Burden Of Lung Disease Research Articles

CNN-O-ELMNet: Optimized Lightweight and Generalized Model for Lung Disease Classification and Severity Assessment.

The high burden of lung diseases on healthcare necessitates effective detection methods. Current Computer-aided design (CAD) systems are limited by their focus on specific diseases and computationally demanding deep learning models. To overcome these challenges, we introduce CNN-O-ELMNet, a lightweight classification model designed to efficiently detect various lung diseases, surpassing the limitations of disease-specific CAD systems and the complexity of deep learning models. This model combines a convolutional neural network for deep feature extraction with an optimized extreme learning machine, utilizing the imperialistic competitive algorithm for enhanced predictions. We then evaluated the effectiveness of CNN-O-ELMNet using benchmark datasets for lung diseases: distinguishing pneumothorax vs. non-pneumothorax, tuberculosis vs. normal, and lung cancer vs. healthy cases. Our findings demonstrate that CNN-O-ELMNet significantly outperformed (p < 0.05) state-of-the-art methods in binary classifications for tuberculosis and cancer, achieving accuracies of 97.85% and 97.70%, respectively, while maintaining low computational complexity with only 2481 trainable parameters. We also extended the model to categorize lung disease severity based on Brixia scores. Achieving a 96.20% accuracy in multi-class assessment for mild, moderate, and severe cases, makes it suitable for deployment in lightweight healthcare devices.

Resolvin D1 improves airway inflammation and exercise capacity in cystic fibrosis lung disease.

Mucus plugging and non-resolving inflammation are inherent features of cystic fibrosis (CF) that may lead to progressive lung disease and exercise intolerance, which are the main causes of morbidity and mortality for people with CF. Therefore, understanding the influence of mucus on basic mechanisms underlying the inflammatory response and identifying strategies to resolve mucus-driven airway inflammation and consequent morbidity in CF are of wide interest. Here, we investigated the effects of the proresolving lipid mediator resolvin (Rv) D1 on mucus-related inflammation as a proof-of-concept to alleviate the burden of lung disease and restore exercise intolerance in CF. We tested the effects of RvD1 on inflammatory responses of human organotypic airways and leukocytes to CF mucus and of humanized mice expressing the epithelial Na + channel (βENaC-Tg) having CF-like mucus obstruction, lung disease, and physical exercise intolerance. RvD1 reduced pathogenic phenotypes of CF-airway supernatant (ASN)-stimulated human neutrophils, including loss of L-selectin shedding and CD16. RNASeq analysis identified select transcripts and pathways regulated by RvD1 in ASN-stimulated CF bronchial epithelial cells that are involved in sugar metabolism, NF-κB activation and inflammation, and response to stress. In in vivo inflammation using βENaC TG mice, RvD1 reduced total leukocytes, PMN, and interstitial Siglec-MΦ when given at 6-8 weeks of age, and in older mice at 10-12 weeks of age, along with the decrease of pro-inflammatory chemokines and increase of anti-inflammatory IL-10. Furthermore, RvD1 treatment promoted the resolution of pulmonary exacerbation caused by Pseudomonas aeruginosa infection and significantly enhanced physical activity and energy expenditure associated with mucus obstruction, which was impaired in βENaC-Tg mice compared with wild-type. These results demonstrate that RvD1 can rectify features of CF and offer proof-of-concept for its therapeutic application in this and other muco-obstructive lung diseases.

Inhaled corticosteroids to improve lung function in children (aged 6–12 years) who were born very preterm (PICSI): a randomised, double-blind, placebo-controlled trial

Despite the substantial burden of lung disease throughout childhood in children who were born very preterm, there are no evidence-based interventions to improve lung health beyond the neonatal period. We tested the hypothesis that inhaled corticosteroid improves lung function in this population. PICSI was a randomised, double-blind, placebo-controlled trial at Perth Children's Hospital (Perth, WA, Australia) to assess whether fluticasone propionate, an inhaled corticosteroid, improves lung function in children who had been born very preterm (<32 weeks of gestation). Eligible children were aged 6-12 years and did not have severe congenital abnormalities, cardiopulmonary defects, neurodevelopmental impairment, diabetes, or any glucocorticoid use within the preceding 3 months. Participants were randomly assigned (1:1) to receive 125 μg fluticasone propionate or placebo twice daily for 12 weeks. Participants were stratified for sex, age, bronchopulmonary dysplasia diagnosis, and recent respiratory symptoms using the biased-coin minimisation technique. The primary outcome was change in pre-bronchodilator forced expiratory volume in 1 s (FEV1) after 12 weeks of treatment. Data were analysed by intention-to-treat (ie, all participants who were randomly assigned and took at least the tolerance dose of the drug). All participants were included in the safety analyses. This trial is registered at the Australian and New Zealand Clinical Trials Registry, number 12618000781246. Between Oct 23, 2018, and Feb 4, 2022, 170 participants were randomly assigned and received at least the tolerance dose (83 received placebo and 87 received inhaled corticosteroid). 92 (54%) participants were male and 78 (46%) were female. 31 participants discontinued treatment before 12 weeks (14 in the placebo group and 17 in the inhaled corticosteroid group), mostly due to the impact of the COVID-19 pandemic. When analysed by intention-to-treat, the change in pre-bronchodilator FEV1 Z score over 12 weeks was -0·11 (95% CI -0·21 to 0·00) in the placebo group and 0·20 (0·11 to 0·30) in the inhaled corticosteroid group (imputed mean difference 0·30, 0·15-0·45). Three of 83 participants in the inhaled corticosteroid group had adverse events requiring treatment discontinuation (exacerbation of asthma-like symptoms). One of 87 participants in the placebo group had an adverse event requiring treatment discontinuation (inability to tolerate the treatment with dizziness, headaches, stomach pains, and worsening of a skin condition). As a group, children born very preterm have only modestly improved lung function when treated with inhaled corticosteroid for 12 weeks. Future studies should consider individual phenotypes of lung disease after preterm birth and other agents to improve management of prematurity-associated lung disease. Australian National Health and Medical Research Council, Telethon Kids Institute, and Curtin University.

The association of clinically relevant variables with chest radiograph lung disease burden quantified in real-time by radiologists upon initial presentation in individuals hospitalized with COVID-19

ObjectivesWe aimed to correlate lung disease burden on presentation chest radiographs (CXR), quantified at the time of study interpretation, with clinical presentation in patients hospitalized with coronavirus disease 2019 (COVID-19). Material and methodsThis retrospective cross-sectional study included 5833 consecutive adult patients, aged 18 and older, hospitalized with a diagnosis of COVID-19 with a CXR quantified in real-time while hospitalized in 1 of 12 acute care hospitals across a multihospital integrated healthcare network between March 24, 2020, and May 22, 2020. Lung disease burden was quantified in real-time by 118 radiologists on 5833 CXR at the time of exam interpretation with each lung annotated by the degree of lung opacity as clear (0%), mild (1–33%), moderate (34–66%), or severe (67–100%). CXR findings were classified as (1) clear versus disease, (2) unilateral versus bilateral, (3) symmetric versus asymmetric, or (4) not severe versus severe. Lung disease burden was characterized on initial presentation by patient demographics, co-morbidities, vital signs, and lab results with chi-square used for univariate analysis and logistic regression for multivariable analysis. ResultsPatients with severe lung disease were more likely to have oxygen impairment, an elevated respiratory rate, low albumin, high lactate dehydrogenase, and high ferritin compared to non-severe lung disease. A lack of opacities in COVID-19 was associated with a low estimated glomerular filtration rate, hypernatremia, and hypoglycemia. ConclusionsCOVID-19 lung disease burden quantified in real-time on presentation CXR was characterized by demographics, comorbidities, emergency severity index, Charlson Comorbidity Index, vital signs, and lab results on 5833 patients. This novel approach to real-time quantified chest radiograph lung disease burden by radiologists needs further research to understand how this information can be incorporated to improve clinical care for pulmonary-related diseases.. An absence of opacities in COVID-19 may be associated with poor oral intake and a prerenal state as evidenced by the association of clear CXRs with a low eGFR, hypernatremia, and hypoglycemia.

Globale Belastung durch Lungenkrankheiten bekämpfen

Three of the six leading causes of death worldwide are lung diseases: chronic obstructive pulmonary disease (COPD), lower respiratory tract infections and lung cancer. Other lung diseases are not to be underestimated either. Asthma is the most common chronic childhood disease, affecting 14% of all children; sleep apnea affects more than one hundred million people worldwide. Moreover, work-related lung diseases still affect more than fifty million workers. Each year, lung diseases kill more than seven million people, and cause distressing symptoms for many more. The 2017 Global Burden of Disease Study found that a country's sociodemographic index is a key determinant of mortality and health impairment from respiratory diseases. This year’s world lung day was held on September 25th, 2022, under the theme “Lung Health for All” and aimed to raise awareness for the global burden of lung diseases, particularly in low- and middle-income countries, and the importance of early detection and reducing inequalities. To address respiratory diseases more effectively, urgent work is needed to develop treatments and management strategies to alleviate symptoms and impact or halt disease progression.

Chest Disease Detection and Classification

Chest diseases &amp; conditions such as Atelectasis, Cardiomegaly, Lung consolidation, Hernia, and Fibrosis becoming increasingly prevalent in the Asia-Pacific region. The Asia-Pacific Burden of Respiratory Diseases study examined the disease and economic burden of lung diseases across the Asia-Pacific and more specifically India. The objective is to use a deep learning model to diagnose pathologies from Chest X-Rays. ML approaches on CT and Xray images aided incorrectly in identifying lung diseases. Respiratory diseases range from mild and self-limiting, such as the common cold, influenza, and pharyngitis to life-threatening diseases such as bacterial pneumonia, pleural thickening, hernia, and severe acute respiratory syndromes, such as COVID-19. Authorities &amp; Doctors will be able to deal with the effects more efficiently if such illnesses can be detected speedily and accurately with little human intervention in the future. In addition, various additional elements, such as environmental influences and commonalities among the most afflicted places, should be considered to slow the spread of lung diseases and precautions should be taken. Chest X-ray exam is one of the most frequent and cost-effective medical imaging examination. However clinical diagnosis of chest X-ray can be challenging, and sometimes believed to be harder than diagnosis via chest CT imaging. Even some promising work have been reported in the past, and especially in recent deep learning work on Tuberculosis (TB) classification. To achieve clinically relevant computer-aided detection and diagnosis (CAD) in real world medical sites on all data settings of chest X-rays is still very difficult, if not impossible when only several thousands of images are employed for study. This is evident from [2] where the performance deep neural networks for thorax disease recognition is severely limited by the availability of only 4143 frontal view images [3].

Tackling the global burden of lung disease through prevention and early diagnosis

Three of the top six causes of death worldwide are lung diseases: chronic obstructive pulmonary disease (COPD), lower respiratory tract infections, and lung cancer. As well as killing 7·6 million people every year, lung disease also causes distressing symptoms and disability for many more. The Global Burden of Disease Study 2017 identified that a country's sociodemographic index was a key factor affecting mortality and loss of health from respiratory diseases.1 Under the slogan “Lung Health for All”, World Lung Day on Sept 25 aims to highlight the global burden caused by lung disease, especially in low-income and middle-income countries (LMICs), and the importance of early detection and the reduction of inequalities.

Lung disease burden assessment by oscillometry in a systematically disadvantaged urban population experiencing homelessness or at-risk for homelessness in Ottawa, Canada from a prospective observational study

RationaleOscillometry is an emerging technique that offers some advantages over spirometry as it does not require forced exhalation and may detect early changes in respiratory pathology. Obstructive lung disease disproportionately impacts people experiencing homelessness with a high symptoms burden, yet oscillometry is not studied in this population.ObjectivesTo assess lung disease and symptom burden using oscillometry in people experiencing homelessness or at-risk of homelessness using a community-based participatory action research approach (The Bridge Model™).MethodsOf 80 recruited, 55 completed baseline oscillometry, 64 completed spirometry, and all completed patient-reported outcomes with demographics, health, and respiratory symptom related questionnaires in the Participatory Research in Ottawa: Management and Point-of-Care for Tobacco Dependence project. Using a two-tail t-test, we compared mean oscillometry values for airway resistance (R5–20), reactance area under the curve (Ax) and reactance at 5 Hz (X5) amongst individuals with fixed-ratio method (FEV1/FVC ratio < 0.70) and LLN (FEV1/FVC ratio ≤ LLN) spirometry diagnosed chronic obstructive pulmonary disease (COPD). We compared mean oscillometry parameters based on participants’ COPD assessment test (CAT) scores using ANOVA test.ResultsThere was no significant difference between the pre- and post- bronchodilator values of R5–20 and Ax for the fixed ratio method (p = 0.63 and 0.43) and the LLN method (p = 0.45 and 0.36). There was a significant difference in all three of the oscillometry parameters, R5–20, Ax and X5, based on CAT score (p = 0.009, 0.007 and 0.05, respectively). There was a significant difference in R5–20 and Ax based on the presence of phlegm (p = 0.03 and 0.02, respectively) and the presence of wheeze (p = 0.05 and 0.01, respectively). Oscillometry data did not correlate with spirometry data, but it was associated with CAT scores and correlated with the presence of self-reported symptoms of phlegm and wheeze in this population.ConclusionsOscillometry is associated with respiratory symptom burden and highlights the need for future studies to generate more robust data regarding the use of oscillometry in systematically disadvantaged populations where disease burden is disproportionately higher than the general population.TrialRegistration: ClinicalTrails.gov—NCT03626064, Retrospective registered: August 2018, https://clinicaltrials.gov/ct2/show/NCT03626064

An epigenome-wide study of DNA methylation profiles and lung function among American Indians in the Strong Heart Study

BackgroundEpigenetic modifications, including DNA methylation (DNAm), are often related to environmental exposures, and are increasingly recognized as key processes in the pathogenesis of chronic lung disease. American Indian communities have a high burden of lung disease compared to the national average. The objective of this study was to investigate the association of DNAm and lung function in the Strong Heart Study (SHS). We conducted a cross-sectional study of American Indian adults, 45–74 years of age who participated in the SHS. DNAm was measured using the Illumina Infinium Human MethylationEPIC platform at baseline (1989–1991). Lung function was measured via spirometry, including forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC), at visit 2 (1993–1995). Airflow limitation was defined as FEV1 < 70% predicted and FEV1/FVC < 0.7, restriction was defined as FEV1/FVC > 0.7 and FVC < 80% predicted, and normal spirometry was defined as FEV1/FVC > 0.7, FEV1 > 70% predicted, FVC > 80% predicted. We used elastic-net models to select relevant CpGs for lung function and spirometry-defined lung disease. We also conducted bioinformatic analyses to evaluate the biological plausibility of the findings.ResultsAmong 1677 participants, 21.2% had spirometry-defined airflow limitation and 13.6% had spirometry-defined restrictive pattern lung function. Elastic-net models selected 1118 Differentially Methylated Positions (DMPs) as predictors of airflow limitation and 1385 for restrictive pattern lung function. A total of 12 DMPs overlapped between airflow limitation and restrictive pattern. EGFR, MAPK1 and PRPF8 genes were the most connected nodes in the protein–protein interaction network. Many of the DMPs targeted genes with biological roles related to lung function such as protein kinases.ConclusionWe found multiple differentially methylated CpG sites associated with chronic lung disease. These signals could contribute to better understand molecular mechanisms involved in lung disease, as assessed systemically, as well as to identify patterns that could be useful for diagnostic purposes. Further experimental and longitudinal studies are needed to assess whether DNA methylation has a causal role in lung disease.

Humain Lens: The Disruptive Impact of AI and Precision Lung Data on Respiratory Trials

Humain Lens: The Disruptive Impact of AI and Precision Lung Data on Respiratory Trials

Inflammation, ageing and diseases of the lung: Potential therapeutic strategies from shared biological pathways

Lung diseases disproportionately affect elderly individuals. The lungs form a unique environment: a highly elastic organ with gaseous exchange requiring the closest proximity of inhaled air containing harmful agents and the circulating blood. The lungs are highly susceptible to senescence, with age and 'inflammageing' creating a pro-inflammatory environment with a reduced capacity to deal with challenges. While lung diseases may have disparate causes, the burden of ageing and inflammation provides a common process that can exacerbate seemingly unrelated pathologies. However, these shared pathways may also provide a common route to treatment, with increased interest in drugs that target ageing processes across respiratory diseases. In this review, we will examine the evidence for the increased burden of lung disease in older adults, the structural and functional changes seen with advancing age and assess what our expanding knowledge of inflammation and ageing pathways could mean for the treatment of lung disease. LINKED ARTICLES: This article is part of a themed issue on Inflammation, Repair and Ageing. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.9/issuetoc.

Advanced In Vitro Lung Models for Drug and Toxicity Screening: The Promising Role of Induced Pluripotent Stem Cells.

The substantial socioeconomic burden of lung diseases, recently highlighted by the disastrous impact of the coronavirus disease 2019 (COVID-19) pandemic, accentuates the need for interventive treatments capable of decelerating disease progression, limiting organ damage, and contributing to a functional tissue recovery. However, this is hampered by the lack of accurate human lung research models, which currently fail to reproduce the human pulmonary architecture and biochemical environment. Induced pluripotent stem cells (iPSCs) and organ-on-chip (OOC) technologies possess suitable characteristics for the generation of physiologically relevant in vitro lung models, allowing for developmental studies, disease modeling, and toxicological screening. Importantly, these platforms represent potential alternatives for animal testing, according to the 3Rs (replace, reduce, refine) principle, and hold promise for the identification and approval of new chemicals under the European REACH (registration, evaluation, authorization and restriction of chemicals) framework. As such, this review aims to summarize recent progress made in human iPSC- and OOC-based in vitro lung models. A general overview of the present applications of in vitro lung models is presented, followed by a summary of currently used protocols to generate different lung cell types from iPSCs. Lastly, recently developed iPSC-based lung models are discussed.

Understanding lung health beliefs in low-resource settings

Although lung disease burden is high and the need for improved health outcomes is great in low-resource settings, successful adoption of implementation research strategies has often been challenging.1 Two common preventable risk factors for chronic respiratory diseases (CRDs) are tobacco use and household air pollution (HAP). However, many middle-income and low-income countries continue to face rising smoking epidemics despite increasing legislation of WHO tobacco control policy recommendations.

Preclinical MRI to quantify pulmonary disease severity and trajectories in poorly characterized mouse models: A pedagogical example using data from novel transgenic models of lung fibrosis

Structural remodeling in lung disease is progressive and heterogeneous, making temporally and spatially explicit information necessary to understand disease initiation and progression. While mouse models are essential to elucidate mechanistic pathways underlying disease, the experimental tools commonly available to quantify lung disease burden are typically invasive (e.g., histology). This necessitates large cross-sectional studies with terminal endpoints, which increases experimental complexity and expense. Alternatively, magnetic resonance imaging (MRI) provides information noninvasively, thus permitting robust, repeated-measures statistics. Although lung MRI is challenging due to low tissue density and rapid apparent transverse relaxation (T2* <1 ms), various imaging methods have been proposed to quantify disease burden. However, there are no widely accepted strategies for preclinical lung MRI. As such, it can be difficult for researchers who lack lung imaging expertise to design experimental protocols—particularly for novel mouse models. Here, we build upon prior work from several research groups to describe a widely applicable acquisition and analysis pipeline that can be implemented without prior preclinical pulmonary MRI experience. Our approach utilizes 3D radial ultrashort echo time (UTE) MRI with retrospective gating and lung segmentation is facilitated with a deep-learning algorithm. This pipeline was deployed to assess disease dynamics over 255 days in novel, transgenic mouse models of lung fibrosis based on disease-associated, loss-of-function mutations in Surfactant Protein-C. Previously identified imaging biomarkers (tidal volume, signal coefficient of variation, etc.) were calculated semi-automatically from these data, with an objectively-defined high signal volume identified as the most robust metric. Beyond quantifying disease dynamics, we discuss common pitfalls encountered in preclinical lung MRI and present systematic approaches to identify and mitigate these challenges. While the experimental results and specific pedagogical examples are confined to lung fibrosis, the tools and approaches presented should be broadly useful to quantify structural lung disease in a wide range of mouse models.

Impact of lung morphology on clinical outcomes with riociguat in patients with pulmonary hypertension and idiopathic interstitial pneumonia: A post hoc subgroup analysis of the RISE-IIP study

Riociguat in Patients with Symptomatic Pulmonary Hypertension associated with Idiopathic Interstitial Pneumonias (RISE-IIP), a randomized, controlled, phase 2b trial of riociguat for pulmonary hypertension associated with idiopathic interstitial pneumonia, was terminated early due to increased mortality in riociguat-treated patients. Baseline characteristics of enrolled patients demonstrated a low diffusing capacity of the lung for carbon monoxide (DLCO) with preserved lung volumes at baseline, suggesting the presence of combined pulmonary fibrosis and emphysema (CPFE) in some patients. This post hoc analysis of RISE-IIP was undertaken to explore lung morphology, assessed by high-resolution computed tomography, and associated clinical outcomes. Available baseline/pre-baseline high-resolution computed tomography scans were reviewed centrally by 2 radiologists. The extent of emphysema and fibrosis was retrospectively scored and combined to provide the total CPFE score. Data were available for 65/147 patients (44%), including 15/27 fatal cases (56%). Of these, 41/65 patients (63%) had CPFE. Mortality was higher in patients with CPFE (12/41; 29%) than those without (3/24; 13%). Fourteen patients with CPFE had emphysema > fibrosis (4 died). No relationship was observed between CPFE score, survival status, and treatment assignment. A low DLCO, short 6-min walking distance, and high forced vital capacity:DLCO ratio at baseline also appeared to be risk factors for mortality. High parenchymal lung disease burden and the presence of more emphysema than fibrosis might have predisposed patients with pulmonary hypertension associated with idiopathic interstitial pneumonia to poor outcomes in RISE-IIP. Future studies of therapy for group 3 pulmonary hypertension should include centrally adjudicated imaging for morphologic phenotyping and disease burden evaluation during screening.

The burden of chronic respiratory diseases in adults in Nepal: A systematic review.

While chronic lung disease causes substantial global morbidity and mortality, global estimates have primarily been based on broad assumptions. Specific country data from low-income countries such as Nepal are limited. This review assessed primary evidence on chronic respiratory disease burden among adults in Nepal. A systematic search was performed in June 2019 (updated May 2020) for studies through nine databases. High levels of heterogeneity deemed a narrative synthesis appropriate. Among 27 eligible studies identified, most were low-moderate quality with cross-sectional and retrospective study design. Chronic lung diseases identified were chronic obstructive pulmonary disease (COPD), asthma, bronchiectasis and restrictive lung diseases. Studies were categorised as: (i) community-based, (ii) hospital-based and (iii) comorbidity-related and disease burden. Reported disease prevalence varied widely (COPD, 1.67–14.3%; asthma, 4.2–8.9%). The prevalence of airflow obstruction was higher among rural dwellers (15.8%) and those exposed to household air pollution from domestic biomass burning as opposed to liquid petroleum gas users (Odds Ratio: 2.06). Several comorbidities, including hypertension and diabetes mellitus added to the disease burden. The review shows limited literature on lung disease burden in Nepal. Publications varied in terms of overall quality. Good quality research studies with prospective cohorts related to respiratory conditions are required.

Vascular Pruning on CT and Interstitial Lung Abnormalities in the Framingham Heart Study

Pulmonary vascular disease is associated with poor outcomes in individuals affected by interstitial lung disease. The pulmonary vessels can be quantified with noninvasive imaging, but whether radiographic indicators of vasculopathy are associated with early interstitial changes is not known. Are pulmonary vascular volumes, quantified from CT scans, associated with interstitial lung abnormalities (ILA) in a community-based sample with a low burden of lung disease? In 2,386 participants of the Framingham Heart Study, we used CT imaging to calculate pulmonary vascular volumes, including the small vessel fraction (a surrogate of vascular pruning). We constructed multivariable logistic regression models to investigate associations of vascular volumes with ILA, progression of ILA, and restrictive pattern on spirometry. In secondary analyses, we additionally adjusted for diffusing capacity and emphysema, and performed a sensitivity analysis restricted to participants with normal FVC and diffusing capacity. In adjusted models, we found that lower pulmonary vascular volumes on CT were associated with greater odds of ILA, antecedent ILA progression, and restrictive pattern on spirometry. For example, each SD lower small vessel fraction was associated with 1.81-fold greater odds of ILA (95%CI, 1.41-2.31; P< .0001), and 1.63-fold greater odds of restriction on spirometry (95%CI, 1.18-2.24; P= .003). Similar patterns were seen after adjustment for diffusing capacity for carbon monoxide, emphysema, and among participants with normal lung function. In this cohort of community-dwelling adults not selected on the basis of lung disease, more severe vascular pruning on CT was associated with greater odds of ILA, ILA progression, and restrictive pattern on spirometry. Pruning on CT may be an indicator of early pulmonary vasculopathy associated with interstitial lung disease.

Flavonoid Content of Selected Foods – A Comparison of Four International Composition Tables

Abstract Objectives As part of the multinational Burden of Lung Disease (BOLD) survey, this study investigated the flavonoid content and agreement levels of foods included in BOLD's food frequency questionnaire (FFQ), using four international flavonoid composition tables. Methods The USDA (American), BioActive Substances in Food Information System (eBASIS; European), Indian Food Composition (IFCT), and Phenol-Explorer (European) Tables were selected for their comparable data on five subclasses of flavonoids (flavan-3-ols, flavanones, flavones, flavonols, and isoflavones). Flavonoid estimates were derived for all foods available in each table (n = 117 USDA; n = 77 eBASIS; n = 69 IFCT; n = 90 Phenol-Explorer), and comparisons were carried out for foods common between tables. Percentage differences of flavonoid content were calculated, and intra-class correlation coefficients (ICCs; 95% confidence intervals [95%CI]) estimated. ICC reliability was categorized as low (&amp;lt;0.5), moderate (0.50–0.75), good (0.75–0.90), or excellent (&amp;gt;0.90). Results Compared to the USDA Table, total flavonoid content was overestimated by 181.5%, 14.1%, and 26.5%, in the eBASIS, IFCT, and Phenol-Explorer tables, respectively. Compared to Phenol-Explorer, total flavonoid content was overestimated by 53.0% in eBASIS and by 29.6% in IFCT. The reliability for total flavonoid content between the USDA and Phenol-Explorer tables was moderate (ICC 0.51; 95% CI 0.33, 0.65), low between Phenol-Explorer and eBASIS (ICC 0.27; 95% CI 0.02, 0.49), and low between Phenol-Explorer and IFCT (ICC 0.22, 95%CI −0.07, 0.48). There was good-to-excellent reliability between USDA and Phenol-Explorer for flavanones and flavones (ICC 0.93; 95%CI 0.82, 0.98; and ICC 0.86; 95%CI 0.73, 0.93, respectively). Phenol-Explorer and IFCT showed good reliability for flavanone and flavanol subclasses. ICCs for other subclasses was low across tables. Conclusions Flavonoid estimates varied considerably across international tables. These differences should be taken into consideration when deriving flavonoid content in population-based surveys. Funding Sources MAA is funded by the European Union's Horizon 2020 Research and Innovation Programme (Marie Sklodowska-Curie Grant Agreement). The UK's Medical Research Council (MR/R011192/1) funds the BOLD stud.

Lung function in adults and future burden of obstructive lung diseases in a long-term follow-up

Spirometry is recommended in symptomatic smokers to identify obstructive lung diseases. However, it is unknown whether there are certain characteristics that can be used to identify the individual risk of developing obstructive lung diseases. The aim of this study was to examine the association between lung function in adults and burden of lung diseases throughout 27 years of follow-up. We performed a cohort study among individuals aged 30–49 years at baseline (1991). Spirometry measurements were divided into three groups: (1) FEV1/FVC < 70, (2) FEV1/FVC: 70–75, (3) FEV1/FVC > 75 (reference). Using negative binominal regression, the burden of lung diseases was measured by contacts to general practice, hospitalisations, redeemed respiratory medicine and socioeconomic parameters between 1991 and 2017. A total of 905 citizens were included; mean age of 40.3 years, 47.5% were males and 51.2% were smokers at baseline. The group with an FEV1/FVC: 70–75 received more respiratory medicine (IRR = 3.37 (95% CI: 2.69–4.23)), had lower income (IRR = 0.96 (95% CI: 0.93–0.98)), and had more contacts to general practice (IRR = 1.14 (95% CI: 1.07–1.21)) and hospitals for lung diseases (IRR = 2.39 (95% CI: 1.96–5.85)) compared to the reference group. We found an association between lung function and the future burden of lung diseases throughout 27 years of follow-up. In particular, adults with an FEV1/FVC: 70–75 need extra attention in the case finding.

Efforts to control air pollution in the Asia-Pacific region.

Efforts to control air pollution in the Asia-Pacific region.