Citations

Abstract IntroductionPatients with interstitial lung disease (ILD) who are admitted to the intensive care unit (ICU) face significant challenges, with high rates of morbidity and mortality. Despite the severity of outcomes in this population, the potential impact of gender disparities on ICU outcomes in ILD has not been well studied.MethodsWe analyzed data from the NIS spanning 2016 to 2018, focusing on adults (≥18 years) hospitalized with ILD (J84), and defined ICU stays using ICD codes for central line placement and mechanical ventilation. The NIS, part of the Healthcare Cost and Utilization Project, provides a weighted, nationally representative sample of U.S. hospitalizations. Demographic, clinical, and hospital characteristics were collected, with race/ethnicity categorized per NIS classifications. Multivariable logistic and linear regression models adjusted for potential confounders to evaluate gender differences in outcomes.ResultsOur study identified 810,295 adult hospitalizations with ILD, of which 42,080 required ICU-level care. Of these, 46.7% were female. Female ICU patients were younger (mean age 66.9 ± 13.8 vs. 69.1 ± 12.7, p<0.001), more likely to be African American (17.0% vs. 10.9%, p<0.001), and less likely to be Caucasian (63.7% vs. 69.2%, p<0.001). Females were more often from lower-income ZIP codes (33.2% vs. 38.3%, p<0.001) and had lower rates of tobacco use disorder (35.0% vs. 43.9%, p<0.001). Mortality was significantly lower in females (40.5% vs. 48.1%, p<0.001). After adjusting for confounders, female gender was independently associated with reduced mortality risk (adjusted odds ratio 0.77, 95% CI 0.70-0.84, p<0.001) and a shorter length of hospital stay (adjusted difference 1.15 days, 95% CI 0.54-1.77).ConclusionOur study highlights notable gender differences in outcomes for patients with ILD admitted to the ICU. Female patients had a significantly lower risk of mortality and shorter hospital stays than male patients, even after adjusting for key clinical and socioeconomic confounders. These findings are consistent with emerging evidence that biological sex and gender-related factors play a critical role in disease expression and outcomes in ILD.Several mechanisms may explain these gender disparities. Sex hormones, such as estrogen, have been shown to exert protective effects in pulmonary fibrosis models, potentially influencing the disease course in women. Incorporating these considerations into clinical practice and future research will be vital for advancing individualized, patient-centered medicine in ILD.

Abstract Rationale: Disparities in unilateral clinician decisions to decline initiating or maintaining life-sustaining treatment (LST) exist. We aimed to determine 1) which US state statutes support unilateral clinician decisions to decline initiating or maintaining LST; 2) what requirements, if any, must be met for these unilateral clinician decisions to occur; and 3) which state statutes address concerns for sociodemographic disparities associated with these decisions. Methods: Between September and October 2024, we used Fastcase, Casetext and official US state government websites to identify statutes for all US states and Washington, DC that addressed clinician decisions to decline to initiate or maintain LST. We defined reason of conscience as explicit mention of conscience, religion, ethics or moral reasons supporting unilateral clinician decision-making. Two reviewers independently analyzed each statute resolving disagreements with consensus adjudication. Results: Almost all (98%, n=50/51) statutes explicitly support unilateral clinician decisions to decline initiating or maintaining at least one form of LST. Reasons supporting these decisions varied across states including medical reasons only (16%), reasons of conscience only (22%), both medical reasons and reasons of conscience (35%), or no medical or conscience reason explicitly provided (25%). Medical reasons supporting unilateral clinician decisions included if LST was “medically ineffective” (24%), “contrary to medical standards” (14%), “medically inappropriate” (10%), or “nonbeneficial” (8%). For states supporting unilateral clinician decisions if LST was medically ineffective, 75% also supported LST to be declined for reason of conscience while 25% did not. When using medical reasons to support unilateral clinician decisions to decline LST, many statutes require that clinicians must first inform patient/surrogate of this decision (37%) and cooperate with transferring the patient to another clinician or institution (75%). Statutes rarely directly required clinicians to obtain a second medical opinion (8%), pursue a medical ethics committee review (6%), or address conflict (2%) in these situations. Although no state statutes explicitly acknowledged the existence of sociodemographic disparities associated with unilateral clinician decisions to initiate or maintain LST, 27% included guidance that addressed decisions to withhold or withdraw LST in specific marginalized groups. Conclusions: While almost all US state statutes allowed clinicians to decline to initiate or maintain LST, the reasons supporting and actions required to pursue these decisions varied. No statute explicitly addressed sociodemographic disparities associated with these decisions, which may perpetuate these disparities across the US.

Abstract Introduction: Endobronchial optical coherence tomography (EB-OCT) imaging has unique potential to diagnose and quantify early, microscopic disease changes and assess therapeutic responsivity in interstitial lung disease (ILD). However, training and time requirements for interpretation and quantitative evaluation of large volumetric EB-OCT datasets need to be optimized to facilitate clinical adoption. We develop and validate a computationally-efficient, rapid EB-OCT quantitative image analysis framework using artificial intelligence (AI) with deep learning architecture for 2D feature segmentation, 3D feature burden and spatial distribution mapping, and computer-aided diagnosis in early ILD subjects. Methods: Volumetric EB-OCT datasets, consisting of 2D cross-sectional images, were acquired from multiple locations in the bilateral lungs of ILD and healthy control subjects. EB-OCT features were manually segmented from cross-sectional images by an expert EB-OCT reader, including fibrosis, microscopic honeycombing, traction bronchiolectasis, normal parenchyma, and emphysema. EB-OCT images with corresponding feature segmentations were used to train and validate a multiclass convolutional neural network. The 2D AI-based segmentation model was subsequently evaluated against manual ‘ground truth’ segmentations for each feature in a de novo ‘test’ dataset of independent subjects using dice similarity score, precision, recall/sensitivity, specificity, and balanced accuracy. To generate 3D AI-based quantitative feature burden and spatial distribution maps, AI-based feature segmentation was performed on each EB-OCT 2D cross-sectional image within a volumetric imaging site. Three external pathologist readers independently interpreted 3D AI-based features maps for each EB-OCT imaging site acquired for a subject (without access to EB-OCT images) and provided a single diagnosis of usual interstitial pneumonia (UIP) or non-UIP ILD. Performance of computer-aided ILD diagnosis was compared against independently evaluated histopathology, clinical diagnosis, and prior EB-OCT image interpretation. Results: EB-OCT was acquired in 51 subjects: 30 in vivo early ILD, 5 in vivo non-ILD controls, and 16 ex vivo end-stage ILD. Overall pixel similarity between 2D manual and AI-based segmentation demonstrated high accuracy for each ILD feature (mean balanced accuracy 0.9). 3D quantitative AI-based feature maps demonstrated strong agreement (Spearman ρ0.87, p<0.001) between manual and AI-based segmentation. AI-based computer-aided diagnosis demonstrated 100% sensitivity/specificity for histologic UIP and clinical IPF for all pathologist readers, with improved diagnostic accuracy and significantly reduced training (45-minute training, 75% reduction) and interpretation time (<1 minute per subject for computer-aided diagnosis, 88% reduction) compared to EB-OCT image interpretation. Conclusion: The AI-based EB-OCT image analysis framework could expedite computer-aided diagnosis of early ILD and robust, quantitative assessment of microscopic disease burden, progression, and therapeutic responsivity.

Abstract RATIONALE: Pulmonary fibrosis is recognized as the end result of multiple and recurrent pathways of lung injury. However, the role of chronic inflammation in non-idiopathic pulmonary fibrosis fibrotic interstitial lung disease (non-IPF f-ILD) remains inconclusive, as acute responses to anti-inflammatory treatment may vary. A reliable predictor for identifying patients who stand to benefit from treatment may be helpful for improving or sustaining lung function and avoiding adverse treatment effects. Our study aims to assess whether initial serum inflammatory markers, C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR), in the absence of clinically suspected infection or other causes of inflammation, are predictive of therapeutic response to anti-inflammatory medications in non-IPF f-ILD. METHODS: We performed a retrospective study comparing treatment response to anti-inflammatory therapy in non-IPF f-ILD stratified by initial CRP or ESR levels. Treatment was defined as corticosteroid or steroid-sparing agent for three months or more with lung function response defined as: 1) relative increase in percent predicted forced vital capacity (FVC%) > 5% in 6 months or > 10% or greater in 12 months; or 2) no change or any increase in FVC% if FVC% was declining prior to treatment initiation (relative decline in FVC% > 5% in the prior 6 months or > 10% in the prior 12 months). Logistic regression was used to predict treatment response as stratified by high vs low-to-normal inflammatory markers, with a mixed model for repeated measures for comparing FVC% change while treated. RESULTS: One hundred sixty-seven non-IPF f-ILD pts received anti-inflammatory therapy with baseline inflammatory markers stratified by high (N = 104) vs low-to-normal (N = 63) prior to treatment. Median age was 64 years with systemic rheumatic disease diagnosed in 58%. Treatment response was higher in patients with elevated inflammatory markers (55.77% vs. 34.92%, P = 0.011), even after adjustment for age, sex, baseline FVC%, and treatment duration (OR 2.45 [1.243-4.828], P = 0.010). FVC% slope from treatment initiation to discontinuation appeared to be increasing in patients with higher baseline inflammatory markers compared to those with low to normal marker levels (P = 0.003) (Figure1). CONCLUSION: Patients with non-IPF f-ILD and high initial inflammatory markers appear to be more acutely responsive to anti-inflammatory therapy with slower FVC decline or improvement over time while on treatment. These findings suggest baseline serum CRP and ESR may be reliable predictors of treatment response and direct treatment duration and intensity for efficacy or reducing adverse effects.

Abstract Introduction: The variety of pulmonary function tests (PFTs) offered in the pulmonary function lab (PFL) can confuse providers unfamiliar with the clinical role of the individual components of the PFT, potentially leading to repeat tests, diagnostic delays, patient burden, and reduced lab efficiency. We hypothesized that a symptom- and diagnosis-based ordering set will reduce the need for repeat testing visits. Methods: Baseline data (June 2022-June 2023) were first collected to establish PFL performance benchmarks and identify common reasons for incomplete or repeat PFL visits. We then implemented an electronic order set reflecting the clinical need of the PFT, based on symptoms, diagnoses, suspected diagnoses, or other common clinical indication in addition to a physician-supervised, results-driven protocol to allow de-escalation of testing when appropriate The pre-implementation data was compared to the post-implementation data (July 2023-June 2024), evaluating for its impact on PFL access, utilization of the specific PFT components (e.g. methacholine challenge test, MCT), and on diagnoses. Results: During the study period 52,292 PFTs were performed during the pre-implementation phase compared to 58,310 tests in the post-implementation phase. Following intervention, the need for a second PFL visit for the same clinical indication decreased from 26% to 13% (p<0.0001). The same day PFL capacity increased by 3-4 patients per day. 80% of primary care providers reported the new order design was more intuitive and easier to use. Among the specific components of the PFT, there was a significant increase in the number MCTs being performed, from 2.5% to 4%, (p<0.0001), with a change rate ranging between 26 – 81% / month. In a subset analysis of 57 consecutive patients having MCTs, the primary indications were evaluation for cough or wheezing (57.9%), initial asthma evaluation (22.8%), and specifically requested by the ordering provider (19.3%). MCT was not performed in 23% due to a low baseline lung function, difficulty with repeatable efforts, recent bronchodilator administration, or due to complicating comorbidities. Of the 39 tests completed, 89% were deemed appropriate, with 32% having positive results and 42% ultimately diagnosed with asthma. Conclusions: A symptom and/or diagnosis guided ordering set for pulmonary function testing appears to improve the efficiency of the PFL, while improving provider experience, PFL access, as well as on patient burden and diagnoses. Further research is needed to determine potential benefits for provider decision-making and patient outcomes.

Abstract Introduction: Chronic obstructive pulmonary disease (COPD) is a top 5 cause of death and bears significant morbidity and mortality. The role of multimorbidity in patients with COPD has been shown to affect quality of life, increase risk of disease exacerbation, and mortality. COPD-targeted treatments have shown limited effects on mortality, but this patient population may benefit from practitioners more aggressively managing other comorbid conditions. Understanding which diseases have the largest impact on mortality in COPD patients may help providers understand which comorbidities to manage aggressively. Methods: We used the National Vital Statistics System (NVSS; 2019 data release), which collects all death certificate data for US citizens along with basic demographic information. We only included those who died with COPD as a diagnosis on their death certificate, defined as those who had international classification of disease, version 10 (ICD-10) codes J40-J44. We then dichotomized the causes of death by COPD vs non-COPD causes, based on the underlying cause of death (UCOD) on the death certificate. UCOD is defined by the NVSS as “the disease or injury which initiated the train of events leading directly to death.” Demographic information was collected, race was self-reported, and level of education was dichotomized as less than HS diploma vs higher. We used chi-square or t-test to determine statistical significance (defined as p <0.05) between groups for demographic information. Results: 308,856 US adults had an ICD-10 code associated with COPD written on their death certificate, of these 156,499 (50.6%) had a UCOD other than COPD. Overall, mean age 77.1 years (SD 2.6 years), 49% were female. The 10 most common diagnoses of those who died of non-COPD causes are presented in Figure 1, with the three most common causes being lung cancer (23689, 15.1%), atherosclerotic heart disease (22,848, 14.6%), and acute myocardial infarction (6422, 4.1%). Six of the top 10 are cardiovascular diseases. Conclusion: Patients with COPD are at high risk of mortality from comorbid conditions, with around 50% dying from non-COPD etiologies according to death certificate data. Most of these etiologies have evidence-based and mortality-reducing interventions such as lung cancer screening and management of cardiovascular risk factors including cholesterol-lowering medications and antihypertensives. While we don't have more granular data in terms of medications and therapies, these findings suggest that guideline-oriented approaches, both in terms of lung cancer screening and cardiovascular-risk reduction, may have a strong impact on mortality reduction in this patient population.

Abstract Introduction: Over 90% of adolescents (18-24 years) have a social media account. In 2021, an estimated 18.3% of 18-24-year-olds used electronic cigarettes. This age group is more likely to use social media as a health information resource than other sources. The social media platform TikTok is the fastest growing platform among adolescents. There is growing interest in vaping cessation among adolescents, and vaping cessation posts have grown accordingly. Our hypothesis is there are diverse vaping cessation methods described by TikTok users important for clinicians to understand. The use of qualitative methods informed by netnography represents an ideal way to evaluate TikTok videos. Methods: TikTok videos describing at least one vaping cessation method posted in English uploaded after January 1, 2022 were eligible for inclusion. Any post associated with advertising, sponsorship, corporations, or retail entities were excluded. Reposts of any kind were excluded. A total of 200 videos were reviewed in duplicate for eligibility. NVivo Version 14 transcription cloud and coding software was used. Coding was conducted independently by the study team until thematic saturation was reached. This study was deemed exempt by the Mayo Clinic Institutional Review Board as social media data is public domain and no identifiers were collected. Results: A total of 52 videos were included. Included videos had an average of 2.4 million views, 285,000 likes, and 11,000 shares. There were a wide variety of vaping cessation methods described. Some methods, such as hand motions mimicking vaping, limiting exposures, and use of nicotine replacement are supported by cigarette smoking cessation literature. There were also numerous videos outlining methods known to be ineffective or harmful, including instructions to vape continuously until illness occurs, and utilizing negative self-affirmations to “scold” yourself when using electronic cigarettes. Themes of inner strength, motivations, and shame were also discussed, and multiple users described their “wake up call” to quit vaping. Conclusions: Social media platforms are growing in popularity with adolescents and individuals under age 18. The inability for users to discriminate between evidence-based health advice and anecdotal experiences represents a key issue for clinicians to be aware of when counseling patients. Given the age demographics of social media users, this issue will grow as the population ages. Clinicians should engage in conversations with their patients about sources of reputable health information, and future directions may include novel methods such as partnering with influencers or social media companies.

Abstract RATIONALE:New-onset atrial fibrillation (NOAF) is a common arrhythmia associated with adverse outcomes in patients with chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea (OSA). Both conditions, through shared mechanisms, raise the likelihood of NOAF incidence, emphasizing the importance of epidemiological data and preventive measures to prevent NOAF burden. Therefore, we examined the risk of NOAF in patients with COPD, OSA, and their overlap syndrome (OS). METHODS: We extracted data from the Banner Healthcare Organization, US Collaborative Network in TriNetX, identifying three patient cohorts using ICD-10 codes for COPD (J40-J44) and OSA (G47.3). This included 73,540 patients with OS, 198,880 patients with OSA only, and 337,010 patients with COPD only. Patients with a prior diagnosis of AF before their diagnosis of OSA or COPD were excluded. Propensity matching was conducted based on age, sex, ethnicity, and cardiovascular disease risk factors and prevalence including hypertension, tobacco use, dyslipidemia, obesity, and ischemic heart disease. We calculated the relative risk (RR), hazard ratio (HR), and 95% confidence intervals (CI) for incident AF among propensity score-matched cohorts, comparing OS with OSA alone and OS with COPD alone.RESULTS: In the OS vs. OSA only comparison, 63,070 patients were matched per cohort. Lifetime incidence of new AF was higher in the OS group (13.65%) compared to the OSA-only group (8.24%), with an RR of 1.66 [95% CI: 1.60-1.72]. Kaplan-Meier analysis indicated a lower AF-free probability in the OS group (65.96%) than in the OSA-only group (77.03%), with an HR of 1.56 (p < 0.001). In the OS vs. COPD only comparison, 65,810 patients were matched per cohort. Incidence of new AF in the OS group was 13.76%, compared to 9.86% in the COPD-only group, with an RR of 1.40 [95% CI: 1.35-1.44]. Kaplan-Meier analysis showed a lower AF-free probability for the OS group (66.13%) versus the COPD-only group (78.94%), with an HR of 1.28 (p < 0.001). Sensitivity analyses restricted to the first five years post-diagnosis revealed a persistently higher relative risk of incident AF in OS patients, with an RR of 1.67 [95% CI: 1.60-1.73] compared to OSA alone, and an RR of 1.34 [95% CI: 1.29-1.39] compared to COPD alone. CONCLUSION:We identified that patients with OS have a higher risk of NOAF compared to either condition alone. This emphasizes the need for vigilant monitoring and targeted interventions in patients with OS to decrease arrhythmogenicity risks.

Abstract Rationale: The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor and cellular chemical sensor. AhR maintains cellular homeostatsis in respons to endogenous and exogenous organic molecules. Airway smooth muscle (ASM) cells are major structural cells in airway which is involved in characteristic features of asthma such as increased airway wall thickness, airway remodeling and airway hyperresponsiveness. Previously, we found notable expression of AhR in human ASM and its increased expression during inflammation and asthma. However, the mechanisms of enhanced AhR expression in ASM is unknown. Therefore, we examined the role of pro-inflammatory signaling pathways in enhanced AhR expression. Methods: Primary human non-asthmatic and asthmatic ASM cells isolated from surgical lung resections (Mayo IRB approved) were cultured in DMEM-F12 medium supplemented with 10% fetal bovine serum and 1% antibiotic/antimycotic. At ∼80% confluency, cells were serum deprived and treated with TNFα (20 ng/mL), IL13 (50 ng/mL) with or without PI3K/Akt inhibitor (Wortmannin: 50 nM), p38 inhibitor (SB203580: 600 nM), NFkB inhibitor (SN50 20 μM), and AP1 inhibitor (SR11302 10 μM). Subsequently, expression of AhR was determined using RNA sequencing, confocal microscopy, real-time qPCR, and Western blotting. AhR expression in isolated ASM fron lung tissue section was determined using laser capture microdissection (LCM). Moreover, role of AP1 in inducing AhR expression was confirmed using c-JUN (AP1) siRNA transfection in ASM cells. Additionally, binding of AP1 to the AhR promoter region was demonstrated by chromatin-immunoprecipitation (ChIP-qPCR) technique. Results: AhR expression was significantly high in asthmatic ASM cells and tissue than non-asthmatics. Exposure to pro-inflammatory cytokine TNFα increased AhR mRNA and protein expression, whereas IL-13 failed to do so. Furthermore, inhibition of p38 significantly reduced AhR expression whereas PI3K inhibition had no effect, indicating a role for p38 in AhR increased expression. AP1 inhibition significantly downregulated AhR, while NFkB inhibition showed no effect. Similarly, siRNA mediated silencing of c-JUN (AP1) also downregulated AhR, indicating AP1 role in AhR upregulation. Furthermore, transcription factor binding study suggested AhR promoter region has binding site for AP1 and NFkB. Interestingly, ChIP-qPCR study confirmed binding of AP1 at AhR promote region in response to TNFα. Conclusions: Collectively, the current study show that pro-inflammatory cytokine TNFα increases AhR expression through p38-AP1 pathway. The data shows that pro-inflammatory cytokines can regulate AhR expression in ASM, suggesting AhR in ASM has a role in asthma.

Abstract Rationale: MUC5B and MUC5AC are neighboring genes on chromosome 11p15 that encode the two predominant mucins secreted in the respiratory airways. Increased airway mucin concentrations and an imbalance between these two mucins drive COPD symptoms and the development of airflow obstruction or COPD, but the epigenomic regulation of this loci has not been characterized in the airways. Methods: We isolated DNA from bronchial airway brushings of 72 participants with >20 pack-years smoking history from the Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS). 36 participants had GOLD-based moderate-to-severe COPD (FEV1/FVC<0.70, FEV1<80%) and 36 were without or with mild COPD. We used the Illumina Infinium Methylation EPIC BeadChip Array to assess proportion of DNA methylation (β) spanning 689,937 CpG sites. We evaluated proportional DNA methylation (β) at 96 CpG loci within a 103kB region using matrixQTL for cis-expression quantitative trait methylation (eQTM: 10kB flanks relative to MUC5AC/MUC5B) integrating bulk RNA-seq data and mQTL models integrating gene sequencing data to identify DNA variation associated with proportion eQTM methylation. Models included age, sex, BMI, clinical site, current smoking vs past smoking, total pack-years, three ancestral components of ancestry, chipset, and position. Results: We identified a top eQTM, cg00524486, marginally associated with MUC5B expression (coefficient estimate=8.75, punadjusted=0.0014, pFDR=0.065, Figure 1B). This eQTM was associated with CT scan parametric response mapping-based functional small airways disease (PRM-fSAD, beta coefficient[β]=3.64, p=0.011). We tested for DNA variation associated with methylation of this top eQTM which identified two methylation quantitative trait loci (mQTL: rs885454 [β=0.044, minor allele frequency[MAF]=0.09, pFDR=0.01], rs868902 [β=0.020, MAF=0.43, pFDR=0.08, Figure 1A) associated with cg00524486 methylation, of which the more frequent mQTL, rs868902, was marginally associated with PRM-fSAD (p=0.07) in the larger SPIROMICS cohort with MUC5B DNA sequencing data. Conclusions: This preliminary multi-omic study of the lower airway epithelium demonstrates that the expression of MUC5B is epigenetically regulated by neighboring CpG probe methylation (eQTM) represented by DNA variation (mQTL). These studies require further confirmation in a larger dataset of airway samples and support a role for epigenetic variation as a biologic contributor and biomarker of early COPD pathogenesis.