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Background: Influenza is considered a self-limiting disease. However, in patients with chronic obstructive pulmonary disease (COPD), it may result in serious outcomes during the flu season. Objectives: The aims of this retrospective study were to explore the characteristics of hospitalized patients with COPD complicated by influenza and determine the factors affecting the prognosis of these patients. Method: Demographic and clinical data were collected for 278 patients totally from the West China Hospital between January 1, 2016 and February 28, 2018. Results: Among the patients with influenza, the positive fungal culture rate, and the rates of antifungal drug and systemic corticosteroids use were higher for those with COPD than for those without COPD. Respiratory failure was more common in patients with influenza and COPD than in patients with influenza only, while the proportion of severe cases was higher among the former than among the latter. Among the patients with COPD, the positive fungal culture rate, particularly for Aspergillus, and the rate of systemic corticosteroids use were higher for those with influenza than for those without influenza. Multivariate analysis revealed that a COPD history of >20 years and smoking for >20 pack-years were independent factors for susceptibility of COPD patients to influenza. Conclusions:Aspergillus infection seems to be more common in patients with influenza and COPD. In addition, COPD complicated by influenza during the seasonal outbreak can easily progress to a severe disease state. Heavy smokers and patients with a prolonged COPD history are more likely to be infected by influenza. [ABSTRACT FROM AUTHOR]

Background: Chronic obstructive pulmonary disease (COPD) has become a leading cause of morbidity and mortality in China, with tobacco smoke, air pollution, and occupational biohazards being the major risk factors. Objectives: The REACH trial is a multicenter, prospective, randomized controlled trial undertaken in China to assess the safety and effectiveness of the Spiration® Valve System (SVS) compared to standard medical care in COPD patients with severe emphysema. Methods: Patients with severe airflow obstruction, hyperinflation, and severe dyspnea with interlobar fissure integrity were evaluated for enrollment. A total of 107 subjects were randomized in a 2: 1 allocation ratio to either the treatment group (SVS valves and medical management) or the control group (medical management alone). Results: The 3-month primary endpoint showed statistically significant improvement in forced expiratory volume in 1 s in the treatment group compared to the control group (0.104 ± 0.18 vs. 0.003 ± 0.15 L, p = 0.001), with the difference being durable through 6 months. Statistically significant target lobe volume reduction was achieved at 3 months (mean change 684.4 ± 686.7 mL) and through 6 months (757.0 ± 665.3 mL). Exercise function and quality of life measures improved in the treatment group, but showed a deterioration in the control group. The serious adverse event (SAE) rate was 33% in the treatment group and 24.2% in the control group. The predominance of SAEs were acute exacerbations of COPD in both groups. There was 1 death in the control group and no deaths in the treatment group. Conclusion: The SVS represents a novel approach for the treatment of severe emphysema with a clinically acceptable risk-benefit profile. [ABSTRACT FROM AUTHOR]

Background: Given the rarity of tracheobronchopathia osteochondroplastica (TO), many young doctors in primary hospitals are unable to identify TO based on bronchoscopy findings., Objectives: To build an artificial intelligence (AI) model for differentiating TO from other multinodular airway diseases by using bronchoscopic images., Design: We designed the study by comparing the imaging data of patients undergoing bronchoscopy from January 2010 to October 2022 by using EfficientNet. Bronchoscopic images of 21 patients with TO at Anhui Chest Hospital from October 2019 to October 2022 were collected for external validation., Methods: Bronchoscopic images of patients with multinodular airway lesions (including TO, amyloidosis, tumors, and inflammation) and without airway lesions in the First Affiliated Hospital of Guangzhou Medical University were collected. The images were randomized (4:1) into training and validation groups based on different diseases and utilized for deep learning by convolutional neural networks (CNNs)., Results: We enrolled 201 patients with multinodular airway disease (38, 15, 75, and 73 patients with TO, amyloidosis, tumors, and inflammation, respectively) and 213 without any airway lesions. To find multinodular lesion images for deep learning, we utilized 2183 bronchoscopic images of multinodular lesions (including TO, amyloidosis, tumor, and inflammation) and compared them with images without any airway lesions (1733). The accuracy of multinodular lesion identification was 98.9%. Further, the accuracy of TO detection based on the bronchoscopic images of multinodular lesions was 89.2%. Regarding external validation (using images from 21 patients with TO), all patients could be diagnosed with TO; the accuracy was 89.8%., Conclusion: We built an AI model that could differentiate TO from other multinodular airway diseases (mainly amyloidosis, tumors, and inflammation) by using bronchoscopic images. The model could help young physicians identify this rare airway disease.

This study aimed to investigate whether changes in progastrin-releasing peptide (ProGRP) levels correlate with treatment response and can be used to optimize clinical management of patients with small-cell lung cancer. Patients with small-cell lung cancer (any stage) receiving chemotherapy were eligible. ProGRP was measured in serum/plasma at baseline and after each chemotherapy cycle using the Elecsys ® ProGRP assay (Roche Diagnostics). Treatment response was assessed by computed tomography scan. The primary objective was to examine whether changes in ProGRP levels correlated with computed tomography scan results after two cycles of chemotherapy. The prognostic value of ProGRP among patients receiving first-line chemotherapy was also assessed. Overall, 261 patients from six centers were eligible. Among patients with elevated baseline ProGRP (>100 pg/mL), a ProGRP decline after Cycle 2 was associated with nonprogression (area under the curve: 84%; 95% confidence interval: 72.8-95.1; n = 141). ProGRP changes from baseline to end of Cycle 1 were predictive of response, as determined by computed tomography scan 3 weeks later (area under the curve: 87%; 95% confidence interval: 74.1-99.2; n = 137). This was enhanced by repeat measurements, with a 92% area under the curve (95% confidence interval: 85.3-97.8) among patients with ProGRP data after both Cycles 1 and 2 (n = 123); if a patient experienced a ≥25% decline in ProGRP after Cycle 1, and ProGRP remained stable or decreased after Cycle 2, the probability of finding progression on the interim computed tomography scan at the end of Cycle 2 was almost zero (sensitivity: 100%, specificity: 71%). Both ProGRP levels at baseline and at the end of first-line chemotherapy were prognostic; the latter provided a moderately improved hazard ratio of 2.43 (95% confidence interval: 1.33-4.46; n = 110) versus 1.87 (95% confidence interval: 1.04-3.37; n = 216). In summary, for patients with small-cell lung cancer and elevated baseline ProGRP levels, ProGRP may be a simple, reliable, and repeatable tool for monitoring response to chemotherapy and provide valuable prognostic information.