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To summarize the main updated evidence about the health effects of air pollution, with a special focus on Southern Europe. Literature was obtained through PubMed Central and the official websites of European Agencies and Scientific Societies. Recent shreds of evidence about the health effects of air pollution coming from international reports and original research were collected and described in this review. Air pollution is an avoidable risk factor that causes a huge burden for society, in terms of death, health disorders, and huge socio-economic costs. The southern European countries face a more threatening problem because they experience the effects of both anthropogenic pollutants and natural dusts (particulate matter [PM]). The European Environment Agency reported the number of premature deaths in the 28 countries of the European Union attributable to air pollutant exposure in the year 2016: 374,000 for PM2.5, 68,000 for nitrogen dioxide, and 14,000 for ozone. In Italy, time series and analytical epidemiological studies showed increased cardio-respiratory hospital admissions and mortality, as well as increased risk of respiratory diseases in people living in urban areas. Based on abundant evidence, the World Health Organization, which hosts the Global Alliance against Chronic Respiratory Diseases (GARD), the scientific respiratory societies, and the patients' associations, as well as others in the health sector, must increase their engagement in advocacy for clean air policies.

Lung cancer screening (LCS) combined with smoking cessation programs is a critical strategy for reducing lung cancer mortality. Understanding the perspectives of cigarette users and former ones on these interventions is essential for enhancing their acceptability and effectiveness. This study aimed to explore, in Italy, the perceptions and experiences of individuals eligible for LCS within the context of a smoking cessation program. This multicenter qualitative study was conducted in two Italian regions as part of a larger project the Italian League against Cancer promoted. Using purposive sampling, we included (a) cigarette users and former ones who participated in an Italian trial, ITALUNG study, and (b) cigarette users who had been offered individual or group smoking cessation interventions and were theoretically eligible for screening in the following years (aged 50-70, ≥15 pack-years). Data were collected through open-ended semi-structured interviews and focus group meetings and analyzed using reflexive thematic analysis. The data analysis yielded six themes covering participants' views on the interactions between the two types of interventions (screening and smoking cessation program). Across their data, we generated the following themes: (i) depreciation and fatalism toward the risk of smoking, (ii) self-blaming and ethicality, (iii) ambivalent impact of the screening on smoking, (iv) LCS-related information and concerns, (v) teachable and motivating moments, and (vi) non-stigmatizing communication and testimony by professionals. Our study underscores the importance of avoiding stigma and respecting the dignity of cigarette users in implementing LCS and smoking cessation programs. Clear communication and supportive interactions with healthcare providers are crucial for enhancing the acceptability and effectiveness of these interventions. Future research should focus on quantifying these findings and exploring additional factors influencing the acceptability and effectiveness of combined LCS and smoking cessation programs.

Background: Pleural effusion (PE) is a common condition where accurate detection is essential for management. Thoracic ultrasound (TUS) is the first-line modality owing to safety, portability, and high sensitivity, but accuracy is operator-dependent. Artificial intelligence (AI)-based automated analysis has been explored as an adjunct, with early evidence suggesting potential to reduce variability and standardise interpretation. This review evaluates the diagnostic accuracy of AI-assisted TUS for PE detection. Methods: This review was registered with PROSPERO (CRD420251128416) and followed PRISMA guidelines. MEDLINE, Scopus, Google Scholar, IEEE Xplore, Cochrane CENTRAL, and ClinicalTrials.gov were searched through 20 August 2025 for studies assessing AI-based TUS analysis for PE. Eligible studies required recognised reference standards (expert interpretation or chest CT). Risk of bias was assessed with QUADAS-2, and certainty with GRADE. Owing to heterogeneity, structured narrative synthesis was performed instead of meta-analysis. Results: Five studies (7565 patients) published between 2021–2025 were included. All used convolutional neural networks with varied architectures (ResNet, EfficientNet, U-net). Sensitivity ranged 70.6–100%, specificity 67–100%, and AUC 0.77–0.99. Performance was reduced for small, trace, or complex effusions and in critically ill patients. External validation showed attenuation compared with internal testing. All studies had high risk of bias in patient selection and index test conduct, reflecting retrospective designs and inadequate dataset separation. Conclusions: AI-assisted TUS shows promising diagnostic performance for PE detection in curated datasets; however, evidence is inconsistent and limited by key methodological weaknesses. Overall certainty is low-to-moderate, constrained by retrospective designs, limited dataset separation, and scarce external validation. Current evidence is insufficient to support routine clinical use. Robust prospective multicentre studies with rigorous independent validation and evaluation of clinically meaningful outcomes are essential before clinical implementation can be considered.

Background: Long COVID has become a burden on healthcare systems worldwide. Research into the etiology and risk factors has been impeded by observing all diverse manifestations as part of a single entity. We aimed to determine patterns of symptoms in convalescing COVID-19 patients. Methods: Symptomatic patients were recruited from four countries. Data were collected regarding demographics, comorbidities, acute disease and persistent symptoms. Factor analysis was performed to elucidate symptom patterns. Associations of the patterns with patients’ characteristics, features of acute disease and effect on daily life were sought. Results: We included 1027 symptomatic post-COVID individuals in the analysis. The majority of participants were graded as having a non-severe acute COVID-19 (N = 763, 74.3%). We identified six patterns of symptoms: cognitive, pain-syndrome, pulmonary, cardiac, anosmia-dysgeusia and headache. The cognitive pattern was the major symptoms pattern, explaining 26.2% of the variance; the other patterns each explained 6.5–9.5% of the variance. The cognitive pattern was higher in patients who were outpatients during the acute disease. The pain-syndrome pattern was associated with acute disease severity, higher in women and increased with age. The pulmonary pattern was associated with prior lung disease and severe acute disease. Only two of the patterns (cognitive and cardiac) were associated with failure to return to pre-COVID occupational and physical activity status. Conclusion: Long COVID diverse symptoms can be grouped into six unique patterns. Using these patterns in future research may improve our understanding of pathophysiology and risk factors of persistent COVID, provide homogenous terminology for clinical research, and direct therapeutic interventions.

The ITALUNG trial started in 2004 and compared lung cancer (LC) and other-causes mortality in 55–69 years-aged smokers and ex-smokers who were randomized to four annual chest low-dose CT (LDCT) or usual care. ITALUNG showed a lower LC and cardiovascular mortality in the screened subjects after 13 years of follow-up, especially in women, and produced many ancillary studies. They included recruitment results of a population-based mimicking approach, development of software for computer-aided diagnosis (CAD) and lung nodules volumetry, LDCT assessment of pulmonary emphysema and coronary artery calcifications (CAC) and their relevance to long-term mortality, results of a smoking-cessation intervention, assessment of the radiations dose associated with screening LDCT, and the results of biomarkers assays. Moreover, ITALUNG data indicated that screen-detected LCs are mostly already present at baseline LDCT, can present as lung cancer associated with cystic airspaces, and can be multiple. However, several issues of LC screening are still unaddressed. They include the annual vs. biennial pace of LDCT, choice between opportunistic or population-based recruitment. and between uni or multi-centre screening, implementation of CAD-assisted reading, containment of false positive and negative LDCT results, incorporation of emphysema. and CAC quantification in models of personalized LC and mortality risk, validation of ultra-LDCT acquisitions, optimization of the smoking-cessation intervention. and prospective validation of the biomarkers.

Background: To quantitatively evaluate CT lung abnormalities in COVID-19 survivors from the acute phase to 24-month follow-up. Quantitative CT features as predictors of abnormalities’ persistence were investigated. Methods: Patients who survived COVID-19 were retrospectively enrolled and underwent a chest CT at baseline (T0) and 3 months (T3) after discharge, with pulmonary function tests (PFTs). Patients with residual CT abnormalities repeated the CT at 12 (T12) and 24 (T24) months after discharge. A machine-learning-based software, CALIPER, calculated the CT percentage of the whole lung of normal parenchyma, ground glass (GG), reticulation (Ret), and vascular-related structures (VRSs). Differences (Δ) were calculated between time points. Receiver operating characteristic (ROC) curve analyses were performed to test the baseline parameters as predictors of functional impairment at T3 and of the persistence of CT abnormalities at T12. Results: The cohort included 128 patients at T0, 133 at T3, 61 at T12, and 34 at T24. The GG medians were 8.44%, 0.14%, 0.13% and 0.12% at T0, T3, T12 and T24. The Ret medians were 2.79% at T0 and 0.14% at the following time points. All Δ significantly differed from 0, except between T12 and T24. The GG and VRSs at T0 achieved AUCs of 0.73 as predictors of functional impairment, and area under the curves (AUCs) of 0.71 and 0.72 for the persistence of CT abnormalities at T12. Conclusions: CALIPER accurately quantified the CT changes up to the 24-month follow-up. Resolution mostly occurred at T3, and Ret persisting at T12 was almost unchanged at T24. The baseline parameters were good predictors of functional impairment at T3 and of abnormalities’ persistence at T12.

Background Traffic-related air pollution is a potential risk factor for human respiratory health. A Geographical Information System (GIS) approach was used to examine whether distance from a main road (the Tosco-Romagnola road) affected respiratory health status. Methods We used data collected during an epidemiological survey performed in the Pisa-Cascina area (central Italy) in the period 1991-93. A total of 2841 subjects participated in the survey and filled out a standardized questionnaire on health status, socio-demographic information, and personal habits. A variable proportion of subjects performed lung function and allergy tests. Highly exposed subjects were defined as those living within 100 m of the main road, moderately exposed as those living between 100 and 250 m from the road, and unexposed as those living between 250 and 800 m from the road. Statistical analyses were conducted to compare the risks for respiratory symptoms and diseases between exposed and unexposed. All analyses were stratified by gender. Results The study comprised 2062 subjects: mean age was 45.9 years for men and 48.9 years for women. Compared to subjects living between 250 m and 800 m from the main road, subjects living within 100 m of the main road had increased adjusted risks for persistent wheeze (OR = 1.76, 95% CI = 1.08-2.87), COPD diagnosis (OR = 1.80, 95% CI = 1.03-3.08), and reduced FEV 1 /FVC ratio (OR = 2.07, 95% CI = 1.11-3.87) among males, and for dyspnea (OR = 1.61, 95% CI = 1.13-2.27), positivity to skin prick test (OR = 1.83, 95% CI = 1.11-3.00), asthma diagnosis (OR = 1.68, 95% CI = 0.97-2.88) and attacks of shortness of breath with wheeze (OR = 1.67, 95% CI = 0.98-2.84) among females. Conclusion This study points out the potential effects of traffic-related air pollution on respiratory health status, including lung function impairment. It also highlights the added value of GIS in environmental health research.

BackgroundITALUNG is contributing to the European evaluation of low-dose CT (LDCT) screening for lung cancer (LC).MethodsEligible subjects aged 55–69 years, smokers or ex-smokers (at least 20 pack-years in the last 10 years), were randomised to receive an annual invitation for LDCT screening for 4 years (active group) or to usual care (control group). All participants were followed up for vital status and cause of death (at the end of 2014) and LC incidence (at the end of 2013). Pathological and clinical information was collected from the Tuscan Cancer Registry data.Results1613 subjects were randomly assigned to the active group and 1593 to the control group. At the end of the follow-up period 67 LC cases were diagnosed in the active group and 71 in the control group (rate ratio (RR)=0.93; 95% CI 0.67 to 1.30). A greater proportion of stage I LC was observed in the active group (36% vs 11%, p<0.001). Non-significant reductions of 17% (RR=0.83; 95% CI 0.67 to 1.03) for overall mortality and 30% (RR=0.70; 95% CI 0.47 to 1.03) for LC-specific mortality were estimated.ConclusionsDespite the lack of statistical significance, the ITALUNG trial outcomes suggest that LDCT screening could reduce LC and overall mortality. Moreover, the comparison of the number of LC cases diagnosed in the two groups does not show overdiagnosis after an adequate follow-up period. A pooled analysis of all European screening trials is advocated to assess the benefit-to-harm ratio of LDCT screening and its implementation in public health settings.Trial registration numberResults, NCT02777996.

Proceedings of the European Semirs in Respiratory Medicine course,Long-Term Integrated Care of COPD Patientsheld in Stresa, Italy, on 16-17 June, 2016

Tobacco dependence is a chronic relapsing disease that needs continuous treatment. In combination with behavioural support, pharmacotherapy is a proven key component for supporting smoking cessation. Effective drugs are available and recommended: nicotine replacement therapy (NRT), bupropion and varenicline. Much research into new pharmacological approaches is ongoing, combining 'old' and 'new' drugs and personalizing a pharmacological treatment for a single smoker/patient; other new medications and vaccines are in development. Overall, pharmacotherapy seems to have efficacy and cost-effectiveness in real life, thus physicians should become familiar with these medicines. Further efforts should be aimed at optimizing treatment management and increasing smoking cessation rates in the general population.