Imaging-based assessment of lung function in a population cooking indoors with biomass fuel: a pilot study.

Biomass fuels (wood) are commonly used indoors in underventilated environments for cooking in the developing world, but the impact on lung physiology is poorly understood. Quantitative computed tomography (qCT) can provide sensitive metrics to compare the lungs of women cooking with wood vs. liquified petroleum gas (LPG). We prospectively assessed (qCT and spirometry) 23 primary female cooks (18 biomass, 5 LPG) with no history of cardiopulmonary disease in Thanjavur, India. CT was obtained at coached total lung capacity (TLC) and residual volume (RV). qCT assessment included texture-derived ground glass opacity [GGO: Adaptive Multiple Feature Method (AMFM)], air-trapping (expiratory voxels ≤ -856HU) and image registration-based assessment [Disease Probability Measure (DPM)] of emphysema, functional small airways disease (%AirTrapDPM), and regional lung mechanics. In addition, within-kitchen exposure assessments included particulate matter <2.5 µm(PM2.5), black carbon, ß-(1, 3)-d-glucan (surrogate for fungi), and endotoxin. Air-trapping went undetected at RV via the threshold-based measure (voxels ≤ -856HU), possibly due to density shifts in the presence of inflammation. However, DPM, utilizing image-matching, demonstrated significant air-trapping in biomass vs. LPG cooks (P = 0.049). A subset of biomass cooks (6/18), identified using k-means clustering, had markedly altered DPM-metrics: greater air-trapping (P < 0.001), lower TLC-RV volume change (P < 0.001), a lower mean anisotropic deformation index (ADI; P < 0.001), and elevated % GGO (P < 0.02). Across all subjects, a texture measure of bronchovascular bundles was correlated to the log-transformed ß-(1, 3)-d-glucan concentration (P = 0.026, R = 0.46), and black carbon (P = 0.04, R = 0.44). This pilot study identified environmental links with qCT-based lung pathologies and a cluster of biomass cooks (33%) with significant small airways disease.NEW & NOTEWORTHY Quantitative computed tomography has identified a cluster of women (33%) cooking with biomass fuels (wood) with image-based markers of functional small airways disease and associated alterations in regional lung mechanics. Texture and image registration-based metrics of lung function may allow for early detection of potential inflammatory processes that may arise in response to inhaled biomass smoke, and help identify phenotypes of chronic lung disease prevalent in nonsmoking women in the developing world.

Predicting severe chronic obstructive pulmonary disease exacerbations using quantitative CT: a retrospective model development and external validation study.

BACKGROUND: Quantitative CT is becoming increasingly common for the characterisation of lung disease; however, its added potential as a clinical tool for predicting severe exacerbations remains understudied. We aimed to develop and validate quantitative CT-based models for predicting severe chronic obstructive pulmonary disease (COPD) exacerbations. METHODS: We analysed the Subpopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS) cohort, a multicentre study done at 12 clinical sites across the USA, of individuals aged 40-80 years from four strata: individuals who never smoked, individuals who smoked but had normal spirometry, individuals who smoked and had mild to moderate COPD, and individuals who smoked and had severe COPD. We used 3-year follow-up data to develop logistic regression classifiers for predicting severe exacerbations. Predictors included age, sex, race, BMI, pulmonary function, exacerbation history, smoking status, respiratory quality of life, and CT-based measures of density gradient texture and airway structure. We externally validated our models in a subset from the Genetic Epidemiology of COPD (COPDGene) cohort. Discriminative model performance was assessed using the area under the receiver operating characteristic curve (AUC), which was also compared with other predictors, including exacerbation history and the BMI, airflow obstruction, dyspnoea, and exercise capacity (BODE) index. We evaluated model calibration using calibration plots and Brier scores. FINDINGS: Participants in SPIROMICS were enrolled between Nov 12, 2010, and July 31, 2015. Participants in COPDGene were enrolled between Jan 10, 2008, and April 15, 2011. We included 1956 participants from the SPIROMICS cohort who had complete 3-year follow-up data: the mean age of the cohort was 63·1 years (SD 9·2) and 1017 (52%) were men and 939 (48%) were women. Among the 1956 participants, 434 (22%) had a history of at least one severe exacerbation. For the CT-based models, the AUC was 0·854 (95% CI 0·852-0·855) for at least one severe exacerbation within 3 years and 0·931 (0·930-0·933) for consistent exacerbations (defined as ≥1 acute episode in each of the 3 years). Models were well calibrated with low Brier scores (0·121 for at least one severe exacerbation; 0·039 for consistent exacerbations). For the prediction of at least one severe event during 3-year follow-up, AUCs were significantly higher with CT biomarkers (0·854 [0·852-0·855]) than exacerbation history (0·823 [0·822-0·825]) and BODE index 0·812 [0·811-0·814]). 6965 participants were included in the external validation cohort, with a mean age of 60·5 years (SD 8·9). In this cohort, AUC for at least one severe exacerbation was 0·768 (0·767-0·769; Brier score 0·088). INTERPRETATION: CT-based prediction models can be used for identification of patients with COPD who are at high risk of severe exacerbations. The newly identified CT biomarkers could potentially enable investigation into underlying disease mechanisms responsible for exacerbations. FUNDING: National Institutes of Health and the National Heart, Lung, and Blood Institute.

Patient Experiences with a Tertiary Care Post-COVID-19 Clinic.

Post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (PASC) is a complex condition with multisystem involvement. We assessed patients' experience with a PASC clinic established at University of Iowa in June 2020. A survey was electronically mailed in June 2021 asking about (1) symptoms and their impact on functional domains using the Patient-Reported Outcomes Measurement Information System (PROMIS) measures (Global Health and Cognitive Function Abilities) (2) satisfaction with clinic services, referrals, barriers to care, and recommended support resources. Survey completion rate was 35% (97/277). Majority were women (67%), Caucasian (93%), and were not hospitalized (76%) during acute COVID-19. As many as 50% reported wait time between 1 and 3 months, 40% traveled >1 h for an appointment and referred to various subspecialities. Participants reported high symptom burden-fatigue (77%), "brain fog" (73%), exercise intolerance (73%), anxiety (63%), sleep difficulties (56%) and depression (44%). On PROMIS measures, some patients scored significantly low (≥1.5 SD below mean) in physical (22.7%), mental (15.9%), and cognitive (17.6%) domains. Approximately 61% to 93% of participants were satisfied with clinical services. Qualitative analysis added insight to their experience with healthcare. Participants suggested potential strategies for optimizing recovery, including continuity of care, a co-located multispecialty clinic, and receiving timely information from emerging research. Participants appreciated that physicians validated their symptoms and provided continuity of care and access to specialists.

Airway Detection in COPD at Low-Dose CT Using Deep Learning and Multiparametric Freeze and Grow.

Purpose: To present and validate a fully automated airway detection method at low-dose CT in patients with chronic obstructive pulmonary disease (COPD). Materials and Methods: In this retrospective study, deep learning (DL) and freeze-and-grow (FG) methods were optimized and applied to automatically detect airways at low-dose CT. Four data sets were used: two data sets consisting of matching standard- and low-dose CT scans from the Genetic Epidemiology of COPD (COPDGene) phase II (2014-2017) cohort (n = 2 × 236; mean age ± SD, 70 years ± 9; 123 women); one data set consisting of low-dose CT scans from the COPDGene phase III (2018-2020) cohort (n = 335; mean age ± SD, 73 years ± 8; 173 women); and one data set consisting of low-dose, anonymized CT scans from the 2003 Dutch-Belgian Randomized Lung Cancer Screening trial (n = 55) acquired by using different CT scanners. Performance measures for different methods were computed and compared by using the Wilcoxon signed rank test. Results: At low-dose CT, 56 294 of 62 480 (90.1%) airways of the reference total airway count (TAC) and 32 109 of 37 864 (84.8%) airways of the peripheral TAC (TACp), detected at standard-dose CT, were detected. Significant losses (P < .001) of 14 526 of 76 453 (19.0%) airways and 884 of 6908 (12.8%) airways in the TAC and 12 256 of 43 462 (28.2%) airways and 699 of 3882 (18.0%) airways in the TACp were observed, respectively, for the multiprotocol and multiscanner data without retraining. When using the automated low-dose CT method, TAC values of 347, 342, 323, and 266 and TACp values of 205, 202, 289, and 141 were observed for those who have never smoked and participants at Global Initiative for Chronic Obstructive Lung Disease stages 0, 1, and 2, respectively, which were superior to the respective values previously reported for matching groups when using a semiautomated method at standard-dose CT. Conclusion: A low-cost, automated CT-based airway detection method was suitable for investigation of airway phenotypes at low-dose CT.Keywords: Airway, Airway Count, Airway Detection, Chronic Obstructive Pulmonary Disease, CT, Deep Learning, Generalizability, Low-Dose CT, Segmentation, Thorax, LungClinical trial registration no. NCT00608764 Supplemental material is available for this article. © RSNA, 2022.

Ambient Air Pollution Exposure and Sleep Quality in COPD.

Rationale: Ambient air pollution exposure is associated with respiratory morbidity among individuals with chronic obstructive pulmonary disease (COPD), particularly among those with concomitant obesity. Although people with COPD report high incidence of poor sleep quality, no studies have evaluated the association between air pollution exposure, obesity, and sleep disturbances in COPD. Methods: We analyzed data collected from current and former smokers with COPD enrolled in the Subpopulations and Intermediate Outcome Measures in COPD -Air Pollution ancillary study (SPIROMICS AIR). Socio-demographics and anthropometric measurements were collected, and 1-year mean historical ambient particulate matter (PM2.5) and ozone concentrations at participants' residences were estimated by cohort-specific spatiotemporal modeling. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI), and regression models were constructed to determine the association of 1-year PM2.5 (1Yr-PM2.5) and 1-year ozone (1Yr-ozone) with the PSQI score, and whether obesity modified the association. Results: In 1308 participants (age: 65.8±7.8 years, 42% women), results of regression analyses suggest that each 10µg/m3 increase in 1Yr-PM2.5 was associated with a 2.1-point increase in PSQI (P=0.03). Obesity modified the association between 1Yr-PM2.5 and PSQI (P=0.03). In obese and overweight participants, a 10µg/m3 increase in 1Yr-PM2.5 was associated with a higher PSQI (4.0 points, P<0.01, and 3.4 points, P<0.01, respectively); but no association in lean-normal weight participants (P=0.51). There was no association between 1 Yr-ozone and PSQI. Conclusions: Overweight and obese individuals with COPD appear to be susceptible to the effects of ambient PM2.5 on sleep quality. In COPD, weight and ambient PM2.5 may be modifiable risk factors to improve sleep quality.

Brain Fog and Fatigue following COVID-19 Infection: An Exploratory Study of Patient Experiences of Long COVID.

Post-acute sequelae of SARS-CoV-2 (PASC) is a poorly understood condition with significant impact on quality of life. We aimed to better understand the lived experiences of patients with PASC, focusing on the impact of cognitive complaints ("brain fog") and fatigue on (1) daily activities, (2) work/employment, and (3) interpersonal relationships. We conducted semi-structured qualitative interviews with 15 patients of a Midwestern academic hospital's post-COVID-19 clinic. We audio-recorded, transcribed, and analyzed interviews thematically using a combined deductive-inductive approach and collected participants' characteristics from chart review. Participants frequently used descriptive and metaphorical language to describe symptoms that were relapsing-remitting and unpredictable. Fatigue and brain fog affected all domains and identified subthemes included symptoms' synergistic effects, difficulty with multitasking, lack of support, poor self-perception, and fear of loss of income and employment. Personal relationships were affected with change of responsibilities, difficulty parenting, social isolation, and guilt due to the burdens placed on family. Furthermore, underlying social stigma contributed to negative emotions, which significantly affected emotional and mental health. Our findings highlight PASC's negative impact on patients' daily lives. Providers can better support COVID-19 survivors during their recovery by identifying their needs in a sensitive and timely manner.

Brain Fog and Fatigue following COVID-19 Infection: An Exploratory Study of Patient Experiences of Long COVID.

Post-acute sequelae of SARS-CoV-2 (PASC) is a poorly understood condition with significant impact on quality of life. We aimed to better understand the lived experiences of patients with PASC, focusing on the impact of cognitive complaints ("brain fog") and fatigue on (1) daily activities, (2) work/employment, and (3) interpersonal relationships. We conducted semi-structured qualitative interviews with 15 patients of a Midwestern academic hospital's post-COVID-19 clinic. We audio-recorded, transcribed, and analyzed interviews thematically using a combined deductive-inductive approach and collected participants' characteristics from chart review. Participants frequently used descriptive and metaphorical language to describe symptoms that were relapsing-remitting and unpredictable. Fatigue and brain fog affected all domains and identified subthemes included symptoms' synergistic effects, difficulty with multitasking, lack of support, poor self-perception, and fear of loss of income and employment. Personal relationships were affected with change of responsibilities, difficulty parenting, social isolation, and guilt due to the burdens placed on family. Furthermore, underlying social stigma contributed to negative emotions, which significantly affected emotional and mental health. Our findings highlight PASC's negative impact on patients' daily lives. Providers can better support COVID-19 survivors during their recovery by identifying their needs in a sensitive and timely manner.

Bronchodilator Responsiveness in Tobacco-Exposed Persons with or without COPD.

BACKGROUND: Bronchodilator responsiveness (BDR), in obstructive lung disease varies over time and may be associated with distinct clinical features. RESEARCH QUESTION: Is consistent BDR over time (always present) differentially associated with obstructive lung disease features relative to inconsistent (sometimes present) or never (never present) BDR in tobacco-exposed people with or without COPD. STUDY DESIGN AND METHODS: We retrospectively analyzed data of 2,269 tobacco-exposed participants in SPIROMICS with or without COPD. We used various BDR definitions: change ≥200ml and ≥12% in FEV1 (FEV1-BDR), in FVC (FVC-BDR), and in FEV1 and/or FVC (ATS-BDR). Using generalized linear models adjusted for demographics, smoking history, post-bronchodilator FEV1 %predicted, and number of visits that the participant completed, we assess the association of BDR group: i) consistent BDR, ii) inconsistent BDR, and iii) never BDR with asthma, CT features, blood eosinophils, and FEV1 decline in participants without COPD (GOLD0) and the entire cohort (participants with or without COPD). RESULTS: Both consistent and inconsistent ATS-BDR were associated with asthma history and greater small airway disease (%PRMfSAD) relative to never ATS-BDR in GOLD0 participants and the entire cohort. We observed similar findings using FEV1-BDR and FVC-BDR definitions. Eosinophils did not consistently vary between BDR groups. Consistent BDR was associated with FEV1 decline over time relative to never BDR in the entire cohort. In GOLD0, both inconsistent (OR=3.20;95%CI 2.21 to 4.66;P<0.001) and consistent ATS-BDR group (OR=9.48;95%CI 3.77 to 29.12;P<0.001) were associated with progression to COPD relative to never ATS-BDR group. INTERPRETATION: Demonstration of BDR, even once, describes an obstructive lung disease phenotype with history of asthma, and greater small airway disease. Consistent demonstration of BDR indicates a high risk for lung function decline over time in the entire cohort and was associated with higher risk for progression to COPD in GOLD0.

Black carbon content in airway macrophages is associated with increased severe exacerbations and worse COPD morbidity in SPIROMICS.

BACKGROUND: Airway macrophages (AM), crucial for the immune response in chronic obstructive pulmonary disease (COPD), are exposed to environmental particulate matter (PM), which they retain in their cytoplasm as black carbon (BC). However, whether AM BC accurately reflects environmental PM2.5 exposure, and can serve as a biomarker of COPD outcomes, is unknown. METHODS: We analyzed induced sputum from participants at 7 of 12 sites SPIROMICS sites for AM BC content, which we related to exposures and to lung function and respiratory outcomes. Models were adjusted for batch (first vs. second), age, race (white vs. non-white), income (<$35,000, $35,000~$74,999, ≥$75,000, decline to answer), BMI, and use of long-acting beta-agonist/long-acting muscarinic antagonists, with sensitivity analysis performed with inclusion of urinary cotinine and lung function as covariates. RESULTS: Of 324 participants, 143 were current smokers and 201 had spirometric-confirmed COPD. Modeled indoor fine (< 2.5 µm in aerodynamic diameter) particulate matter (PM2.5) and urinary cotinine were associated with higher AM BC. Other assessed indoor and ambient pollutant exposures were not associated with higher AM BC. Higher AM BC was associated with worse lung function and odds of severe exacerbation, as well as worse functional status, respiratory symptoms and quality of life. CONCLUSION: Indoor PM2.5 and cigarette smoke exposure may lead to increased AM BC deposition. Black carbon content in AMs is associated with worse COPD morbidity in current and former smokers, which remained after sensitivity analysis adjusting for cigarette smoke burden. Airway macrophage BC, which may alter macrophage function, could serve as a predictor of experiencing worse respiratory symptoms and impaired lung function.

Prolonged, Physiologically Relevant Nicotine Concentrations in the Airways of Smokers.

Nicotine from cigarette smoke is a biologically active molecule that has pleiotropic effects in the airway, which could play a role in smoking induced lung disease. However, whether nicotine and its metabolites reach sustained, physiologically relevant concentrations on airway surfaces of smokers is not well defined. To address these issues, concentrations of nicotine, cotinine, and hydroxycotinine were measured by mass spectrometry (MS) in supernatants of induced sputum obtained from participants in the SubPopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS), an ongoing observational study that included never smokers, former smokers, and current smokers with and without chronic obstructive pulmonary disease (COPD). A total of 980 sputum supernatants were analyzed from 77 healthy never smokers, 494 former smokers (233 with COPD), and 396 active smokers (151 with COPD). Sputum nicotine, cotinine, and hydroxycotinine concentrations corresponded to self-reported smoking status and were strongly correlated to urine measures. A cutoff of ~8-10 ng/mL of sputum cotinine distinguished never smokers from active smokers. Accounting for sample dilution during processing, active smokers had airway nicotine concentrations in the 70-850 ng/mL (~0.5 to 5 µM) range, and concentrations remained elevated even in current smokers who had not smoked within 24 hours. This study demonstrates that airway nicotine and its metabolites are readily measured in sputum supernatants and can serve as biological markers of smoke exposure. In current smokers, nicotine is present at physiologically relevant concentrations for prolonged periods, supporting a contribution to cigarette induced airways disease.

Contrastive learning and subtyping of post-COVID-19 lung computed tomography images.

Patients who recovered from the novel coronavirus disease 2019 (COVID-19) may experience a range of long-term symptoms. Since the lung is the most common site of the infection, pulmonary sequelae may present persistently in COVID-19 survivors. To better understand the symptoms associated with impaired lung function in patients with post-COVID-19, we aimed to build a deep learning model which conducts two tasks: to differentiate post-COVID-19 from healthy subjects and to identify post-COVID-19 subtypes, based on the latent representations of lung computed tomography (CT) scans. CT scans of 140 post-COVID-19 subjects and 105 healthy controls were analyzed. A novel contrastive learning model was developed by introducing a lung volume transform to learn latent features of disease phenotypes from CT scans at inspiration and expiration of the same subjects. The model achieved 90% accuracy for the differentiation of the post-COVID-19 subjects from the healthy controls. Two clusters (C1 and C2) with distinct characteristics were identified among the post-COVID-19 subjects. C1 exhibited increased air-trapping caused by small airways disease (4.10%, p = 0.008) and diffusing capacity for carbon monoxide %predicted (DLCO %predicted, 101.95%, p < 0.001), while C2 had decreased lung volume (4.40L, p < 0.001) and increased ground glass opacity (GGO%, 15.85%, p < 0.001). The contrastive learning model is able to capture the latent features of two post-COVID-19 subtypes characterized by air-trapping due to small airways disease and airway-associated interstitial fibrotic-like patterns, respectively. The discovery of post-COVID-19 subtypes suggests the need for different managements and treatments of long-term sequelae of patients with post-COVID-19.

A 4-Year Retrospective Claims Analysis of Oral Corticosteroid Use and Health Conditions in Newly Diagnosed Medicare FFS Patients with COPD.

Purpose: We analyzed population-level administrative claims data for Medicare fee-for-service (FFS) beneficiaries to provide insights on systemic oral corticosteroid (OCS) use patterns and associated health conditions and acute events among patients newly diagnosed with chronic obstructive pulmonary disease (COPD). Background: COPD is a progressive inflammatory disease of the lungs, characterized by acute exacerbations that may lead to increased mortality. Short courses of systemic corticosteroids (SCS) are recommended to reduce recovery time from exacerbations, although SCS use has been associated with increased risk of adverse events. Methods: This study used 2013-2019 Medicare 100% FFS research identifiable files, which contain all Medicare Parts A, B, and D paid claims incurred by 100% of Medicare FFS beneficiaries. Descriptive statistics for patients newly diagnosed with COPD were analyzed, including OCS use, select health conditions and acute events, and COPD exacerbations. Statistical models were used to analyze the relationship between the incidence of select health conditions and events and cumulative OCS dosage. Results: Of Medicare FFS patients newly diagnosed with COPD, 36% received OCS in the 48 months following diagnosis, and 38% of OCS episodes lasted longer than the recommended 5-7 days. Patients had a variety of health conditions or acute events in the 24-month period prior to new COPD diagnosis, such as hypertension, depression/anxiety, type 2 diabetes, or osteoporosis, that could heighten the risks of OCS use. Patients treated with >1000 mg of prednisolone equivalent OCS in the 48 months following COPD diagnosis had a higher incidence of new conditions or events, including cardiovascular disease, heart failure, hypertension, obesity, dyspepsia, infections, and depression/anxiety, than patients with no OCS use. Conclusion: These results highlight the potential risks of OCS in COPD treatment, including prolonged use among complex Medicare patients, and reinforce the importance of preventive treatment strategies and therapy optimization early in the disease course.

Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD exposure may lead to HD-associated lung injuries (HDLI). However, many people who have claimed that they experienced HD exposure were not diagnosed with HDLI but still felt discomfort, possibly due to the unknown effects of HD. Therefore, this study examined HD-exposed subjects with normal-appearing lungs, as well as unexposed subjects, in clusters (subgroups) with distinct characteristics, classified by deep-learning-derived computed-tomography (CT)-based tissue pattern latent traits. Among the major clusters, cluster 0 (C0) and cluster 5 (C5) were dominated by HD-exposed and unexposed subjects, respectively. C0 was characterized by features attributable to lung inflammation or fibrosis in contrast with C5. The computational fluid and particle dynamics (CFPD) analysis suggested that the smaller airway sizes observed in the C0 subjects led to greater airway resistance and particle deposition in the airways. Accordingly, women appeared more vulnerable to HD-associated lung abnormalities than men.

Bronchodilators in Tobacco-Exposed Persons with Symptoms and Preserved Lung Function.

BACKGROUND: Many persons with a history of smoking tobacco have clinically significant respiratory symptoms despite an absence of airflow obstruction as assessed by spirometry. They are often treated with medications for chronic obstructive pulmonary disease (COPD), but supporting evidence for this treatment is lacking. METHODS: We randomly assigned persons who had a tobacco-smoking history of at least 10 pack-years, respiratory symptoms as defined by a COPD Assessment Test score of at least 10 (scores range from 0 to 40, with higher scores indicating worse symptoms), and preserved lung function on spirometry (ratio of forced expiratory volume in 1 second [FEV1] to forced vital capacity [FVC] ≥0.70 and FVC ≥70% of the predicted value after bronchodilator use) to receive either indacaterol (27.5 µg) plus glycopyrrolate (15.6 µg) or placebo twice daily for 12 weeks. The primary outcome was at least a 4-point decrease (i.e., improvement) in the St. George's Respiratory Questionnaire (SGRQ) score (scores range from 0 to 100, with higher scores indicating worse health status) after 12 weeks without treatment failure (defined as an increase in lower respiratory symptoms treated with a long-acting inhaled bronchodilator, glucocorticoid, or antibiotic agent). RESULTS: A total of 535 participants underwent randomization. In the modified intention-to-treat population (471 participants), 128 of 227 participants (56.4%) in the treatment group and 144 of 244 (59.0%) in the placebo group had at least a 4-point decrease in the SGRQ score (difference, -2.6 percentage points; 95% confidence interval [CI], -11.6 to 6.3; adjusted odds ratio, 0.91; 95% CI, 0.60 to 1.37; P = 0.65). The mean change in the percent of predicted FEV1 was 2.48 percentage points (95% CI, 1.49 to 3.47) in the treatment group and -0.09 percentage points (95% CI, -1.06 to 0.89) in the placebo group, and the mean change in the inspiratory capacity was 0.12 liters (95% CI, 0.07 to 0.18) in the treatment group and 0.02 liters (95% CI, -0.03 to 0.08) in the placebo group. Four serious adverse events occurred in the treatment group, and 11 occurred in the placebo group; none were deemed potentially related to the treatment or placebo. CONCLUSIONS: Inhaled dual bronchodilator therapy did not decrease respiratory symptoms in symptomatic, tobacco-exposed persons with preserved lung function as assessed by spirometry. (Funded by the National Heart, Lung, and Blood Institute and others; RETHINC ClinicalTrials.gov number, NCT02867761.).

E-cigarette or vaping product use-associated lung injury: A review of clinico-radio-pathological characteristics.

Aggressive, albeit false marketing of electronic nicotine delivery systems (ENDS) or vaping devices as safer alternatives to cigarette smoking, combined with lack of regulations, has led to its mass adoption, especially among youth. A sudden increase in acute lung injuries was noted in 2019 which was linked to ENDS. It was termed by the Centers for Disease Control and Prevention (CDC) as electronic cigarette or vaping product use-associated lung injury (EVALI). Analysis of bronchoalveolar lavage fluid samples linked EVALI to vitamin E acetate (VEA), which is used as a diluting agent for marijuana oils. Patients with EVALI present with a combination of non-specific respiratory, gastrointestinal, and systemic symptoms. Laboratory results may show elevated inflammatory biomarkers. EVALI is a diagnosis of exclusion and must meet the following criteria: i) history of vaping within last 90 days, ii) abnormal chest imaging, iii) negative evaluation for infection, and iv) no other plausible diagnosis. A spectrum of computed tomography (CT) chest findings has been reported in EVALI, ranging from diffuse alveolar damage to organizing pneumonia, characterized by bilateral ground-glass opacities, consolidation, and septal thickening. A similar spectrum is seen on histopathology, characterized by lipid-laden alveolar macrophages, with varying degrees of infiltrative inflammatory cells and fibrin deposition. Early and accurate identification of the EVALI pattern can help optimize patient care. For example, in diffuse alveolar damage (DAD), a lower threshold for ventilation support and corticosteroid may improve outcomes. Here, we review the etiopathogenesis, clinical management, histopathology, and imaging features of EVALI.

Increased mortality associated with frequent exacerbations in COPD patients with mild-to-moderate lung function impairment, and smokers with normal spirometry.

Background: The burden of frequent respiratory exacerbations in COPD patients with mild-to-moderate spirometric impairment and smokers with preserved lung function is unknown. Methods: We categorized COPD participants in COPDGene with post-bronchodilator FEV1%predicted≥50% by the annual exacerbation frequency into three groups: i)frequent exacerbators (top 5%; n = 109), ii)exacerbators (>0 but less than frequent exacerbators; n = 1,009), and iii)No exacerbation (n = 981). Exacerbations were defined as respiratory episodes requiring antibiotics and/or systemic steroids. We performed a Cox proportional hazards regression analysis to examine the association with mortality. We repeated the same process in current/former smokers with preserved spirometry (FEV1≥80%predicted and FEV1/FVC≥0.7). Results: Among 2,099 COPD participants, frequent exacerbators had ≥1.8 exacerbations/year and were responsible for 34.3% of the total exacerbations. There were 102 (10.4%) deaths in the group with no exacerbations, 119 (11.8%) in the exacerbator group, and 24 (22%) in the frequent exacerbators. Adjusted mortality in frequent exacerbators was higher relative to individuals with no exacerbations (hazard ratio (HR) = 1.98; 95%CI = 1.25-3.13). An increase in frequency of exacerbations by one exacerbation/year was associated with increased mortality (HR = 1.40,95%CI = 1.21-1.62). Among 3,143 participants with preserved spirometry, frequent exacerbators had ≥0.8 exacerbations/year and were responsible for more than half of the exacerbations. There were 93 (4.2%) deaths in the group with no exacerbations, 28 (3.8%) in the exacerbator group, and 14 (7.6%) in the frequent exacerbators. The adjusted mortality was increased in frequent exacerbators with preserved spirometry relative to those with no exacerbations (HR = 2.25; 95%CI = 1.26-4.01). Conclusions: In COPD participants with mild-to-moderate spirometric impairment and smokers with preserved spirometry, the frequent exacerbator phenotype is responsible for a large proportion of total exacerbations and associated with high mortality.

A computed tomography imaging-based subject-specific whole-lung deposition model.

The respiratory tract is an important route for beneficial drug aerosol or harmful particulate matter to enter the body. To assess the therapeutic response or disease risk, whole-lung deposition models have been developed, but were limited by compartment, symmetry or stochastic approaches. In this work, we proposed an imaging-based subject-specific whole-lung deposition model. The geometries of airways and lobes were segmented from computed tomography (CT) lung images at total lung capacity (TLC), and the regional air-volume changes were calculated by registering CT images at TLC and functional residual capacity (FRC). The geometries were used to create the structure of entire subject-specific conducting airways and acinar units. The air-volume changes were used to estimate the function of subject-specific ventilation distributions among acinar units and regulate flow rates in respiratory airway models. With the airway dimensions rescaled to a desired lung volume and the airflow field simulated by a computational fluid dynamics model, particle deposition fractions were calculated using deposition probability formulae adjusted with an enhancement factor to account for the effects of secondary flow and airway geometry in proximal airways. The proposed model was validated in silico against existing whole-lung deposition models, three-dimensional (3D) computational fluid and particle dynamics (CFPD) for an acinar unit, and 3D CFPD deep lung model comprising conducting and respiratory regions. The model was further validated in vivo against the lobar particle distribution and the coefficient of variation of particle distribution obtained from CT and single-photon emission computed tomography (SPECT) images, showing good agreement. Subject-specific airway structure increased the deposition fraction of 10.0-µm particles and 0.01-µm particles by approximately 10%. An enhancement factor increased the overall deposition fractions, especially for particle sizes between 0.1 and 1.0 µm.

Vitamin D-mediated effects on airway innate immunity in vitro.

INTRODUCTION: Vitamin D supplementation has been suggested to enhance immunity during respiratory infection season. We tested the effect of active vitamin D (calcitriol) supplementation on key airway innate immune mechanisms in vitro. METHODS: Primary human airway epithelial cells (hAECs) grown at the air liquid interface were supplemented with 10-7 M calcitriol for 24 hours (or a time course) and their antimicrobial airway surface liquid (ASL) was tested for pH, viscoscity, and antibacterial and antiviral properties. We also tested hAEC ciliary beat frequency (CBF). Next, we assessed alterations to hAEC gene expression using RNA sequencing, and based on results, we measured neutrophil migration across hAECs. RESULTS: Calcitriol supplementation enhanced ASL bacterial killing of Staphylococcus aureus (p = 0.02) but did not enhance its antiviral activity against 229E-CoV. It had no effect on ASL pH or viscosity at three timepoints. Lastly, it did not affect hAEC CBF or neutrophil migration, although there was a trend of enhanced migration in the presence of a neutrophil chemokine (p = 0.09). Supplementation significantly altered hAEC gene expression, primarily of AMP-related genes including CAMP and TREM1. CONCLUSION: While vitamin D supplementation did not have effects on many airway innate immune mechanisms, it may provide a useful tool to resolve respiratory bacterial infections.