Tuberculosis and Respiratory Diseases最新文献

Background: Respiratory infection is a major cause of acute exacerbation of chronic obstructive pulmonary disease (AECOPD). We investigated the presence of bacterial and viral pathogens and clinical features in patients with AECOPD.

Methods: This retrospective study included 1,186 patients diagnosed with AECOPD from 28 hospitals in South Korea between 2015-2018. Pathogen identification rates, basic characteristics and clinical features, and associated factors for infection with potentially drug-resistant (PDR) pathogens were evaluated using microbiological tests.

Results: Bacteria, viruses, and both were found in 262 (22.1%), 265 (22.5%), and 129 (10.9%) patients, respectively. The most common pathogens were Pseudomonas aeruginosa (17.8%), Mycoplasma pneumoniae (11.2%), Streptococcus pneumoniae (9.0%), influenza A virus (19.0%), rhinovirus (15.8%), and respiratory syncytial virus (6.4%). A history of pulmonary tuberculosis (OR 1.66; P=0.046), bronchiectasis (OR 1.99; P=0.032), and triple inhaler use within six months (OR 2.04; P=0.005) were significant associated factors for PDR pathogen infection. Hospital stay length (15.9 days vs. 12.4 days; P=0.018) and ICU admission rates (15.9% vs. 9.5%; P=0.030) were increased in patients infected with PDR pathogens.

Conclusions: This study indicates that various types of pathogens are implicated during AECOPD. However, further research is needed to confirm whether these pathogens influence AECOPD development and progression.

Thoracic radiology is a primary field where artificial intelligence (AI) has been extensively researched. Recent advancements in AI demonstrate potential improvements in radiologists' performance. AI facilitates the detection and classification of abnormalities, as well as the quantification of both normal and abnormal anatomical structures. Furthermore, it enables prognostication based on these quantitative values. In this review article, the recent achievements of AI in thoracic radiology will be reviewed, mainly focused on deep learning, and the current limitations and future directions of this cutting-edge technique will be discussed.

A significant portion of newly diagnosed lung cancer cases occur in populations exposed to air pollution. The World Health Organization has identified air pollution as a human carcinogen, prompting many countries to implement monitoring systems for ambient particulate matter (PM). PM consists of a complex mix of organic and inorganic particles, both solid and liquid, present in the air. Given the carcinogenic properties of PM and the prevalence of lung cancer in exposed populations, it is crucial to explore their connection and clinical implications to effectively prevent lung cancer in this group. This review examines the link between ambient PM and lung cancer. Epidemiological studies have shown a dose-response relationship between PM exposure and lung cancer risk. PM exposure leads to oxidative stress, disrupting the body's redox balance and causing DNA damage, a key factor in cancer development. Recent findings on the strong correlation between ambient PM and adenocarcinoma suggest that understanding the specific molecular and pathological background of pollution-related lung cancer is important. In addition to efforts to control emission sources at the international level, a more individualized approach is necessary to prevent PM-related lung cancer development.

Backgrounds: The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the Clinical Frailty Scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization.

Methods: We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥ 5 at hospital discharge.

Results: Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2 ± 12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4 ± 0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3-4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty.

Conclusion: Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.

Background: High-resolution chest computed tomography (CT) is a crucial assessment tool for diagnosis of Birt-Hogg-Dubé syndrome (BHD). This study aims to analyze the differences of lung cyst between BHD and other cystic lung diseases.

Methods: From January 2020 to December 2022, we retrospectively screened all patients who underwent chest CT at Gangnam Severance Hospital. We included the patients with multiple lung cysts for the analysis of chest CT images.

Results: Over a three-year period, out of 52,823 patients who underwent a chest CT scan, 301 patients (0.6%) with multiple lung cysts were enrolled, of which 24 (8.0%) were diagnosed with BHD. Notably, 95.8% and 83.3% of BHD patients exhibited bilateral cysts and basal predominance, and had larger cysts with a maximal diameter (averaging 32.1mm [interquartile range 26.5mm to 43.5mm]) than lymphangioleiomyomatosis (17.0mm [13.2;19.1], p<0.001) and others' group (11.3mm [7.9;17.0], p<0.001). Additionally, 95.8% of BHD patients has a diverse range in cyst sizes and morphologies. Multivariate logistic regression analysis identified bilateral cysts (OR 12.393, 95% CI: 1.613-274.682, p=0.038), basal predominance (OR 8.511, 95% CI: 2.252-39.392, p=0.002), maximum diameter (OR 1.053, 95% CI: 1.009-1.108, p=0.032), and diversity of morphology (OR 19.513, 95% CI: 2.833-398.119, p=0.010) as factors associated with BHD diagnosis. By stepwise selection, a multivariate prediction model for BHD diagnosis was established, demonstrating a sensitivity of 95.83%, a specificity of 81.22%, and an AUC of 0.951 (95% CI: 0.914-0.987).

Conclusion: Distinguishing features of lung cyst from other cystic lung diseases include bilateral cysts, basal dominance, large size, and irregular shape. The predictive model can assist in identifying undiagnosed patients with BHD.

Background: The sequelae of post-coronavirus disease 2019 (COVID-19) pneumonia on lung function, exercise capacity, and quality of life were observed in both shortterm and long-term. However, the study about the respiratory and locomotor muscle strength in severe and critically ill COVID-19 survivors are still limited. Therefore, we aimed to examine long-term pulmonary function, functional capacities, and respiratory and locomotor body muscle strength in severe to critically ill post-COVID-19 survivors.

Methods: A prospective observational study was conducted in 22 post-COVID-19 pneumonia and healthy adults. Clinical characteristics during admission, pulmonary function, functional capacity, respiratory muscles, and locomotor muscles strength were examined at 1, 3, and 6 months after discharge from the hospital.

Results: The generalized linear mixed model showed that percent predicted of forced expiratory volume in the 1 second (%FEV1), percent predicted of forced vital capacity (%FVC), maximum inspiratory pressure (MIP), handgrip strength, 6-minute walk distance, and five times sit to stand (5TSTS) were significantly lower in post-COVID-19 pneumonia patients than in healthy subjects during the follow-up period. The percent predicted of maximal voluntary ventilation (%MVV), and locomotor muscle strength were not different between the two groups throughout the follow-up period. Among post-COVID-19 pneumonia patients, %FEV1, %FVC, %MVV, 5TSTS, locomotor muscle strength significantly improved at three months compared to baseline at 1 month.

Conclusion: Pulmonary function, functional capacity, respiratory, and locomotor muscle strength of survivors from COVID-19 were impaired and recovery was observed after three to six months. These emphasized the need to evaluate the long-term consequences of COVID-19.

Background: Patients with chronic obstructive pulmonary disease (COPD) expressing eosinophilia experience slightly fewer episodes of community-acquired pneumonia (CAP), than those without eosinophilia. However, the severity and burden of hospitalized pneumonia patients with COPD involving eosinophilia have not been assessed.

Methods: We evaluated the differences in clinical characteristics between patients with CAP and COPD with or without eosinophilia by a post hoc analysis of a prospective, multi-center, cohort study data.

Results: Of 349 CAP patients with COPD, 45 (12.9%) had eosinophilia (blood eosinophil ≥300 cells/μL). Patients with eosinophilia had a lower sputum culture percentile (8.1% vs. 23.4%, p<0.05), a lower percentile of neutrophils (70.3% vs. 80.2%, p<0.05), reduced C-reactive protein levels (30.6 mg/L vs. 86.6 mg/L, p<0.05), and a lower pneumonia severity index score (82.5 vs. 90.0, p<0.05), than those without eosinophilia. The duration of antibiotic treatment (8.0 days vs. 10.0 days, p<0.05) and hospitalization (7.0 days vs. 9.0 days, p<0.05) were shorter in eosinophilic patients. The cost of medical care per day (256.4 US$ vs. 291.0 US$, p<0.05), cost for the medication (276.4 US$ vs. 349.9 US$, p<0.05), and cost for examination (685.5 US$ vs. 958.1 US$, p<0.05) were lower in patients with eosinophilia than those without eosinophilia.

Conclusion: Eosinophilia serves as a favorable marker for the severity of pneumonia, health-care consumption, and cost of medical care in patients with CAP and COPD.

Background: Successful liberation from mechanical ventilation is one of the most crucial processes in critical care, because it is the first step through which a respiratory failure patient begins to transition out of the intensive care unit, and return to normal life. Therefore, when devising appropriate strategies for removing mechanical ventilation, it is essential to consider scientific and systematic approaches, as well as the individual experiences of healthcare professionals. Recently, numerous studies have investigated methods and tools to identify when mechanically ventilated patients are ready to breathe on their own. The Korean Society of Critical Care Medicine therefore provides these recommendations to clinicians for liberation from the ventilator.

Methods: Meta-analyses and comprehensive syntheses were used to thoroughly review, compile, and summarize the complete body of relevant evidence. All studies were meticulously assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) method, and the outcomes were presented succinctly as evidence profiles. These evidence syntheses were discussed by a multidisciplinary committee of experts in mechanical ventilation, who then developed and approved the recommendations.

Results: Recommendations for nine questions on ventilator liberation about Population, Intervention, Comparator, and Outcome (PICO) are presented in this document. This guideline presents seven conditional recommendations, one expert consensus recommendation, and one conditional deferred recommendation.

Conclusion: We developed these clinical guidelines for mechanical ventilation liberation to provide meaningful recommendations. These guidelines reflect the best treatment for patients seeking liberation from mechanical ventilation.

Bronchiectasis is a chronic respiratory disease characterized by abnormal dilation of the bronchi that causes cough, sputum, and recurrent infections. As it may be associated with various respiratory or systemic diseases, a critical aspect of managing bronchiectasis is to identify the underlying cause. Immunodeficiency is a rare but important cause of bronchiectasis, and its treatability is a significant trait for bronchiectasis management. While primary immunodeficiencies in bronchiectasis are well recognized, secondary immunodeficiencies remain under-reported and under-researched. Secondary immunodeficiencies may result from various diseases and conditions, such as hematologic malignancies, human immunodeficiency virus infection, renal transplantation, or the use of immunosuppressive drugs, and may contribute to the occurrence of bronchiectasis. Recurrent pulmonary and/or extrapulmonary infections in bronchiectasis may indicate the presence of secondary immunodeficiency in patients with these underlying conditions. For treatment, examining the underlying condition, managing bronchiectasis adequately, and prophylactic antibiotics (e.g., macrolide) and/or supplementary immunoglobulin G therapy may provide potential benefits. Considering the projected increase in the prevalence of secondary immunodeficiencies and bronchiectasis, future guidelines and research on the diagnosis and optimized treatment are needed.