediction accuracy similar to that of the WRN model as SL.

Prediction models for respiratory outcomes in patients with COVID-19: integration of quantitative computed tomography parameters, demographics, and laboratory features.

Background: We aimed to develop integrative machine-learning models using quantitative computed tomography (CT) parameters in addition to initial clinical features to predict the respiratory outcomes of coronavirus disease 2019 (COVID-19). Methods: This was a retrospective study involving 387 patients with COVID-19. Demographic, initial laboratory, and quantitative CT findings were used to develop predictive models of respiratory outcomes. High-attenuation area (HAA) (%) and consolidation (%) were defined as quantified percentages of the area with Hounsfield units between -600 and -250 and between -100 and 0, respectively. Respiratory outcomes were defined as the development of pneumonia, hypoxia, or respiratory failure. Multivariable logistic regression and random forest models were developed for each respiratory outcome. The performance of the logistic regression model was evaluated using the area under the receiver operating characteristic curve (AUC). The accuracy of the developed models was validated by 10-fold cross-validation. Results: A total of 195 (50.4%), 85 (22.0%), and 19 (4.9%) patients developed pneumonia, hypoxia, and respiratory failure, respectively. The mean patient age was 57.8 years, and 194 (50.1%) were female. In the multivariable analysis, vaccination status and levels of lactate dehydrogenase, C-reactive protein (CRP), and fibrinogen were independent predictors of pneumonia. The presence of hypertension, levels of lactate dehydrogenase and CRP, HAA (%), and consolidation (%) were selected as independent variables to predict hypoxia. For respiratory failure, the presence of diabetes, levels of aspartate aminotransferase, and CRP, and HAA (%) were selected. The AUCs of the prediction models for pneumonia, hypoxia, and respiratory failure were 0.904, 0.890, and 0.969, respectively. Using the feature selection in the random forest model, HAA (%) was ranked as one of the top 10 features predicting pneumonia and hypoxia and was first place for respiratory failure. The accuracies of the cross-validation of the random forest models using the top 10 features for pneumonia, hypoxia, and respiratory failure were 0.872, 0.878, and 0.945, respectively. Conclusions: Our prediction models that incorporated quantitative CT parameters into clinical and laboratory variables showed good performance with high accuracy.

Fibrosis score predicts mortality in patients with fibrotic hypersensitivity pneumonitis.

Background: Variable clinical courses make it challenging to predict mortality resulting from fibrotic hypersensitivity pneumonitis (HP). This study evaluated the usefulness of radiologic parameters for predicting mortality in patients with fibrotic HP. Methods: Clinical data and high-resolution computed tomography (HRCT) images, which were scored for reticulation, honeycombing, ground glass opacity (GGO), consolidation, and mosaic attenuation (MA) by visual assessment, were retrospectively analyzed in a total of 101 patients with fibrotic HP (all biopsy-proven cases). Fibrosis score was defined as the sum of reticulation and honeycombing scores. Results: The mean age of the 101 patients was 58.9 years, and 60.4% were females. During the follow-up (median: 55.5 months; interquartile range: 37.7-89.0 months), the 1-, 3-and 5-year mortality rates were 3.9, 16.8, and 32.7%, respectively. The non-survivors were older and had significantly lower lung function and minimum oxygen saturation during the 6-min walk test than the survivors. The non-survivors had higher scores of reticulation, honeycombing, GGO, fibrosis, and MA on HRCT than survivors. In the multivariable Cox analysis, reticulation, GGO, and fibrosis scores were independent prognostic factors for mortality in patients with fibrotic HP, as well as age. Fibrosis score showed great performance for predicting the 5-year mortality (AUC = 0.752, p < 0.001) and higher mortality was recorded for patients with high fibrosis score (≥12.0%) (the mean survival time: 58.3 vs. 146.7 months, p < 0.01) than those without. Conclusion: Our results suggest that radiologic fibrosis score may be a useful predictor of mortality in patients with fibrotic HP.

Clinical phenotypes of chronic cough categorised by cluster analysis.

BACKGROUND: Chronic cough is a heterogeneous disease with various aetiologies that are difficult to determine. Our study aimed to categorise the phenotypes of chronic cough. METHODS: Adult patients with chronic cough were assessed based on the characteristics and severity of their cough using the COugh Assessment Test (COAT) and the Korean version of the Leicester Cough Questionnaire. A cluster analysis was performed using the K-prototype, and the variables to be included were determined using a correlation network. RESULTS: In total, 255 participants were included in the analysis. Based on the correlation network, age, score for each item, and total COAT score were selected for the cluster analysis. Four clusters were identified and characterised as follows: 1) elderly with mild cough, 2) middle-aged with less severe cough, 3) relatively male-predominant youth with severe cough, and 4) female-predominant elderly with severe cough. All clusters had distinct demographic and symptomatic characteristics and underlying causes. CONCLUSIONS: Cluster analysis of age, score for each item, and total COAT score identified 4 distinct phenotypes of chronic cough with significant differences in the aetiologies. Subgrouping patients with chronic cough into homogenous phenotypes could provide a stratified medical approach for individualising diagnostic and therapeutic strategies.

Effects of gastroesophageal reflux disease treatment with proton pump inhibitors on the risk of acute exacerbation and pneumonia in patients with COPD.

BACKGROUND: Gastroesophageal reflux disease (GERD) has been suggested as a risk factor for acute exacerbation of chronic obstructive pulmonary disease (COPD). However, it remains undetermined whether proton pump inhibitor (PPI) treatment reduces the risk of exacerbation or affects the risk of pneumonia. This study aimed to evaluate the risks of both exacerbation and pneumonia following PPI treatment for GERD in patients with COPD. METHODS: This study used a reimbursement database of the Republic of Korea. Patients aged ≥ 40 years with COPD as a main diagnosis and who received PPI treatment for GERD at least for 14 consecutive days between January 2013 and December 2018 were included in the study. A self-controlled case series analysis was conducted to calculate the risk of moderate and severe exacerbation and pneumonia. RESULTS: A total of 104,439 patients with prevalent COPD received PPI treatment for GERD. The risk of moderate exacerbation was significantly lower during the PPI treatment than at baseline. The risk of severe exacerbation increased during the PPI treatment but significantly decreased in the post-treatment period. Pneumonia risk was not significantly increased during the PPI treatment. The results were similar in patients with incident COPD. CONCLUSIONS: The risk of exacerbation was significantly reduced after PPI treatment compared with the non-treated period. Severe exacerbation may increase due to uncontrolled GERD but subsequently decrease following PPI treatment. There was no evidence of an increased risk of pneumonia.