Pulmonary Medicine最新文献

Introduction: Heated, humidified high-flow air (HHHFA) has been shown to reduce exacerbations in patients with COPD or bronchiectasis with significant sputum production. This pilot study evaluated the short-term effects of nocturnal HHHFA in COPD patients with chronic bronchitis.

Methods: This was a prospective, single-center, open-label, randomized, placebo-controlled trial. Participants with COPD, chronic bronchitis, and ≥ 2 exacerbations in the prior year were randomized to either nocturnal HHHFA or usual care. Assessments included sleep quality, dyspnea, quality of life, cough, lung function, imaging, and exercise capacity at baseline and 6 weeks.

Results: Of 11 eligible participants, seven completed the study (four intervention, three control). Baseline characteristics were generally similar, though the intervention group had a higher BMI and a lower emphysema percentage. No statistically significant differences were observed between groups in primary or secondary outcomes.

Conclusions: Nocturnal HHHFA over 6 weeks did not improve clinical or imaging outcomes in this small cohort of COPD patients with chronic bronchitis. The study was likely underpowered due to recruitment challenges. Larger trials are needed to assess the potential of HHHFA in this population.

Trial registration: ClinicalTrials.gov identifier: NCT03959982.

Background: Cystic fibrosis (CF) is an autosomal recessive disorder caused by variants in the CFTR gene. Although the F508del mutation is common globally, the Middle East exhibits a higher prevalence of rare, region-specific variants. The triple-combination therapy elexacaftor/tezacaftor/ivacaftor (ETI) has revolutionized CF management; however, its efficacy in individuals with rare variants, often underrepresented in clinical trials, remains less certain. This study is aimed at evaluating the real-world outcomes of ETI therapy in CF patients with rare CFTR variants predominantly found in the Middle East.

Methods: This retrospective, single-center study included 12 patients with CF carrying rare Middle Eastern variants. Data on percent predicted Forced Expiratory Volume in 1 second (ppFEV1), body mass index (BMI), and annual exacerbation frequency were collected before and after 12 months of ETI treatment. Nine of these patients were previously on ivacaftor and were switched to ETI. Changes in clinical outcomes were analyzed using Wilcoxon signed-rank tests due to nonnormally distributed data.

Results: Following 12 months of ETI therapy, significant improvements were observed. The median ppFEV1 increased by 9.5% (range: 2-15). The median annual frequency of exacerbations decreased by two events (range: 0-4). BMI showed a modest median improvement of 1.5 kg/m², which was not statistically significant. The cohort comprised nine females (75%) and three males (25%), with a median age of 24.3 years (range: 18.5-35.2 years) at the time of ETI initiation or transition.

Conclusion: ETI therapy led to statistically significant improvements in lung function and a reduction in pulmonary exacerbations in CF patients with rare Middle Eastern variants. These findings, from the first report of its kind in this region, support the expansion of ETI access to individuals with rare CFTR variants, particularly in underserved populations, based on functional response. This underscores the benefit of ETI beyond the common F508del mutation.

Introduction: Pulmonary embolism (PE) is the third leading cause of cardiovascular death after stroke and myocardial infarction. Accurate and timely identification of patients could have a significant impact on reducing the mortality rate and better patient management.

Aim: The purpose of this study was to evaluate the diagnostic performance of quantitative parameters measured based on CTPA images to determine the most important and relevant imaging parameters for diagnosing patients with PE.

Methods and materials: In this cross-sectional, multicenter study, the electronic files of 1428 cases suspected of PE were reviewed from 2021 to 2023. The diagnostic performances of anthropometric parameters, right ventricle-to-left ventricle (LV) diameter ratio, and CT obstruction index measured based on CTPA images were evaluated for the diagnosis of PTE.

Results: Radiological manifestations associated with PE were IV septum deviation, RV/LV diameter ratio, CT obstruction score, and pulmonary infarction with OR values of 10.53, 38.71, 6.59, and 78.16, respectively (p < 0.001). CT obstruction index with a threshold of 1 was the best parameter for the diagnosis of PE. Accuracy, sensitivity, specificity, and AUC of the CT obstruction index were 96.10%, 98.68%, 94.84%, and 0.96%, respectively. Pulmonary infarction with multifocal involvement as the second strongest parameter had a sensitivity of 81.58%, specificity of 98.76%, accuracy of 93.25%, kappa coefficient of 0.93, and an AUC of 0.90.

Conclusion: CT obstruction index and pulmonary infarction with multifocal involvement perform better than the reports of the presence of disease in CTPA images. Therefore, these two parameters must be reported by radiologists and implemented as the primary criteria for diagnosing PE.

Introduction: COVID-19 has infected many patients globally, primarily impacting the respiratory system and causing symptoms such as coughing and shortness of breath. Various factors influence the severity of the infection, with obstructive sleep apnea (OSA) being one of them.

Aims: The aim was to investigate the correlation between the severity of OSA and the severity of COVID-19 infection, as indicated by hospitalization, ICU admission, and the duration of recovery from the disease.

Methodology: A retrospective cohort study on OSA patients who follow-up at a tertiary referral hospital sleep clinic and were infected with COVID-19. COVID-19 infection information, such as severity, duration, and vaccination, was collected via phone calls. OSA severity was assessed using the apnea-hypopnea index (AHI). Data were analyzed using SPSS software, and a p value < 0.05 was considered significant.

Results: A total of 136 confirmed OSA and COVID-19-positive patients were included in the study. The majority were elderly and obese. Then, 29% of patients had mild, 30% had moderate, and 41% had severe OSA. The severity of OSA was significantly correlated with the COVID-19 type of treatment and recovery duration (p value = 0.002 and 0.001, respectively. Severe OSA correlated with higher BMI values. Notably, the type of COVID-19 vaccine, number of doses, and whether the COVID-19 infection occurred before or after vaccination did not affect the severity of OSA.

Conclusion: The severity of OSA and COVID-19 infection were correlated. The management of OSA severity and the control over other comorbidities may lower the chance of severe COVID-19 infection among OSA patients.

Aim: The aim of the study is to evaluate the distribution and drug resistance of infectious pathogens in hospitalized patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD).

Methods: This is a retrospective study of AECOPD patients who underwent pathogen evaluation and drug susceptibility tests.

Results: A total of 199 hospitalized AECOPD patients were analyzed. Among them, 77.9% had monoinfection, and 22.1% had multiple infections. Two hundred and eighty-eight strains were isolated, with 61.1% gram-negative, 3.8% gram-positive, and 35.0% fungi, while 58 strains were colonized. Common bacteria included Haemophilus parainfluenzae, Acinetobacter baumannii, and Pseudomonas aeruginosa. Staphylococcus aureus and Enterococcus faecalis were the main gram-positive cocci, and Pseudohyphae were the main fungi. Fifty gram-negative strains showed drug resistance (19 colonized strains), with high resistance to ceftriaxone in A. baumannii, P. aeruginosa, Klebsiella pneumoniae, and Escherichia coli. Methicillin-resistant S. aureus was resistant to penicillin but sensitive to other antibiotics.

Conclusion: The study highlights the distribution of pathogens and the prevalence of drug-resistant strains among AECOPD patients.

Background: The use of positive expiratory pressure (PEP), which includes conical-PEP breathing, has been proposed for use during exercise among patients with chronic obstructive pulmonary disease (COPD) to reduce dynamic hyperinflation (DH) and improve exercise capacity. However, evidence on the effects of exercise training with conical-PEP for pulmonary rehabilitation (PR) remains limited. This study was conducted to evaluate the aforementioned effects on exercise capacity, DH, and quality of life among patients with moderate to very severe COPD.

Methods: Forty-two patients with moderate to very severe COPD were assigned to a home-based PR program. They were then randomly allocated to exercise training with conical-PEP (n = 21, age 64.5 ± 6.8 years) or without conical-PEP (control group, n = 21, age 67.2 ± 8.0 years) for 8-10 weeks. The outcomes of the 6-min walk distance (6MWD), the endurance spot marching test (ESMT) for endurance time, an inspiratory capacity (IC) test to assess DH, the transition dyspnea index (TDI), St. George's Respiratory Questionnaire (SGRQ), and the COPD Assessment Test (CAT) were recorded at baseline and at the program's end (post-PR).

Results: There were no significant differences in 6MWD (p = 0.116) or ESMT endurance time (p = 0.247) between the conical-PEP and control groups at post-PR. Compared to baseline, the post-PR measurements showed a significant reduction in end-exercise IC in the control group (Δ -0.08 L, 95% CI: -0.16 to -0.01 L, p = 0.033) but no significant reduction in the conical-PEP group (Δ -0.07 L, 95% CI: -0.19 to 0.05 L, p = 0.193). No significant differences were found between the groups at post-PR in terms of TDI (p = 0.277), SGRQ (p = 0.687), or CAT (p = 0.704) scores.

Conclusion: The addition of conical-PEP during exercise training for PR in COPD did not provide significant benefits over exercise training without conical-PEP. Further research is warranted.

Background: Accurate assessment of lung function among asthmatic children is crucial for effective disease management. The Global Lung Initiative (GLI) has developed widely used spirometric reference equations. However, locally derived equations may better reflect regional population characteristics and more accurately predict asthma control status. The impact of using local versus GLI equations, particularly the newly developed race-neutral equations, remains under investigation. This study examined how the choice of spirometric equation affects asthma assessment. Method: Spirometry was conducted on a sample of 438 asthmatic children (257 boys), and asthma control was assessed using the Global Initiative for Asthma Symptoms test (GINA-AST). Reference values, z-scores, and lower limits of normality (LLNs) were calculated for each child using both local and GLI reference equations. Concordance between equations was assessed using Cohen's kappa, and the sensitivity and specificity of each equation in detecting asthma control status were evaluated. Results: Significant differences were found in spirometry values across equations. The local equation displayed the highest sensitivity for detecting uncontrolled asthma and showed the greatest agreement with GINA-AST. Mean FEV₁ z-scores varied across equations, though intraclass correlation coefficients (ICCs) were high. Conclusions: This study highlights the substantial impact that the choice of spirometric equation has on asthma control assessment. Local equations may offer greater diagnostic sensitivity, potentially leading to more accurate disease classification and improved management outcomes.

Background: Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is an established procedure for diagnosing thoracic diseases and staging of lung cancers. However, some limitations of cytology specimens from EBUS-TBNA include small sample size, low tumour cellularity, necrosis and specimen contamination. Endobronchial ultrasound-guided transbronchial mediastinal cryobiopsy (EBUS-TBMC) is a promising alternative that provides a larger histology specimen which may improve diagnostic accuracy and molecular testing. This study is aimed at evaluating the benefits of EBUS-TBMC over EBUS-TBNA, focusing on improving next-generation sequencing (NGS) success rates, and assessing its efficacy and safety in a real-world setting. Methods: Data from 203 patients (99 underwent EBUS-TBNA and 104 underwent EBUS-TBMC) were retrospectively traced and analysed using descriptive statistics. Results: The overall diagnostic yield was significantly higher for EBUS-TBMC (90.38%) than that for EBUS-TBNA (67.68%; p < 0.001). For heterogeneous lesions, the diagnostic yield was 92.31% for EBUS-TBMC and 69.44% for EBUS-TBNA (p = 0.011). For non-small-cell lung cancer (NSCLC), EBUS-TBMC specimens demonstrated higher overall tumour cellularity (65% vs. 30%; p < 0.001) and better success in detecting driver alterations through NGS (85.36% vs. 61.90%; p = 0.035). The median procedure duration was shorter for EBUS-TBMC (22 vs. 32 min; p < 0.001), and the complication rates were comparable between the two techniques. These findings suggest that EBUS-TBMC offers additional diagnostic advantages over EBUS-TBNA for heterogeneous lesions and significantly facilitates the acquisition of cell-rich specimens for NGS testing. Conclusion: EBUS-TBMC increases the overall diagnostic yield of mediastinal diseases. EBUS-TBMC provides cell-rich histology specimens with high tumour content, facilitating NGS testing in the management of NSCLC.

Asthma diagnosis can be confirmed by observing significant bronchodilator response (BDR) through peak expiratory flow (PEF) at home or forced expiratory volume in 1 s (FEV₁) via spirometry in a clinical setting. We aimed to use the administration of salbutamol after a methacholine challenge test as a model of bronchodilation to study how accurately the change in PEF predicts improvement in lung function, as defined by an increase in FEV₁. We analyzed 869 adult patients who were administered salbutamol after a methacholine challenge. To compare relative changes in PEF and FEV₁ during bronchodilation, we used regression analysis and constructed a Bland and Altman plot. ROC analysis, sensitivity, specificity, positive and negative predictive values, and kappa coefficient assessed how precisely increases in PEF detected a 12% and 0.2-L improvement in FEV₁. The average relative increase in FEV₁ was significantly greater than that in PEF. The area under the curve in the ROC analysis was 0.844 for PEF change to detect a 12% and 0.2-L increase in FEV₁. The kappa values for changes in PEF and FEV₁ ranged from fair to moderate. BDR detected by the recommended 15% and 60 L/min cut-off for PEF identified less than half of true positives, while a 10% cut-off correctly identified close to 75% of them. PEF increase is not a reliable measure of BDR in comparison to FEV₁ increase, and a 10% improvement in PEF was the least inaccurate cut-off. Substituting the PEF meter with a handheld spirometer should be further investigated for asthma home monitoring.

Lung diseases, including pneumonia and COVID-19, are prevalent globally, necessitating early diagnosis for effective treatment. Medical imaging is widely regarded as an effective method for detecting lung diseases. Numerous researchers have dedicated their efforts to developing advanced detection techniques, significantly contributing to the prevention and management of these conditions. Despite advancements in imaging diagnostic methods, chest radiographs remain pivotal due to their cost-effectiveness and rapid results. This study proposes an automated system for detecting multiple lung diseases in x-ray and CT scans using a customized convolutional neural network (CNN) alongside pretrained models and an image enhancement approach. The dataset used comprises 6400 images sourced from Kaggle, categorized into three classes: pneumonia, COVID-19, and normal. To address dataset imbalance, data augmentation techniques were applied. The model includes preprocessing and classification stages, achieving high performance metrics: 96% precision, 95.33% recall, 95.66% F1-score, and 97.24% accuracy, highlighting its effectiveness compared to other deep learning models.