ERJ Open Research最新文献

The "triple combination" test developed by Porcel and colleagues avoids the need for simultaneous serum sampling and has similar diagnostic performance characteristics to Light's criteria https://bit.ly/4o5jrp7.

Background: Achieving good asthma control is a goal of asthma management. In children, asthma control and quality-of-life assessments include determining the presence of wheeze. However, wheeze is unreliably reported with high disagreement (>50%) between parental and physician detection of wheeze. Objectively defining wheeze using WheezeScan™ (a user-friendly, artificial intelligence-based device) could improve assessment of asthma control and hence management.

Objective: Our primary aim is to determine whether adding WheezeScan™ to routine clinical care improves parental asthma control assessment (ACA) in children (aged 4-11 years). Our secondary aims are to examine the impact of WheezeScan™ upon patient-reported outcomes (PROs), the parent asthma management self-efficacy scale (PAMS), healthcare costs and ease of WheezeScan™ use. The primary hypothesis is that using WheezeScan™ alters the ACA group.

Methods: Our multicentre prospective cohort study involves 125 children with specialist-confirmed asthma. Over 5 weeks, parents/caregivers use the WheezeScan™ twice-daily at home and whenever wheezing is suspected. After the first week of using the WheezeScan™, asthma medications may be adjusted based upon the child's asthma control score and WheezeScan™ data. Study outcomes are collected at baseline, week 1 and week 5. Our primary end-point is the proportion of children whose assessment of asthma control changed between week 1 and baseline, based upon parental assessments using WheezeScan™ data. Secondary outcomes are PROs (asthma-related quality of life), PAMS, healthcare costs and WheezeScan™ ease of use.

Conclusions: This protocol describes our study to determine whether using digital technology to accurately identify wheeze in children with asthma improves their asthma assessment and asthma-related PROs, including PAMS and healthcare costs.

Background: There is indirect evidence that inhaled traffic-related particulate matter (PM) penetrates into the human circulation. Since nanoparticles readily adhere to red blood cells (RBCs) in vitro, we sought to determine whether a mechanism of systemic transport of translocated traffic-related particles is via adherence to RBCs in vivo.

Methods: Adult volunteers were exposed to traffic-related emissions from a main road for 1 h. Volunteers were also exposed to emissions wearing a FFP2 mask. Exposure to black carbon PM was assessed by portable aethalometer. The mean area (μm²) of adherent black PM per RBC was determined from unstained blood smears from 3000 cells by light microscopy. Particle composition was determined by scanning transmission electron microscopy and energy-dispersive X-ray analyses. The capacity of diesel exhaust particles to adhere to human RBCs in vitro was determined, and RBCs were examined after intratracheal instillation of diesel exhaust particles to a mouse model.

Results: Exposure to traffic-related emissions increased personal black carbon PM (n=12, p=0.001 versus baseline). Exposure increased the area of particles adherent to RBCs (p<0.001 versus baseline), and this was reduced by wearing a FFP2 mask (p=0.002 versus no mask). Traffic exposure increased the abundance of metal-bearing nanoparticles associated with RBCs. Diesel exhaust particles adhered to RBCs in vitro in a dose-dependent manner. Particles were found adherent to circulating RBCs after intratracheal instillation of diesel exhaust particles.

Conclusion: Adhesion of traffic-related PM to RBCs is a systemic transport mechanism. Quantification of particles on RBCs is a putative practical biomarker of inhaled dose.

This article presents key insights from the 2025 #ERSCongress as observed by Early Career Members of the Allied Respiratory Professionals Assembly @ERS_Assembly9 https://bit.ly/4amfzwg.

Background: Multimorbidity (≥2 chronic diseases) is common among older adults and is linked to increased disability and mortality. Sleep disordered breathing (SDB) is underdiagnosed and has been associated with several chronic diseases. However, little is known about the specific patterns of comorbidity in the elderly. This study investigated the association between SDB and multimorbidity patterns in individuals aged ≥65 years and assessed the impact of SDB on all-cause mortality.

Methods: This registry-based case-control study utilised the Danish National Patient Registries from 2002 to 2019. Individuals aged ≥65 years diagnosed with SDB were identified and matched 1:4 with controls based on age, sex, cohabitation status and region of residence. Comorbidities were categorised using eight World Health Organization (WHO) disease chapters, and 22 specific chronic diseases were assessed within 7 years prior to SDB diagnosis. Conditional logistic regression estimated odds ratios (ORs) for comorbidities; Cox hazard regression models evaluated mortality risk.

Results: A total of 21 555 patients with SDB were matched to 86 212 controls. Patients with SDB had significantly higher odds of multimorbidity (OR 2.99, p<0.01), with increased prevalence across all eight WHO disease groups. The highest ORs were found in the cardiovascular (OR 2.52, p<0.01) and metabolic disease categories (OR 2.52, p<0.01). SDB was associated with elevated all-cause mortality (hazard ratio 1.09, p<0.01).

Conclusion: SDB in older adults is associated with multimorbidity and increased mortality, highlighting the need for increased recognition and coordinated treatment of SDB in elderly patients with multiple chronic conditions.

Background: Light's criteria remain the standard for distinguishing exudative from transudative pleural effusions, but require serum sampling and lack specificity. We assessed whether a pleural fluid-only approach could match the diagnostic accuracy.

Methods: We analysed 7280 diagnostic thoracenteses from a single centre, divided into derivation (n=5000) and validation (n=2280) cohorts. We compared Light's criteria with a triple (protein >3 g·dL^-1, lactate dehydrogenase (LDH) >250 IU·L^-1 or cholesterol >55 mg·dL^-1) and a double (LDH >250 IU·L^-1 or cholesterol >55 mg·dL^-1) combination using sensitivity, specificity, likelihood ratios and area under the curve (AUC). AUCs were assessed using the DeLong method with multiple imputations from a mixed model. McNemar's test examined discordant classifications.

Results: The triple combination showed no significant AUC difference versus Light's criteria in either cohort and had equivalent sensitivity (99% versus 98% in derivation; both 98% in validation). In the derivation cohort, McNemar's test showed a small but statistically significant excess of false negative exudates with the triple combination (p<0.001), whereas no significant difference was found in the validation cohort (p=0.241). The triple combination correctly reclassified 19-20% of transudates misclassified by Light's criteria, while the reverse occurred in 11-14%. The double combination yielded the highest AUCs but missed more exudates, limiting its clinical safety.

Conclusion: A pleural fluid-only triple combination matches Light's criteria in diagnostic accuracy, avoids serum sampling and improves specificity with minimal sensitivity loss in one cohort. This approach may be a practical alternative for the initial classification of pleural effusion when blood sampling is unavailable or undesirable.

Respiratory muscle training can be used in conjunction with CPAP or in situations precluding use of CPAP therapy. It should be used as a complimentary measure rather than an alternative to CPAP. https://bit.ly/3JqDDU7.

Rationale: COPD is characterised by chronic airflow limitation and persistent inflammation. Inhaled corticosteroids (ICS) are often used to reduce airway inflammation in patients. However, the response to ICS treatment varies among patients, and blood eosinophils may not fully reflect treatment effectiveness. In this study, we aim to identify gene modules associated with ICS responsiveness and assess the underlying biological pathways.

Methods: We included 55 patients from the GLUCOLD study with mild-moderate COPD treated with ICS for 6 months with available gene expression data from biopsies. Treatment response was defined as changes in post-bronchodilator forced expiratory volume in 1 s (FEV₁) % predicted, post-bronchodilator FEV₁/forced vital capacity and residual volume/total lung capacity. To identify gene modules significantly correlated with ICS treatment responsiveness, we applied Weighted Gene Co-Expression Network Analysis (WGCNA). To explore the biological relevance of these modules, functional enrichment analysis was conducted using the STRING database, and key genes were identified through Gene Network Inference using the Ensemble of Trees (GENIE3) approach.

Results: We identified four gene modules associated to ICS-induced improvement in FEV₁ % predicted. Pathway enrichment analysis revealed key biological pathways including cilium function, positive regulation of various metabolic processes and inflammation. These pathways were also reflected by key genes including LRRC6, IFT46, AKT2 and PIK3C3.

Conclusion: This study identified gene modules and pathways associated with ICS responsiveness in COPD, providing a potential mechanistic explanation for the variability in ICS treatment responsiveness in COPD.

Background: Exacerbation of COPD (ECOPD) has been linked to increased cardiovascular disease (CVD) risk within the first year, yet longer term risk is unclear. We aimed to investigate the short-term and long-term CVD risks after severe ECOPD.

Methods: Patients with self-reported or spirometry-detected COPD at baseline and patients with newly documented COPD during follow-up were included from the China Kadoorie Biobank. Multiple data sources were used to collect information on ECOPD hospitalisation and CVD incidence during follow-up. Time-dependent Cox regression models were used to estimate the hazard ratios and 95% confidence intervals for each risk period following ECOPD compared to the baseline period.

Results: Of the 46 514 patients included, 48.2% had screen-detected COPD, 26.2% had self-reported COPD and 25.6% had newly documented COPD. During a median 11-year follow-up, 1185 acute myocardial infarction, 5778 other ischaemic heart disease, 1078 heart failure, 2390 pulmonary heart disease, 4989 ischaemic stroke and 1648 intracerebral haemorrhage cases occurred. Post-ECOPD risks of all outcomes were prominently elevated, with first-week hazard ratios (95% CI) of 8.60 (5.40-13.70), 6.68 (5.16-8.65), 10.98 (6.74-17.89), 24.76 (19.40-31.60), 3.11 (2.16-4.48) and 2.40 (1.27-4.54), respectively. The risks diminished thereafter but could persist for 6 years or longer. All three categories of patients with COPD faced increased risks of most outcomes, with patients with COPD at baseline bearing higher post-ECOPD risks of other ischaemic heart disease and pulmonary heart disease.

Conclusion: CVD risks increased considerably after ECOPD, with risks of cardiac diseases and ischaemic stroke increased for 6 years or longer. Patients with screen-detected COPD had a similar burden of ECOPD and subsequent CVD to patients with doctor-diagnosed COPD.

Pathophysiology of LAM could be partly explained by abnormal overexpression of proteases such as cathepsin K (CatK). In this pilot study, we found an increase in pro-CatK levels in LAM patients compared to healthy female volunteers. https://bit.ly/46U3vAG.