10개 논문이 있습니다.
The introduction of inhaled corticosteroids (ICS) for the management of asthma hasled to a decrease in acute exacerbation of asthma. However, there are concerns regardingthe safety of long-term ICS use, particularly pneumonia. Growing evidenceindicates that ICS use is associated with an increased risk of pneumonia in patientswith chronic obstructive pulmonary disease, whereas the risk in patients with asthmaremains unclear. This review discusses the effect of ICS on pneumonia among patientswith asthma to update the existing literature. Asthma is associated with an increasedrisk of pneumonia. Several hypotheses have been proposed to explain this association,including that asthma impairs the clearance of bacteria owing to chronic inflammation. Therefore, controlling airway inflammation with ICS may prevent the occurrence ofpneumonia in asthma. In addition, two meta-analyses investigating randomized controltrials showed that ICS use was associated with a protective effect against pneumoniain asthma.
Asthma is a chronic inflammatory airway disease that is characterized by variable airflowobstruction. The Korean Asthma Study Group of the Korean Academy of Tuberculosisand Respiratory Diseases has recently updated the Korean Asthma Guideline. This review summarizes the updated Korean Asthma Guideline. Asthma prevalence isincreasing worldwide, and in Korea. Variable airflow obstruction can be confirmed bybronchodilator response or other tests, and should be established prior to the controllermedication. A low-dose inhaled corticosteroid-formoterol is used to alleviate symptomsin all treatment step, and it can be used as a controller as well as reliever in steps3–5. This approach is preferred, because it reduces the risk of severe exacerbations,compared to the use of short-acting β2-agonist as reliever. In severe asthma, phenotype/endotype based on the underlying inflammation should be evaluated. For type 2severe asthma, the biologics should be considered.
Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity andmortality worldwide. The lower airways contain a rich and diverse microbiome, whichmay play a significant regulatory role in both health and disease. In COPD, the microbiomebecomes perturbed, causing dysbiosis. Increased representation of membersin the Proteobacteria phylum and certain members in the Firmicutes phylum has beenassociated with increased risk of exacerbations and mortality. Therapies such as inhaledcorticosteroids and azithromycin may modulate the airway microbiome or itsmetabolites in patients with COPD. This paper provides an up-to-date overview of theairway microbiome and its importance in the pathophysiology of COPD and as potentialtherapeutic target in the future.
Since the introduction of low-dose computed tomography (CT) screening for patients athigh risk of lung cancer, the detection rate of suspicious lung cancer has increased. Inaddition, there have been many advances in therapeutics targeting oncogenic driversin non-small cell lung cancer. Therefore, accurate pathological diagnosis of lung cancer,including molecular diagnosis, is increasingly important. This review examines theproblems in the pathological diagnosis of suspected lung cancer. For successful pathologicaldiagnosis of lung cancer, clinicians should determine the appropriate modalityof the diagnostic procedure, considering individual patient characteristics, CT findings,and the possibility of complications. Furthermore, clinicians should make efforts toobtain a sufficient amount of tissue sample using non- or less-invasive procedures forpathological diagnosis and biomarker analysis.
Bronchiectasis, which is characterized by irreversibly damaged and dilated bronchi,causes significant symptoms, poor quality of life, and increased economic burdenand mortality rates. Despite its increasing prevalence and clinical significance, bronchiectasiswas previously regarded as an orphan disease, and ideal treatment of thisdisease has been poorly understood. The European Respiratory Society and BritishThoracic Society have recently published guidelines to assist physicians in the clinicalfield. Guidelines and reports suggest comprehensive management that includes bothnon-pharmacological and pharmacological treatment. Physiotherapy and pulmonaryrehabilitation are two of the most important non-pharmacologic therapies in bronchiectasispatients; long-term inhaled antibiotics and macrolide therapy have gained significantevidence in reducing exacerbation risk in frequent exacerbators. In this review, wesummarize recent updates on bronchiectasis treatment to prevent exacerbation andmanage clinical deterioration.
Background: The Global Initiative for Chronic Obstructive Lung Disease (GOLD) update2023 proposed new definitions of chronic obstructive pulmonary disease (COPD)and COPD exacerbation. However, an agreement on the definitions has not been made,either internationally or domestically. This study aimed to reach an agreement betweenexperts on the new definitions of COPD and COPD exacerbation in South Korea. Methods: A modified Delphi method was used to make an agreement on the definitionsof COPD and COPD exacerbation proposed by the GOLD update 2023. We performedtwo rounds of the survey including 15 Korean experts on COPD, asthma, andtuberculosis. Results: More than two-thirds of the experts agreed on 12 of the 13 statements relatedto the definitions of COPD and COPD exacerbation in the two rounds of the survey. The experts agreed on the definitions of COPD and COPD exacerbation that should berevised in line with the definitions proposed by the GOLD update 2023. However, theexperts showed an uncertain opinion on the statement that the definition of COPD includespatients with persistent airflow obstruction due to bronchiectasis. Conclusion: Based on this Delphi survey, experts’ agreement was made on the definitionsof COPD and COPD exacerbation proposed by the GOLD update 2023.
Background: Surgical resection is the standard treatment for early-stage lung cancer. Since postoperative lung function is related to mortality, predicted postoperative lungfunction is used to determine the treatment modality. The aim of this study was to evaluatethe predictive performance of linear regression and machine learning models. Methods: We extracted data from the Clinical Data Warehouse and developed threesets: set I, the linear regression model; set II, machine learning models omitting themissing data: and set III, machine learning models imputing the missing data. Six machinelearning models, the least absolute shrinkage and selection operator (LASSO),Ridge regression, ElasticNet, Random Forest, eXtreme gradient boosting (XGBoost),and the light gradient boosting machine (LightGBM) were implemented. The forced expiratoryvolume in 1 second measured 6 months after surgery was defined as the outcome. Five-fold cross-validation was performed for hyperparameter tuning of the machinelearning models. The dataset was split into training and test datasets at a 70:30ratio. Implementation was done after dataset splitting in set III. Predictive performancewas evaluated by R2 and mean squared error (MSE) in the three sets. Results: A total of 1,487 patients were included in sets I and III and 896 patientswere included in set II. In set I, the R2 value was 0.27 and in set II, LightGBM was thebest model with the highest R2 value of 0.5 and the lowest MSE of 154.95. In set III,LightGBM was the best model with the highest R2 value of 0.56 and the lowest MSE of174.07. Conclusion: The LightGBM model showed the best performance in predicting postoperativelung function.
Background: Tuberculosis (TB)-related stigma has been well-documented. Since theemergence of the coronavirus disease 2019 (COVID-19), different organizations havebeen alerted to the fact that stigma could arise again. Due to stigma’s negative effects,this qualitative study aimed to explore the stigma felt by patients by evaluating the following:COVID-19 stigma and its temporal progression through the pandemic; stigmaperceived by different patients with TB before and during COVID-19 pandemic; and differenceperceived by individuals who contracted both diseases. Methods: A semi-structured interview was developed according to the available literatureon the theme. It was performed individually in 2022 upon receiving signedinformed consent. Participants were recruited with a purposive sampling approach bysearching medical records. Those who currently or previously had pulmonary TB and/or COVID-19 were included. Data were subjected to thematic analysis. Results: Nine patients were interviewed, including six (66.7%) females. The median ageof patients was 51±14.7 years. Four participants (44.4%) had completed high schooland four (44.4%) were never smokers. Three had both TB and COVID-19. Four only hadTB and two only had COVID-19. Interviews identified eight main themes: knowledgeand beliefs, with several misconceptions identified; attitudes towards the disease, varyingfrom social support to exclusion; knowledge and education, assumed as of extremeimportance; internalized stigma, with self-rejection; experienced stigma, with discriminationepisodes; anticipated stigma, modifying actions for avoiding stigma; perceivedstigma, with judgment by others prevailed; and temporal evolution of stigma. Conclusion: Individuals expressed strong stigma for both diseases. De-stigmatizationof respiratory infectious diseases is crucial for limiting stigma’s negative impact.
Background: Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is oftenfound in high TB incidence countries, and to avoid unnecessary evaluation and medication,differentiation from active TB is important. This study develops a deep learning (DL)model to estimate activity in a single chest radiographic analysis. Methods: A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRsfrom 558 individuals were retrospectively collected. A pretrained convolutional neuralnetwork was fine-tuned to classify active and inactive TB. The model was pretrainedwith 8,964 pneumonia and 8,525 normal cases from the National Institute of Health(NIH) dataset. During the pretraining phase, the DL model learns the following tasks:pneumonia vs. normal, pneumonia vs. active TB, and active TB vs. normal. The performanceof the DL model was validated using three external datasets. Receiver operatingcharacteristic analyses were performed to evaluate the diagnostic performance to determineactive TB by DL model and radiologists. Sensitivities and specificities for determiningactive TB were evaluated for both the DL model and radiologists. Results: The performance of the DL model showed area under the curve (AUC) valuesof 0.980 in internal validation, and 0.815 and 0.887 in external validation. The AUC valuesfor the DL model, thoracic radiologist, and general radiologist, evaluated using oneof the external validation datasets, were 0.815, 0.871, and 0.811, respectively. Conclusion: This DL-based algorithm showed potential as an effective diagnostic toolto identify TB activity, and could be useful for the follow-up of patients with inactive TBin high TB burden countries.
Background: Effective treatment of fluoroquinolone-resistant multidrug-resistant tuberculosis(FQr-MDR-TB) is difficult because of the limited number of available core anti-TBdrugs and high rates of resistance to anti-TB drugs other than FQs. However, few studieshave examined anti-TB drugs that are effective in treating patients with FQr-MDR-TBin a real-world setting. Methods: The impact of anti-TB drug use on treatment outcomes in patients with pulmonaryFQr-MDR-TB was retrospectively evaluated using a nationwide integrated TBdatabase (Korean Tuberculosis and Post-Tuberculosis). Data from 2011 to 2017 wereincluded. Results: The study population consisted of 1,082 patients with FQr-MDR-TB. The overalltreatment outcomes were as follows: treatment success (69.7%), death (13.7%),lost to follow-up or not evaluated (12.8%), and treatment failure (3.9%). On a propensity-score-matched multivariate logistic regression analysis, the use of bedaquiline (BDQ),linezolid (LZD), levofloxacin (LFX), cycloserine (CS), ethambutol (EMB), pyrazinamide,kanamycin (KM), prothionamide (PTO), and para-aminosalicylic acid against susceptiblestrains increased the treatment success rate (vs. unfavorable outcomes). The use ofLFX, CS, EMB, and PTO against susceptible strains decreased the mortality (vs. treatmentsuccess). Conclusion: A therapeutic regimen guided by drug-susceptibility testing can improvethe treatment of patients with pulmonary FQr-MDR-TB. In addition to core anti-TB drugs,such as BDQ and LZD, treatment of susceptible strains with later-generation FQs andKM may be beneficial for FQr-MDR-TB patients with limited treatment options.