Background: Chronic respiratory diseases constitute a considerable part in the practice of pulmonologists and primary care physicians; spirometry is integral for the diagnosis and monitoring of these diseases, yet remains underutilized. The Air Next spirometer (NuvoAir, Sweden) is a novel ultra-portable device that performs spirometric measurements connected to a smartphone or tablet via Bluetooth®. Methods: The objective of this study was to assess the accuracy and validity of these measurements by comparing them with the ones obtained with a conventional desktop spirometer. Two hundred subjects were enrolled in the study with various spirometric patterns (50 patients with asthma, 50 with chronic obstructive pulmonary disease and 50 with interstitial lung disease) as well as 50 healthy individuals. Results: For the key spirometric parameters in the interpretation of spirometry, i.e. FEV₁, FVC, FEV₁/FVC and FEF_25–75%, Pearson correlation and Interclass Correlation Coefficient were greater than 0.94, exhibiting perfect concordance between the two spirometers. Similar results were observed in an exploratory analysis of the subgroups of patients. Using Bland-Altman plots we have shown good reproducibility in the measurements between the two devices, with small mean differences for the evaluated spirometric parameters and the majority of measurements being well within the limits of agreement. Conclusions: Our results support the use of Air Next as a reliable spirometer for the screening and diagnosis of various spirometric patterns in clinical practice.

Asthma is a prevalent chronic pulmonary condition with significant morbidity and mortality. Tobacco smoking is implicated in asthma pathophysiology, diagnosis, prognosis and treatment. Smokers display increased prevalence and incidence of asthma, but a causal association cannot be claimed using existing evidence. Second-hand smoking and passive exposure to tobacco in utero and early life have also been linked with asthma development. Currently, approximately one-fourth of asthma patients are smokers. Regular smokers with asthma might display accelerated lung function decline and non-reversible airflow limitation, making their distinction from chronic obstructive pulmonary disease patients challenging. Asthma patients who smoke typically have uncontrolled disease, as shown by increased symptoms, more exacerbations and impaired quality of life. On the other hand, smoking cessation improves lung function and asthma severity. Thus, asthma patients and their caregivers should be actively questioned about their smoking status at each medical encounter, and smoking cessation ought to be strongly encouraged both for patients with asthma and their close contacts. Smokers with asthma should be provided with comprehensive smoking cessation interventions on top of other anti-asthma medications.

Interstitial lung diseases (ILDs) comprise a rather heterogeneous group of diseases varying in pathophysiology, presentation, epidemiology, diagnosis, treatment and prognosis. Even though they have been recognized for several years, there are still areas of research debate. In the majority of ILDs, imaging modalities and especially high-resolution Computed Tomography (CT) scans have been the cornerstone in patient diagnostic approach and follow-up. The intricate nature of ILDs and the accompanying data have led to an increasing adoption of artificial intelligence (AI) techniques, primarily on imaging data but also in genetic data, spirometry and lung diffusion, among others. In this literature review, we describe the most prominent applications of AI in ILDs presented approximately within the last five years. We roughly stratify these studies in three categories, namely: (i) screening, (ii) diagnosis and classification, (iii) prognosis.

Chronic Obstructive Pulmonary Disease (COPD) is a chronic inflammatory disease with multisystemic manifestations. Studies either held on stable disease patients or during exacerbations have demonstrated that COPD is strongly related to venous thromboembolism and cardiovascular events. The aim of the present review of the literature was to provide an in-depth overview regarding the alterations of coagulation factors and prothrombotic changes generated in patients with stable COPD and during COPD exacerbations.

Background/Objectives: Small airway disease/dysfunction (SAD) is crucial in obstructive airway diseases but is less investigated in interstitial lung disease (ILD). There are only a few physiological studies investigating SAD in the context of pulmonary fibrosis. Oscillometry is a simple technique that assesses SAD with minimal patient effort. In this study, we investigated the role of oscillometry in patients with mild pulmonary fibrosis without evident obstructive disorder, focusing on small airways. Methods: Oscillometry and pulmonary function test (PFT) data of consecutive patients newly diagnosed with pulmonary fibrosis of unknown etiology in a university hospital ILD clinic were collected and analyzed. Results: Data from 34 patients with mild pulmonary fibrosis were collected in 6 months. Disease severity, as evaluated by FVC, presented strong correlations with the oscillometry parameters: resistance (R5: r = −0.588, p < 0.001), reactance (X5: r = 0.671, p < 0.001), resonant frequency (Fres: r = −0.562, p = 0.001), and the area of reactance (AX: r = −0.515, p = 0.002). The oscillometry parameter R5-19-expressing was abnormal in 27% of patients, correlated with FEF25-75% (r = −0.370, p = 0.021) and was a predictor of a FEF25-75% < 60% pred. with AUC 0.738 (95%Cl 0.519–0.956). R5-19 correlated with FVC (r = −0.481, p = 0.004) and was the only SAD parameter that correlated with the composite physiologic index (CPI, r = 0.338, p = 0.04), while FEF 25-75% and RV/TLC% did not. Conclusions: Oscillometry is an easy to perform technique that may reveal early mechanical alterations caused by pulmonary fibrosis. Peripheral resistance, as expressed by R5-19, which identifies small airway dysfunction as a marker of peripheral lung pathology, may be complementary to pulmonary function testing and may also have prognostic implications for ILD patients.

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease of the airways and lung parenchyma with multiple systemic manifestations. Exacerbations of COPD are important events during the course of the disease, as they are associated with increased mortality, severe impairment of health-related quality of life, accelerated decline in lung function, significant reduction in physical activity, and substantial economic burden. Telemedicine is the use of communication technologies to transmit medical data over short or long distances and to deliver healthcare services. The need to limit in-person appointments during the COVID-19 pandemic has caused a rapid increase in telemedicine services. In the present review of the literature covering published randomized controlled trials reporting results regarding the use of digital tools in acute exacerbations of COPD, we attempt to clarify the effectiveness of telemedicine for identifying, preventing, and reducing COPD exacerbations and improving other clinically relevant outcomes, while describing in detail the specific telemedicine interventions used.