Air Pollution Exposure and Interstitial Lung Features in SPIROMICS Participants with COPD.

RATIONALE: It is unknown whether air pollution is associated with radiographic features of interstitial lung disease in individuals with chronic obstructive pulmonary disease (COPD). OBJECTIVES: To determine whether air pollution increases prevalence of interstitial lung abnormalities (ILA) or percent high-attenuation area (HAA) on computed tomography (CT) in individuals with a heavy smoking history and COPD. METHODS: We performed a cross-sectional study of SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), focused on current or former smokers with COPD. 10-year exposure to particulate matter < 2.5 µm (PM2.5), nitrogen oxides (NOx), nitrogen dioxide (NO2), and ozone (O3) prior to enrollment CTs (completed between 2010-2015) were estimated with validated spatiotemporal models at residential addresses. We applied adjusted multivariable modified Poisson regression and linear regression to investigate associations between pollution exposure and relative risk of ILA or increased percent HAA (between -600 and -250 Hounsfield units) respectively. We assessed for effect modification by MUC5B-promoter polymorphism (GT/TT vs GG at rs3705950), smoking status, sex, and percent emphysema. RESULTS: Among 1272 participants with COPD assessed for HAA, 424 were current smokers, 249 were carriers of the variant MUC5B allele (GT/TT). 519 participants were assessed for ILA. We found no association between pollution exposure and ILA or HAA. Associations between pollutant exposures and risk of ILA were modified by the presence of MUC5B polymorphism (p-value interaction term for NOx = 0.04 and PM2.5 = 0.05) and smoking status (p-value interaction term for NOx = 0.05, NO2 = 0.01, and O3 = 0.05). With higher exposure to NOx and PM2.5, MUC5B variant carriers had increased risk of ILA (Relative Risk [RR] per 26ppb NOx 2.41; 95% Confidence Interval [CI] 0.97 to 6.0) and RR per 4 µg·m-3 PM2.5 1.43; 95% CI 0.93 to 2.2). With higher exposure to NO2, former smokers had increased risk of ILA (RR per 10ppb 1.64; 95% CI 1.0 to 2.7). CONCLUSIONS: Exposure to ambient air pollution was not associated with interstitial features on CT in this population of heavy smokers with COPD. MUC5B modified the association between pollution and ILA, suggesting that gene-environment interactions may influence prevalence of interstitial lung features in COPD.

Genetics and Genomics of Pulmonary Fibrosis: Charting the Molecular Landscape and Shaping Precision Medicine.

Recent genetic and genomic advancements have elucidated the complex etiology of idiopathic pulmonary fibrosis (IPF) and other progressive fibrotic interstitial lung diseases (ILDs), emphasizing the contribution of heritable factors. This state-of-the-art review synthesizes evidence on significant genetic contributors to pulmonary fibrosis (PF), including rare genetic variants and common single nucleotide polymorphisms (SNPs). The MUC5B promoter variant is unusual, a common SNP that markedly elevates the risk of early and established PF. We address the utility of genetic variation in enhancing understanding of disease pathogenesis, clinical phenotypes, improving disease definitions, and informing prognosis and treatment response. Critical research gaps are highlighted, particularly the underrepresentation of non-European ancestries in PF genetic studies and the exploration of PF phenotypes beyond usual interstitial pneumonia (UIP)/IPF. We discuss the role of telomere length, often critically short in PF, and its link to progression and mortality, underscoring the genetic complexity involving telomere biology genes (TERT, TERC) and others like SFTPC and MUC5B. Additionally, we address the potential of gene-by-environment interactions to modulate disease manifestation, advocating for precision medicine in PF. Insights from gene expression profiling studies and multi-omic analyses highlight the promise for understanding disease pathogenesis and offer new approaches to clinical care, therapeutic drug development, and biomarker discovery. Finally, we discuss the ethical, legal, and social implications of genomic research and therapies in PF, stressing the need for sound practices and informed clinical genetic discussions. Looking forward, we advocate for comprehensive genetic testing panels and polygenic risk scores to improve the management of PF and related ILDs across diverse populations.

Design of a multiple criteria decision analysis framework for prioritizing high-impact health technologies in a regional health service.

OBJECTIVES: This study aims to develop a framework for establishing priorities in the regional health service of Murcia, Spain, to facilitate the creation of a comprehensive multiple criteria decision analysis (MCDA) framework. This framework will aid in decision-making processes related to the assessment, reimbursement, and utilization of high-impact health technologies. METHOD: Based on the results of a review of existing frameworks for MCDA of health technologies, a set of criteria was proposed to be used in the context of evaluating high-impact health technologies. Key stakeholders within regional healthcare services, including clinical leaders and management personnel, participated in a focus group (n = 11) to discuss the proposed criteria and select the final fifteen. To elicit the weights of the criteria, two surveys were administered, one to a small sample of healthcare professionals (n = 35) and another to a larger representative sample of the general population (n = 494). RESULTS: The responses obtained from health professionals in the weighting procedure exhibited greater consistency compared to those provided by the general public. The criteria more highly weighted were "Need for intervention" and "Intervention outcomes." The weights finally assigned to each item in the multicriteria framework were derived as the equal-weighted sum of the mean weights from the two samples. CONCLUSIONS: A multi-attribute function capable of generating a composite measure (multicriteria) to assess the value of high-impact health interventions has been developed. Furthermore, it is recommended to pilot this procedure in a specific decision context to evaluate the efficacy, feasibility, usefulness, and reliability of the proposed tool.

Computational Deconvolution of Cell Type-Specific Gene Expression in COPD and IPF Lungs Reveals Disease Severity Associations.

RATIONALE: Chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are debilitating diseases associated with divergent histopathological changes in the lungs. At present, due to cost and technical limitations, profiling cell types is not practical in large epidemiology cohorts (n>1000). Here, we used computational deconvolution to identify cell types in COPD and IPF lungs whose abundances and cell type-specific gene expression are associated with disease diagnosis and severity. METHODS: We analyzed lung tissue RNA-seq data from 1026 subjects (COPD, n=465; IPF, n=213; control, n=348) from the Lung Tissue Research Consortium. We performed RNA-seq deconvolution, querying thirty-eight discrete cell-type varieties in the lungs. We tested whether deconvoluted cell-type abundance and cell type-specific gene expression were associated with disease severity. RESULTS: The abundance score of twenty cell types significantly differed between IPF and control lungs. In IPF subjects, eleven and nine cell types were significantly associated with forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLCO), respectively. Aberrant basaloid cells, a rare cells found in fibrotic lungs, were associated with worse FVC and DLCO in IPF subjects, indicating that this aberrant epithelial population increased with disease severity. Alveolar type 1 and vascular endothelial (VE) capillary A were decreased in COPD lungs compared to controls. An increase in macrophages and classical monocytes was associated with lower DLCO in IPF and COPD subjects. In both diseases, lower non-classical monocytes and VE capillary A cells were associated with increased disease severity. Alveolar type 2 cells and alveolar macrophages had the highest number of genes with cell type-specific differential expression by disease severity in COPD and IPF. In IPF, genes implicated in the pathogenesis of IPF, such as matrix metallopeptidase 7, growth differentiation factor 15, and eph receptor B2, were associated with disease severity in a cell type-specific manner. CONCLUSION: Utilization of RNA-seq deconvolution enabled us to pinpoint cell types present in the lungs that are associated with the severity of COPD and IPF. This knowledge offers valuable insight into the alterations within tissues in more advanced illness, ultimately providing a better understanding of the underlying pathological processes that drive disease progression.

CO and O2 Interaction with Kinked Pt Surfaces.

We investigate the chemical interaction of carbon monoxide (CO) and oxygen (O2) with kink atoms on steps of platinum crystal surfaces using a specially designed Pt curved sample. We aim at describing the fundamental stages of the CO oxidation reaction, i.e., CO-covered/poisoned stage and O-covered/active stage, at the poorly known kinked Pt facets by probing CO uptake/saturation and O2 saturation, respectively. Based on the systematic analysis that the curved surface allows, and using high-resolution X-ray photoemission, a diversity of terrace and step/kink species are straightforwardly identified and accurately quantified, defining a smooth structural and chemical variation across different crystal planes. In the CO-saturated case, we observe a preferential adsorption at step edges, where the CO coverage reaches a CO molecule per step Pt atom, significantly higher than their close-packed analogous steps with straight terrace termination. For the O-saturated surface, a significantly higher O coverage is observed in kinked planes compared to the Pt(111) surface. While the strong adsorption of CO at the kinked edges points toward a higher ignition temperature of the CO oxidation at kinks as compared to terraces, the large O coverage at steps may lead to an increased reactivity of kinked surfaces during the active stage of the CO oxidation.

The IRE1α-XBP1 arm of the unfolded protein response is a host factor activated in SARS-CoV-2 infection.

SARS-CoV-2 infection can cause severe pneumonia, wherein exacerbated inflammation plays a major role. This is reminiscent of the process commonly termed cytokine storm, a condition dependent on a disproportionated production of cytokines. This state involves the activation of the innate immune response by viral patterns and coincides with the biosynthesis of the biomass required for viral replication, which may overwhelm the capacity of the endoplasmic reticulum and drive the unfolded protein response (UPR). The UPR is a signal transduction pathway composed of three branches that is initiated by a set of sensors: inositol-requiring protein 1 (IRE1), protein kinase RNA-like ER kinase (PERK), and activating transcription factor 6 (ATF6). These sensors control adaptive processes, including the transcriptional regulation of proinflammatory cytokines. Based on this background, the role of the UPR in SARS-CoV-2 replication and the ensuing inflammatory response was investigated using in vivo and in vitro models of infection. Mice and Syrian hamsters infected with SARS-CoV-2 showed a sole activation of the Ire1α-Xbp1 arm of the UPR associated with a robust production of proinflammatory cytokines. Human lung epithelial cells showed the dependence of viral replication on the expression of UPR-target proteins branching on the IRE1α-XBP1 arm and to a lower extent on the PERK route. Likewise, activation of the IRE1α-XBP1 branch by Spike (S) proteins from different variants of concern was a uniform finding. These results show that the IRE1α-XBP1 system enhances viral replication and cytokine expression and may represent a potential therapeutic target in SARS-CoV-2 severe pneumonia.

Vessel and Airway Characteristics in One-Year CT-defined Rapid Emphysema Progression: SPIROMICS.

Rationale: Rates of emphysema progression vary in chronic obstructive pulmonary disease (COPD), and the relationship with vascular and airway pathophysiology remain unclear. Objective: We sought to determine if indices of peripheral (segmental and beyond) pulmonary arterial (PA) dilation measured via computed tomography (CT) are associated with a 1-year index of emphysema (EI: %voxels<-950HU) progression. Methods: 599 GOLD 0-3 former and never-smokers were evaluated from the SubPopulations and InterMediate Outcome Measures in COPD Study (SPIROMICS) cohort: rapid-emphysema-progressors (RP, n=188; 1-year ΔEI>1%), non-progressors (NP, n=301; 1-year ΔEI±0.5%) and never-smokers (NS: N=110). Segmental PA cross-sectional areas were standardized to associated airway luminal areas (Segmental : Pulmonary Artery-to-Airway Ratio: PAARseg). Full inspiratory CT scan-derived total (arteries + veins) pulmonary vascular volume (TPVV) was compared to vessel volume with radius smaller than 0.75mm (SVV.75/TPVV). Airway-to-lung ratios (an index of dysanapsis and COPD risk) were compared to TPVV-lung-volume-ratios. Results: Compared with NP, RP exhibited significantly larger PAARseg (0.73±0.29 vs. 0.67±0.23; p=0.001), lower TPVV-to-lung-volume ratio (3.21%±0.42% vs. 3.48%±0.38%; p=5.0 x 10-12), lower airway-to-lung-volume ratio (0.031±0.003 vs. 0.034±0.004; p=6.1 x 10-13) and larger SVV.75/TPVV (37.91%±4.26% vs. 35.53±4.89; p=1.9 x 10-7). In adjusted analyses, a 1-SD increment in PAARseg was associated with a 98.4% higher rate of severe exacerbations (95%CI: 29 to 206%; p = 0.002) and 79.3% higher in odds of being in the rapid emphysema progression group (95%CI: 24% to 157%; p = 0.001). At year-2 followup, the CT-defined RP group demonstrated a significant decline in post-bronchodilator-FEV1% predicted. Conclusion: Rapid one-year progression of emphysema was associated with indices indicative of higher peripheral pulmonary vascular resistance and a possible role played by pulmonary vascular-airway dysanapsis.

The Effect of Chronic Altitude Exposure on COPD Outcomes in the SPIROMICS Cohort.

RATIONALE: Individuals with COPD have airflow obstruction and maldistribution of ventilation. For those living at high altitude, any gas exchange abnormality is compounded by reduced partial pressures of inspired oxygen. OBJECTIVES: Does residence at higher-altitude exposure affect COPD outcomes, including lung function, imaging characteristics, symptoms, health status, functional exercise capacity, exacerbations, or mortality? METHODS: From the SPIROMICS cohort, we identified individuals with COPD living below 1,000 ft (305 m) elevation (n= 1,367) versus above 4,000 ft (1,219 m) elevation (n= 288). Multivariable regression models were used to evaluate associations of exposure to high altitude with COPD-related outcomes. MEASUREMENTS AND MAIN RESULTS: Living at higher altitude was associated with reduced functional exercise capacity as defined by 6MWD (-32.3 m, (-55.7 to -28.6)). There were no differences in patient-reported outcomes as defined by symptoms (CAT, mMRC), or health status (SGRQ). Higher altitude was not associated with a different rate of FEV1 decline. Higher altitude was associated with lower odds of severe exacerbations (IRR 0.65, (0.46 to 0.90)). There were no differences in small airway disease, air trapping, or emphysema. In longitudinal analyses, higher altitude was associated with increased mortality (HR 1.25, (1.0 to 1.55)); however, this association was no longer significant when accounting for air pollution. CONCLUSIONS: Chronic altitude exposure is associated with reduced functional exercise capacity in individuals with COPD, but this did not translate into differences in symptoms or health status. Additionally, chronic high-altitude exposure did not affect progression of disease as defined by longitudinal changes in spirometry.

Lung-function trajectories: relevance and implementation in clinical practice.

Lung development starts in utero and continues during childhood through to adolescence, reaching its peak in early adulthood. This growth is followed by gradual decline due to physiological lung ageing. Lung-function development can be altered by several host and environmental factors during the life course. As a result, a range of lung-function trajectories exist in the population. Below average trajectories are associated with respiratory, cardiovascular, metabolic, and mental health comorbidities, as well as with premature death. This Review presents progressive research into lung-function trajectories and assists the implementation of this knowledge in clinical practice as an innovative approach to detect poor lung health early, monitor respiratory disease progression, and promote lung health. Specifically, we propose that, similar to paediatric height and weight charts used globally to monitor children's growth, lung-function charts could be used for both children and adults to monitor lung health status across the life course. To achieve this proposal, we introduce our free online Lung Function Tracker tool. Finally, we discuss challenges and opportunities for effective implementation of the trajectory concept at population level and outline an agenda for crucial research needed to support such implementation.

A multidimensional classifier to support lung transplant referral in patients with pulmonary fibrosis.

BACKGROUND: Lung transplantation remains the sole curative option for patients with idiopathic pulmonary fibrosis (IPF), but donor organs remain scarce, and many eligible patients die before transplant. Tools to optimize the timing of transplant referrals are urgently needed. METHODS: Least absolute shrinkage and selection operator was applied to clinical and proteomic data generated as part of a prospective cohort study of interstitial lung disease (ILD) to derive clinical, proteomic, and multidimensional logit models of near-term death or lung transplant within 18 months of blood draw. Model-fitted values were dichotomized at the point of maximal sensitivity and specificity, and decision curve analysis was used to select the best-performing classifier. We then applied this classifier to independent IPF and non-IPF ILD cohorts to determine test performance characteristics. Cohorts were restricted to patients aged ≤72 years with body mass index 18 to 32 to increase the likelihood of transplant eligibility. RESULTS: IPF derivation, IPF validation, and non-IPF ILD validation cohorts consisted of 314, 105, and 295 patients, respectively. A multidimensional model comprising 2 clinical variables and 20 proteins outperformed stand-alone clinical and proteomic models. Following dichotomization, the multidimensional classifier predicted near-term outcome with 70% sensitivity and 92% specificity in the IPF validation cohort and 70% sensitivity and 80% specificity in the non-IPF ILD validation cohort. CONCLUSIONS: A multidimensional classifier of near-term outcomes accurately discriminated this end-point with good test performance across independent IPF and non-IPF ILD cohorts. These findings support refinement and prospective validation of this classifier in transplant-eligible individuals.

Adaptive multi-interventional trial platform to improve patient care for fibrotic interstitial lung diseases.

BACKGROUND: Fibrotic interstitial lung diseases (fILDs) are a heterogeneous group of lung diseases associated with significant morbidity and mortality. Despite a large increase in the number of clinical trials in the last 10 years, current regulatory-approved management approaches are limited to two therapies that prevent the progression of fibrosis. The drug development pipeline is long and there is an urgent need to accelerate this process. This manuscript introduces the concept and design of an innovative research approach to drug development in fILD: a global Randomised Embedded Multifactorial Adaptive Platform in fILD (REMAP-ILD). METHODS: Description of the REMAP-ILD concept and design: the specific terminology, design characteristics (multifactorial, adaptive features, statistical approach), target population, interventions, outcomes, mission and values, and organisational structure. RESULTS: The target population will be adult patients with fILD, and the primary outcome will be a disease progression model incorporating forced vital capacity and mortality over 12 months. Responsive adaptive randomisation, prespecified thresholds for success and futility will be used to assess the effectiveness and safety of interventions. REMAP-ILD embraces the core values of diversity, equity, and inclusion for patients and researchers, and prioritises an open-science approach to data sharing and dissemination of results. CONCLUSION: By using an innovative and efficient adaptive multi-interventional trial platform design, we aim to accelerate and improve care for patients with fILD. Through worldwide collaboration, novel analytical methodology and pragmatic trial delivery, REMAP-ILD aims to overcome major limitations associated with conventional randomised controlled trial approaches to rapidly improve the care of people living with fILD.

Early-Life Exposure to Air Pollution and Childhood Asthma Cumulative Incidence in the ECHO CREW Consortium.

Importance: Exposure to outdoor air pollution contributes to childhood asthma development, but many studies lack the geographic, racial and ethnic, and socioeconomic diversity to evaluate susceptibility by individual-level and community-level contextual factors. Objective: To examine early life exposure to fine particulate matter (PM2.5) and nitrogen oxide (NO2) air pollution and asthma risk by early and middle childhood, and whether individual and community-level characteristics modify associations between air pollution exposure and asthma. Design, Setting, and Participants: This cohort study included children enrolled in cohorts participating in the Children's Respiratory and Environmental Workgroup consortium. The birth cohorts were located throughout the US, recruited between 1987 and 2007, and followed up through age 11 years. The survival analysis was adjusted for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, neighborhood characteristics, and cohort. Statistical analysis was performed from February 2022 to December 2023. Exposure: Early-life exposures to PM2.5 and NO2 according to participants' birth address. Main Outcomes and Measures: Caregiver report of physician-diagnosed asthma through early (age 4 years) and middle (age 11 years) childhood. Results: Among 5279 children included, 1659 (31.4%) were Black, 835 (15.8%) were Hispanic, 2555 (48.4%) where White, and 229 (4.3%) were other race or ethnicity; 2721 (51.5%) were male and 2596 (49.2%) were female; 1305 children (24.7%) had asthma by 11 years of age and 954 (18.1%) had asthma by 4 years of age. Mean values of pollutants over the first 3 years of life were associated with asthma incidence. A 1 IQR increase in NO2 (6.1 µg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.25 [95% CI, 1.03-1.52]) and children younger than 11 years (HR, 1.22 [95% CI, 1.04-1.44]). A 1 IQR increase in PM2.5 (3.4 µg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.31 [95% CI, 1.04-1.66]) and children younger than 11 years (OR, 1.23 [95% CI, 1.01-1.50]). Associations of PM2.5 or NO2 with asthma were increased when mothers had less than a high school diploma, among Black children, in communities with fewer child opportunities, and in census tracts with higher percentage Black population and population density; for example, there was a significantly higher association between PM2.5 and asthma incidence by younger than 5 years of age in Black children (HR, 1.60 [95% CI, 1.15-2.22]) compared with White children (HR, 1.17 [95% CI, 0.90-1.52]). Conclusions and Relevance: In this cohort study, early life air pollution was associated with increased asthma incidence by early and middle childhood, with higher risk among minoritized families living in urban communities characterized by fewer opportunities and resources and multiple environmental coexposures. Reducing asthma risk in the US requires air pollution regulation and reduction combined with greater environmental, educational, and health equity at the community level.

Factors Contributing to Negative Outcomes Associated with Medications and Drug-Related Problems in Kidney Replacement Therapy-A Hospital-Based Prospective Observational Study.

BACKGROUND: Negative outcomes associated with medications (NOM) and drug-related problems (DRP) significantly impact individuals with kidney replacement therapy (KRT) given the complexities of managing kidney disease and associated comorbidities. The present study aims to assess the frequency of NOMs/DRPs among KRT patients and identify contributing factors. METHODS: A cross-sectional study was conducted at Virgen de las Nieves University Hospital (Granada, Spain), involving 117 outpatient adults with KRT. Data were collected from February 2021 to July 2023 using electronic records, semi-structured interviews (Dáder Method), and discussions with nephrology specialists. NOMs/DRPs were identified following treatment guidelines. Binary logistic regression was used to determine associated factors (p-value < 0.05). RESULTS: Across 117 patients, 2436 NOMs and 3303 DRPs were identified, averaging 20.82 NOMs and 28.23 DRPs per patient. Prevalent NOMs included untreated conditions (58.95%), quantitative ineffectiveness (35.43%), and non-quantitative safety problems (5.13%). Dominant DRPs were undertreated conditions (37.63%), wrong dose/posology/length (33.00%), risk of adverse drug reactions (ADR) (16.14%), and non-adherence (6.87%). Patients with ADR, undertreated conditions, and anemia were associated with quantitative ineffectiveness. Risk of ADR and vitamin D deficiency/insufficiency correlated with non-quantitative safety problems. CONCLUSIONS: KRT patients exhibited a substantial prevalence of NOMs/DRPs. Further research is needed to deepen our understanding of these complexities for improved patient care.

Association study of human leukocyte antigen variants and idiopathic pulmonary fibrosis.

Introduction: Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial pneumonia marked by progressive lung fibrosis and a poor prognosis. Recent studies have highlighted the potential role of infection in the pathogenesis of IPF, and a prior association of the HLA-DQB1 gene with idiopathic fibrotic interstitial pneumonia (including IPF) has been reported. Owing to the important role that the human leukocyte antigen (HLA) region plays in the immune response, here we evaluated if HLA genetic variation was associated specifically with IPF risk. Methods: We performed a meta-analysis of associations of the HLA region with IPF risk in individuals of European ancestry from seven independent case-control studies of IPF (comprising 5159 cases and 27 459 controls, including a prior study of fibrotic interstitial pneumonia). Single nucleotide polymorphisms, classical HLA alleles and amino acids were analysed and signals meeting a region-wide association threshold of p<4.5×10-4 and a posterior probability of replication >90% were considered significant. We sought to replicate the previously reported HLA-DQB1 association in the subset of studies independent of the original report. Results: The meta-analysis of all seven studies identified four significant independent single nucleotide polymorphisms associated with IPF risk. However, none met the posterior probability for replication criterion. The HLA-DQB1 association was not replicated in the independent IPF studies. Conclusion: Variation in the HLA region was not consistently associated with risk in studies of IPF. However, this does not preclude the possibility that other genomic regions linked to the immune response may be involved in the aetiology of IPF.

Local heterogeneity of normal lung parenchyma and small airways disease are associated with COPD severity and progression.

BACKGROUND: Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline. METHODS: PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n = 8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model. RESULTS: Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (ß of 0.106, p < 0.001) and VfSAD (ß of 0.065, p = 0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69. CONCLUSIONS: We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

Mapping the concept of health care integration: A lexicographic analysis of scientific literature.

BACKGROUND: Systems fragmentation is a major challenge for an efficient organization, integration being a potential solution also proposed in health care field, including pharmacy as a player. However, the use of different terms and definitions in the literature hinders the comparison of different integration initiatives. OBJECTIVE: To identify and map the terms used in scientific literature regarding integration in health care and to characterize each emerging topic. METHODS: A lexicographic analysis of the integration of healthcare systems literature indexed in PubMed was conducted. Ten different systematic searches, four using only Medical Subject Headings (MeSH) and six using text words, were conducted in March 2023. Journal scattering was analyzed following Bradford's distribution using the Leimkuhler model. An overall text corpus was created with titles and abstracts of all the records retrieved. The corpus was lemmatized, and the most used bigrams were tokenized as single strings. To perform a topic modeling, the lemmatized corpus text was analyzed using IRaMuTeQ, producing descending hierarchic classification and a correspondence analysis. The 50 words with higher chi-square statistics in each class were considered as representative of the class. RESULTS: A total of 42,479 articles published from 1943 to 2023 in 4469 different journals were retrieved. The MeSH "Delivery of Health Care, Integrated", created in the 1996 MeSH update, was the most productive retrieving 33.7 % of the total articles but also retrieving 22.6 % of articles not retrieved in any other search. The text word "Integration" appeared in 15,357 (36.2 %) records. The lexicographic analysis resulted in 7 classes, named as: Evidence and implementation, Quantitative research, Professional education, Qualitative research, Governance and leadership, Clinical research, and Financial resources. Association between the classes and the searches or the text-words used ranged from moderate to weak demonstrating the lack of a standard pattern of use of terms in literature regarding healthcare integration. CONCLUSIONS: The term "integration" and the MeSH "Delivery of Health Care, Integrated" are the most used to represent the concept of integration in healthcare and should be the preferred terms in the literature.

Machine Learning of Plasma Proteomics Classifies Diagnosis of Interstitial Lung Disease.

RATIONALE: Distinguishing connective tissue disease associated interstitial lung disease (CTD-ILD) from idiopathic pulmonary fibrosis (IPF) can be clinically challenging. OBJECTIVES: Identify proteins that separate and classify CTD-ILD from IPF patients. METHODS: Four registries with 1247 IPF and 352 CTD-ILD patients were included in analyses. Plasma samples were subjected to high-throughput proteomics assays. Protein features were prioritized using Recursive Feature Elimination (RFE) to construct a proteomic classifier. Multiple machine learning models, including Support Vector Machine, LASSO regression, Random Forest (RF), and imbalanced-RF, were trained and tested in independent cohorts. The validated models were used to classify each case iteratively in external datasets. MEASUREMENT AND MAIN RESULTS: A classifier with 37 proteins (PC37) was enriched in biological process of bronchiole development and smooth muscle proliferation, and immune responses. Four machine learning models used PC37 with sex and age score to generate continuous classification values. Receiver-operating-characteristic curve analyses of these scores demonstrated consistent Area-Under-Curve 0.85-0.90 in test cohort, and 0.94-0.96 in the single-sample dataset. Binary classification demonstrated 78.6%-80.4% sensitivity and 76%-84.4% specificity in test cohort, 93.5%-96.1% sensitivity and 69.5%-77.6% specificity in single-sample classification dataset. Composite analysis of all machine learning models confirmed 78.2% (194/248) accuracy in test cohort and 82.9% (208/251) in single-sample classification dataset. CONCLUSIONS: Multiple machine learning models trained with large cohort proteomic datasets consistently distinguished CTD-ILD from IPF. Identified proteins involved in immune pathways. We further developed a novel approach for single sample classification, which could facilitate honing the differential diagnosis of ILD in challenging cases and improve clinical decision-making.

RoBétArmé Project: Human-robot collaborative construction system for shotcrete digitization and automation through advanced perception, cognition, mobility and additive manufacturing skills.

The importance of construction automation has grown worldwide, aiming to deliver new machineries for the automation of roads, tunnels, bridges, buildings and earth-work construction. This need is mainly driven by (i) the shortage and rising costs of skilled workers, (ii) the tremendous increased needs for new infrastructures to serve the daily activities and (iii) the immense demand for maintenance of ageing infrastructure. Shotcrete (sprayed concrete) is increasingly becoming popular technology among contractors and builders, as its application is extremely economical and flexible as the growth in construction repairs in developed countries demand excessive automation of concrete placement. Even if shotcrete technology is heavily mechanized, the actual application is still performed manually at a large extend. RoBétArméEuropean project targets the Construction 4.0 transformation of the construction with shotcrete with the adoption of breakthrough technologies such as sensors, augmented reality systems, high-performance computing, additive manufacturing, advanced materials, autonomous robots and simulation systems, technologies that have already been studied and applied so far in Industry 4.0. The paper at hand showcases the development of a novel robotic system with advanced perception, cognition and digitization capabilities for the automation of all phases of shotcrete application. In particular, the challenges and barriers in shotcrete automation are presented and the RoBétArmésuggested solutions are outlined. We introduce a basic conceptual architecture of the system to be developed and we demonstrate the four application scenarios on which the system is designated to operate.

The RoBétArmé European project targets the Construction 4.0 transformation of the construction with shotcrete with the adoption of breakthrough technologies such as sensors, augmented reality systems, high-performance computing, additive manufacturing, advanced materials, autonomous robots and simulation systems, technologies that have already been studied and applied so far in Industry 4.0. This paper showcases a case study on which novel robotic systems will be developed for the automation of shotecrete application. The outcomes of this research can be widely used in other application technologies related to the construction domain.

A Spanish value set for the SF-6D based on the SF-12 v1.

AIM: This paper reports the first estimation of an SF-6D value set based on the SF-12 for Spain. METHODS: A representative sample (n = 1020) of the Spanish general population valued a selection of 56 hypothetical SF-6D health states by means of a probability lottery equivalent (PLE) method. The value set was derived using both random effects and mean models estimated by ordinary least squares (OLS). The best model was chosen on the basis of its predictive ability assessed in terms of mean absolute error (MAE). RESULTS: The model yielding the lowest MAE (0.075) was that based on main effects using OLS. Pain was the most significant dimension in predicting health state severity. Comparison with the previous SF-6D (SF-36) model estimated for Spain revealed no significant differences, with a similar MAE (0.081). Nevertheless, the new SF-6D (SF-12) model predicted higher utilities than those generated by the SF-6D (SF-36) scoring algorithm (minimum value - 0.071 vs - 0.357). CONCLUSION: A value set for the SF-6D (SF-12) based on Spanish general population preferences elicited by means of a PLE technique is successfully estimated. The new estimated SF-6D (SF-12) preference-based measure provides a valuable tool for researchers and policymakers to assess the cost-effectiveness of new health technologies in Spain.