Search Results (303)

Background: Scedosporium apiospermum is a filamentous fungus increasingly recognized as an opportunistic pathogen in immunocompromised hosts, though rare infections in immunocompetent individuals with structural lung disease have been reported. Its diagnosis and management remain challenging due to non-specific clinical presentation and intrinsic resistance to multiple antifungal agents. Case Presentation: We report the case of a 66-year-old immunocompetent woman with idiopathic bilateral non-cystic fibrosis bronchiectasis, who presented with subacute cough and increased sputum production. Chest high-resolution CT revealed new subsolid and ground-glass infiltrates superimposed on stable bronchiectatic changes. Bronchoalveolar lavage (BAL) cultures isolated S. apiospermum as the sole pathogen. The patient was treated with oral voriconazole (200 mg BID) for 4 weeks, followed by a 4-week course of aerosolized amphotericin B. Clinical and radiological improvement was observed, and no relapse occurred during follow-up. Discussion: This case highlights the potential for S. apiospermum to cause clinically relevant pulmonary infection in structurally abnormal but immunocompetent lungs. Non-CF bronchiectasis may facilitate fungal colonization due to impaired mucociliary clearance and chronic mucus retention. Combined antifungal therapy involving systemic voriconazole and inhaled amphotericin B (though not yet standardized) was employed based on clinical rationale and the available literature, resulting in favorable outcomes. Conclusions:S. apiospermum pulmonary infection, although rare in immunocompetent hosts with bronchiectasis, should be considered in cases of new or persistent infiltrates. Early recognition and individualized antifungal strategies, including the potential role of inhaled agents, may improve clinical outcomes. This case reinforces the importance of multidisciplinary collaboration in the management of complex fungal infections in chronic airway disease. Full article

Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome with multiple clinical and inflammatory phenotypes. The coexistence of bronchiectasis, known as bronchiectasis–COPD overlap (BCO), identifies a subgroup with increased morbidity and mortality. Non-invasive breath analysis using electronic noses (e-noses) has shown promise in identifying disease-specific volatile organic compound (VOC) patterns (“breathprints”). Our aim was to evaluate the ability of an e-nose to differentiate between COPD and BCO patients, and to assess its utility in detecting inflammatory endotypes (neutrophilic vs. eosinophilic). In a monocentric, prospective, real-life study, 98 patients were enrolled over nine months. Forty-two patients had radiologically confirmed BCO, while fifty-six had COPD without bronchiectasis. Exhaled breath samples were analyzed using the Cyranose 320 e-nose. Principal component analysis (PCA) and discriminant analysis were used to identify group-specific breathprints and inflammatory profiles. PCA revealed significant breathprint differences between BCO and COPD (p = 0.021). Discriminant analysis yielded an overall accuracy of 69.6% (AUC 0.768, p = 0.037). The highest classification performance (76.8%) was achieved when distinguishing eosinophilic COPD from neutrophilic BCO. These findings suggest distinct inflammatory profiles that may be captured non-invasively. E-nose technology holds potential for the non-invasive endotyping of COPD, especially in identifying neutrophilic BCO as a unique inflammatory entity. Breathomics may support early, personalized treatment strategies. Full article

Respiratory diseases represent a persistent global health challenge, underscoring the need for intelligent, accurate, and personalized diagnostic and therapeutic systems. Existing methods frequently suffer from limitations in diagnostic precision, lack of individualized treatment, and constrained adaptability to complex clinical scenarios. To address these challenges, our study introduces a modular AI-powered framework that integrates an audio-based disease classification model with simulated molecular biomarker profiles to evaluate the feasibility of future multimodal diagnostic extensions, alongside a synthetic-data-driven prescription recommendation engine. The disease classification model analyzes respiratory sound recordings and accurately distinguishes among eight clinical classes: bronchiectasis, pneumonia, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), asthma, chronic obstructive pulmonary disease (COPD), bronchiolitis, and healthy respiratory state. The proposed model achieved a classification accuracy of 99.99% on a holdout test set, including 94.2% accuracy on pediatric samples. In parallel, the prescription module provides individualized treatment recommendations comprising drug, dosage, and frequency trained on a carefully constructed synthetic dataset designed to emulate real-world prescribing logic.The model achieved over 99% accuracy in medication prediction tasks, outperforming baseline models such as those discussed in research. Minimal misclassification in the confusion matrix and strong clinician agreement on 200 prescriptions (Cohen’s $\kappa$ = 0.91 [0.87–0.94] for drug selection, 0.78 [0.74–0.81] for dosage, 0.96 [0.93–0.98] for frequency) further affirm the system’s reliability. Adjusted clinician disagreement rates were 2.7% (drug), 6.4% (dosage), and 1.5% (frequency). SHAP analysis identified age and smoking as key predictors, enhancing model explainability. Dosage accuracy was 91.3%, and most disagreements occurred in renal-impaired and pediatric cases. However, our study is presented strictly as a proof-of-concept. The use of synthetic data and the absence of access to real patient records constitute key limitations. A trialed clinical deployment was conducted under a controlled environment with a positive rate of satisfaction from experts and users, but the proposed system must undergo extensive validation with de-identified electronic medical records (EMRs) and regulatory scrutiny before it can be considered for practical application. Nonetheless, the findings offer a promising foundation for the future development of clinically viable AI-assisted respiratory care tools. Full article

Objectives: Non-cystic fibrosis bronchiectasis (BE) is a chronic airway disease with increasing prevalence, reduced quality of life, and increased mortality. Inhaled corticosteroids (ICS) are used in BE despite limited evidence of effect on lung function parameters. ICS may increase the risk of Staphylococcus aureus (S. aureus) infections in patients with BE, but this is unexplored. We examined the association between ICS use prior to BE diagnosis at different doses and the risk of S. aureus isolation in patients with BE. Methods: We conducted a national register-based cohort study including Danish patients with a BE diagnosis code between 2001 and 2018 with a 1-year follow-up time from the date of diagnosis. ICS exposure was categorized based on accumulated prescriptions redeemed 365 days before BE diagnosis and divided into none, low, moderate, or high use based on clinically relevant doses. A cause-specific Cox proportional hazards regression model was used to estimate the risk of S. aureus isolation. A sensitivity analysis, an inverse probability of treatment weighted model (IPTW), was performed. Results: A total of 5093 patients were included in this study. S. aureus was isolated in 156 patients (3.1%). High-dose ICS was associated with an increased risk of S. aureus isolation, HR 3.81 (95% CI 2.51; 5.79). No association for low or moderate use was found, low-dose HR 1.22 (95% CI 0.77; 1.93), and moderate-dose HR 1.24 (95% CI 0.72; 2.16). IPTW analysis yielded similar results. Conclusions: High-dose ICS use in patients with BE was associated with an increased risk of S. aureus isolation. ICS should be used cautiously in patients with BE. Full article

Objectives: Although patients with bronchiectasis tend to have obstructive nonreversible lung functions, some have bronchodilator response (BDR), and a relatively large number are treated with bronchodilators. We assessed BDR in patients with cystic fibrosis (CF) and other bronchiectatic diseases and healthy controls (HCs) in a randomized controlled setup. Methods: Patients with cystic fibrosis (CF), primary ciliary dyskinesia (PCD) and non-CF non-PCD bronchiectasis (non-CF/PCD), as well as HCs, were recruited. Participants were randomly assigned to receive salbutamol (four puffs) and then a placebo or a placebo and then salbutamol. BDR was calculated using the American Thoracic Society (ATS)/European Respiratory Society (ERS) standard, defined as the change related to the individual’s predicted value (new method) or to the initial value (old method). Results: Sixty-nine patients (CF = 30, PCD = 20, non-CF/PCD = 19) and 20 HCs were included. Patients with CF and PCD (but not non-CF/PCD) had a statistically greater mean response to salbutamol compared with the placebo, (CF–salbutamol first: 2.82 vs. 0.85%, p = 0.01; placebo first: 2.39 vs. −0.27%, p = 0.02; PCD–salbutamol first: 5.32 vs. 1.88%, p = 0.01; placebo first: 2.24 vs. 0.77%, p = 0.05). Few patients had significant BDR (new method, >10%)—CF (0), PCD (2), non-CF/PCD (0) and HCs (2)): using the old method, an additional PCD patient and three non-CF/PCD had significant BDR (>12%). Conclusions: Significant BDR seems to be rare in patients with bronchiectasis. In CF and PCD, the response was greater than the placebo; the clinical significance of this difference and its therapeutic implications, as well as the best method to determine BDR, have yet to be determined. Full article

Background: Exophiala dermatitidis is a dematiaceous, thermotolerant, yeast-like fungus increasingly recognized as an opportunistic pathogen in chronic airway diseases. While commonly associated with cystic fibrosis, its clinical significance in non-cystic fibrosis bronchiectasis (NCFB) remains unclear. Case Presentation: We report the case of a 66-year-old immunocompetent woman with a history of breast cancer in remission and NCFB, who presented with chronic cough and dyspnea. Chest CT revealed bilateral bronchiectasis with new pseudonodular opacities. Bronchoalveolar lavage cultures identified E. dermatitidis, along with Pseudomonas aeruginosa and methicillin-sensitive Staphylococcus aureus. Given clinical stability and the absence of systemic signs, initial therapy included oral voriconazole, levofloxacin, doxycycline, and inhaled amikacin. Despite persistent fungal isolation on repeat bronchoscopy, the patient remained asymptomatic with stable radiologic and functional findings. Antifungal therapy was discontinued, and the patient continued under close monitoring. The patient exhibited clinical and radiological stability despite repeated fungal isolation, reinforcing the hypothesis of persistent colonization rather than active infection. Discussion: This case underscores the diagnostic challenges in distinguishing fungal colonization from true infection in structurally abnormal lungs. In NCFB, disrupted mucociliary clearance and microbial dysbiosis may facilitate fungal persistence, even in the absence of overt immunosuppression. The detection of E. dermatitidis should prompt a comprehensive evaluation, integrating clinical, radiologic, and microbiologic data to guide management. Voriconazole is currently the antifungal agent of choice, though therapeutic thresholds and duration remain undefined. Conclusions: This report highlights the potential role of E. dermatitidis as an under-recognized respiratory pathogen in NCFB and the importance of a multidisciplinary, individualized approach to diagnosis and treatment. This case underscores the need for further research on fungal colonization in NCFB and the development of evidence-based treatment guidelines. Further studies are needed to clarify the pathogenic significance, optimal management, and long-term outcomes of E. dermatitidis in non-CF chronic lung diseases. Full article

The accurate and early detection of respiratory diseases is vital for effective diagnosis and treatment. This study presents a new approach for classifying lung sounds using a double denoising method combined with a 1D Convolutional Neural Network (CNN). The preprocessing uses Fast Fourier Transform to clean up sounds and High-Pass Filtering to improve the quality of breathing sounds by eliminating noise and low-frequency interruptions. The Short-Time Fourier Transform (STFT) extracts features that capture localised frequency variations, crucial for distinguishing normal and abnormal respiratory sounds. These features are input into the 1D CNN, which classifies diseases such as bronchiectasis, pneumonia, asthma, COPD, healthy, and URTI. The dual denoising method enhances signal clarity and classification performance. The model achieved 96% validation accuracy, highlighting its reliability in detecting respiratory conditions. The results emphasise the effectiveness of combining signal augmentation with deep learning for automated respiratory sound analysis, with future research focusing on dataset expansion and model refinement for clinical use. Full article

Background/Objectives: In 2024, Lithuania developed a national lung cancer screening program (the Program), targeting individuals aged 50 to 70 years, regardless of their smoking history, with screenings conducted once every three years. The Program aims not only to actively detect lung nodules (lung cancer) but also to identify clinically significant concomitant findings. The pilot study aimed to evaluate the screening process’s feasibility and organizational efficiency of the screening process, as well as its potential clinical effectiveness. Methods: Three family medicine centers were selected for participation. The Coordinating Center contacted individuals aged 50 to 70 sequentially and invited them to participate, regardless of smoking status. In total, 1014 individuals were prospectively enrolled and underwent low-dose chest computed tomography (LDCT) screening between 26 September 2024 and 14 February 2025. Results: Of the individuals invited, 76.1% agreed to participate. Lung-RADS v2022 category 4 nodules were identified in 1.4% of participants (n = 14), including six smokers and eight non-smokers. Additionally, one participant with a Lung-RADS category 2 nodule was diagnosed with squamous cell carcinoma originating from peripheral lung changes. Newly identified significant incidental findings were detected in 25.9% of participants: 5.1% had pulmonary or mediastinal findings (most commonly emphysema, interstitial lung changes, and bronchiectasis), 18.7% had cardiovascular findings (usually coronary artery calcification, aortic valve calcification, and aorta dilation), and 2.1% had other clinically relevant conditions (e.g., thyroid nodules, diaphragmatic changes). Following assessment by family physicians, 17.6% of all participants were referred to medical specialists, including pulmonologists, cardiologists, and others. Conclusions: This pilot study demonstrated that the Lithuanian lung cancer screening model is feasible, well-organized, and clinically valuable. The findings support the Program’s readiness for broader implementation at the national level. Full article

Bronchiectasis (BE) and bronchomalacia (BM) are chronic respiratory diseases in dogs, yet their combined occurrence (BEBM) is not well studied. This retrospective study analyzed 65 dogs diagnosed via endoscopy with BE, BM, or BEBM (E-BE, E-BM, E-BEBM) to identify clinical and pathological differences and assess how imaging results (radiography and computed tomography (CT)) align with endoscopic findings. Clinical symptoms like coughing, dyspnea, and exercise intolerance were similar across all groups, except lung crackles, which were more common in E-BEBM. Inflammation seen during bronchoscopy and bronchoalveolar lavage fluid results, including neutrophil counts, showed no significant differences between groups. Bacterial infections were present in 15% of dogs with no difference among groups. Diagnostic agreement between radiography and endoscopy was low: 18.1% for E-BE, 10.5% for E-BM, and 38.4% for E-BEBM. CT results matched endoscopic findings in all E-BE cases but only in half of E-BM and 40% of E-BEBM cases. The bronchial-to-arterial ratio, a benchmark for BE diagnosis, did not align with CT findings. Overall, the study found limited clinical or pathological differences between BE, BM, and BEBM and limited concordance between imaging and endoscopic findings, emphasizing the need for further research to clarify potential implications for treatment strategies. Full article

Background and Objective: Primary ciliary dyskinesia (PCD) is a rare genetic disorder that affects the mucociliary system, leading to progressive lung damage. This deterioration can result in bronchiectasis, atelectasis, and respiratory failure, necessitating lung transplantation in severe cases. This study aims to assess ciliary motility and ultrastructure in the bronchial epithelium of transplanted lungs in patients with PCD to determine whether mucociliary function is preserved post-transplantation. The findings seek to enhance scientific understanding and provide prognostic insights for these patients. Materials and Methods: A prospective observational study was conducted on two patients with PCD and advanced lung disease who underwent bilateral lung transplantation. Nasal and bronchial cilia samples were analyzed using high-speed videomicroscopy and transmission electron microscopy. Follow-up assessments included ciliary function analysis, lung rejection monitoring, and quality-of-life evaluations, with follow-up extending up to 30 months post-transplant. Results: Post-transplant evaluations demonstrated normal ciliary motility and ultrastructure in the transplanted lungs throughout the study period (up to 30 months), indicating the long-term preservation of mucociliary function. Conclusions: Transplanted lungs in patients with PCD maintain normal bronchial ciliary motility and structure in the long term, suggesting a favorable prognosis for both the graft and the recipient. These findings support the feasibility and long-term effectiveness of lung transplantation in patients with PCD. Full article

Background: Differentiating nontuberculous mycobacterial pulmonary disease (NTM-PD) from pulmonary tuberculosis (PTB) remains challenging due to overlapping clinical features, particularly in resource-limited settings where diagnostic errors are frequent. This retrospective case–control study (January 2023–June 2024) aimed to identify key clinical predictors and develop a diagnostic model to distinguish NTM-PD from PTB. Methods: Patients initially presumed to have PTB (meeting clinical–radiological criteria but lacking bacteriological confirmation at admission) at a tertiary tuberculosis hospital were enrolled. Final diagnoses of NTM-PD (n = 105) and PTB (n = 105) were confirmed by mycobacterial culture identification. Clinical, laboratory, and radiological data were compared using univariate analysis. Variables showing significant differences (p < 0.05) were entered into multivariable logistic regression. Diagnostic performance was evaluated via receiver operating characteristic (ROC) curve analysis. Results: Female sex (odds ratio [OR] = 2.51, 95% confidence interval [CI] 1.12–5.60), hemoptysis (OR = 2.20, 1.05–4.62), bronchiectasis (OR = 5.92, 2.56–13.71), and emphysema/pulmonary bullae (OR = 2.69, 1.16–6.24) emerged as independent predictors of NTM-PD, while systemic symptoms favored PTB (OR = 0.45, 0.20–0.99). The model demonstrated 91.4% specificity and 68.6% sensitivity with an area under the curve [AUC] of 0.871. Conclusions: This high-specificity model helps prioritize NTM-PD confirmation in females with hemoptysis and structural lung changes (computed tomography evidence of bronchiectasis and/or emphysema) while maintaining PTB suspicion when systemic symptoms (fever, night sweats, weight loss) dominate. The approach may reduce misguided antitubercular therapy in resource-limited settings awaiting culture results. Full article

Background: Despite the multiple waves of the COVID-19 pandemic, follow-up strategies for recovered patients remain inconclusive. This study aimed to evaluate chest computed tomography (CT) and pulmonary function test (PFT) abnormalities in convalescents six months after COVID-19 and to compare these findings with those from a representative population cohort. The goal was to support more individualized pulmonary management of post-COVID-19 sequelae. Methods: This study population consisted of 2 groups: I—232 post-COVID-19 patients and II—543 patients from a population cohort. Chest CT was performed during the acute phase of COVID-19 and six months after. The PFTs were conducted six months after COVID-19. Results: There were no significant differences in FEV1, FVC, TLC, and DLCO in the two study groups. A singular GGO in 24 patients (20%), a crazy paving pattern in 1 patient (0.8%), thickening of interlobular septa in 4 patients (3.5%), consolidations in 4 patients (3.5%), traction bronchiectasis in 6 patients (5%), fibrosis in 6 patients (5%), and singular nodular densities in 68 patients (58%) were observed in chest CT 6 months after COVID-19. Most radiological abnormalities were clinically insignificant and did not require further diagnostic evaluation. No significant differences in chest CT and PFT six months after infection were observed between patients differing in the severity of inflammation during the acute disease or SARS-CoV-2 variant. Conclusions: The majority of chest CT abnormalities resolved within six months of recovery, regardless of SARS-CoV-2 variant or initial disease severity. Pulmonary function tests should be prioritized in post-COVID-19 follow-up, as PFT results in convalescents were comparable to those observed in the general population. Full article

Background and Objective: This study’s objective was to determine the impact of the percentage of lung tissue within the normal density range (PLND) on exacerbations and hospitalizations compared with the modified Bhalla and Reiff scores. We also investigated the effects of these measures on pulmonary function tests (PFTs). Materials and Methods: This retrospective analysis involved adult cystic fibrosis (CF) patients who had thoracic computed tomography (CT) while in a stable clinical condition. A dedicated radiologist analyzed CT images and conducted modified Bhalla, Reiff, and PLND assessments. We analyzed the exacerbations and hospitalizations in the year after the CT scan. We also examined PFTs at the time of the CT scan and one year later. Results: This study’s population consisted of 63 subjects (33 men), with a median age of 23.2 years. The median modified Bhalla score was 9.0 (IQR: 7.0–12.0), the median Reiff score was 11.0 (IQR: 8.0–15.0), and the median PLND was 79.4% (IQR: 74.5–82.0). The Bhalla score had the strongest relationship with both the number of exacerbations (p < 0.001, r: −0.559) and hospitalizations the following year (p < 0.001, r: −0.636), followed by the PLND score and the Reiff score. Youden’s index shows that the optimum cut-off values for hospitalization at ≤2 and >2 are 6.5 for the modified Bhalla score, 13.5 for the Reiff score, and 76.5% for the PLND. Conclusions: The measurement of PLND may serve as a predictor for exacerbation and hospitalization rates, aligning with the modified Bhalla and Reiff scores, and shows potential for application in follow-up assessments. Full article