Citations

Objective: Reverse hybrid coronary revascularization (RHCR) is the integration of percutaneous coronary intervention (PCI) followed by sternal-sparing coronary artery bypass grafting in patients with multivessel coronary artery disease (CAD). We sought to review our RHCR experience over a 10-year period using PCI first followed by robotic totally endoscopic coronary artery bypass (TECAB). Methods: We reviewed the indications and outcomes in patients who underwent RHCR (PCI with drug-eluting stents first, followed by TECAB). Results: From July 2013 to August 2024, 882 robotic TECAB procedures were performed at our institution. Of these, 60 patients underwent RHCR. The mean age of the patients was 66.7 ± 10 years, and 74% were male patients. The target vessel stented was the right coronary artery in 52 patients (87%), circumflex coronary artery in 10 patients (17%), and diagonal in 4 patients (7%). The average time from PCI to TECAB was 3.8 ± 1.64 months. A total of 35 patients (58%) underwent multivessel grafting, with 74% bilateral internal thoracic artery (ITA) use. The mean operative time was 253 ± 88 min, and the mean hospital length of stay was 2 ± 0.76 days. There were no conversions, perioperative strokes, or myocardial infarctions. At mean follow-up of 34 ± 27 months, cardiac-related mortality occurred in 1 patient. Freedom from major adverse cardiac or cerebrovascular events including repeat revascularization was 93%. Conclusions: RHCR is safe and feasible in selected patients with multivessel CAD. In experienced hands, stenting first followed by robotic TECAB with left ITA or bilateral ITA grafts resulted in excellent early and midterm outcomes. Further studies are warranted.

Abstract Introduction Resilient smokers, who maintain respiratory health despite smoking, remain poorly characterized. Airway epithelial cell gene expression in resilient smokers can provide insight into mechanisms and pathways that may protect smokers from developing smoking-related lung disease. The objective of this study is to identify genes and potential pathways associated with lung-related resilience. Methods Resilient smokers were defined based on a previously published multi-dimensional definition which includes the absence of: 1) spirometric airflow limitation, 2) symptoms (cough/sputum, dyspnea), 3) radiographic (HRCT) abnormalities, 4) exacerbations, and 5) an accelerated FEV1 decline. “Non-resilient” smokers had preserved spirometry but showed abnormalities in at least one domain of resilience. We analyzed airway epithelial brush samples from 21 resilient and 34 non-resilient smokers from SPIROMICS. Differential gene expression was performed using DESeq2 package in R, which estimates differential expression using generalized linear models. We adjusted for sequencing batch, age (continuous), race, gender, and current smoking status. While controlling for these covariates we evaluated differential gene expression between resilient and non-resilient smokers, the interaction between resilience and smoking status, and in each sub-category of resilient (absence of symptoms, radiographic abnormalities, exacerbations, and accelerated decline in FEV1). Results We identified 98 genes that were differentially expressed (FDR ≤0.1) when comparing resilient to non-resilient smokers, 20 of those genes were up regulated in resilient smokers (Figure 1). Notable genes included cadherin-12 (CDH12), aspartate beta-hydroxylase (ASPH), and protein kinase AMP-activated alpha 2 (PRKAA2). CDH12 is involved in cell adhesion and epithelial integrity. ASPH influences cell adhesion and signaling. PRKAA2 plays role in cellular homeostasis and stress response, which may be altered in non-resilient smokers, affecting cellular metabolism and inflammation. BPI folding containing family A member (BPIFA1) was significantly associated with smoking status in the interaction analysis, suggesting its role in modulating the impact of smoking on resilience. BPIFA1 has anti-microbial properties, regulates immune responses, and contributes mucosal surface protection. Sub-category analysis identified 17 genes associated with resilience to symptoms and 2 genes related to physiologic resilience (FEV1 decline), though no significant genes were associated with radiographic or exacerbation resilience. Conclusion Differential gene expression of airway epithelial cells identified distinct expression patterns between resilient and non-resilient smokers. Specifically, genes associated with epithelial cell adhesion, signaling, and cellular homeostasis were up regulated in resilient smokers. These findings suggest that resilient smokers may have transcriptomic profiles and potential mechanisms that mitigate the effects of cigarette smoke.

Abstract Effective communication during handoffs and transitions of care is crucial, as over 50% of sentinel patient events are due to communication gaps, according to the Joint Commission. In our open multi-specialty Intensive Care Unit (ICU) at a tertiary care center, we noticed variability in handoff practices leading to provider dissatisfaction, delays in care and increased potential for errors. To address this, we developed and implemented a standardized handoff procedure. METHODS: A multi-disciplinary team comprised of fellow physicians, nursing and advanced practice provider (APP) leadership conducted an online anonymized baseline survey (B) in December 2023 in our open mixed ICU assessing multidisciplinary provider satisfaction in the process of transitioning patients out of the ICU. Based on this, we identified areas for improvement in the ICU transfer-out process, focusing on communication methods and handoff standardization. Between February and June 2024, we designed and posted signage near provider work areas to clearly designate the primary team based on the level of care and co-managing specialties. We also developed electronic record-based template dot phrases based on the I-PASS format to help standardize information provided during handoff, and ICU team members were educated on the use of the same. Post-implementation (PI) surveys were anonymously conducted in June 2024 to assess the impact of changes, with data analysis comparing pre- and post-implementation metrics, and regular feedback meetings facilitated iterative improvements. RESULTS: We received 40 survey responses (B =20 and PI=20). In the baseline survey, 65% identified room for improvement, particularly with the timing of provider handoffs, inconsistencies in transfer documentation, and clarity on the responsible medical team. Post-implementation survey results showed a 15% improvement with 80% reported no problems during the process, and 85% rated the clarity of the process as “very clear” and “clear,” with 15% neutral. Regarding staff communication, 90% rated it as “good” to “very good,” with 5% neutral. Dot phrase utilization was deemed “very helpful” to “helpful” by 54%, while 46% were neutral. The majority (95%) reported no challenges during the transfer-out process, and 80% were satisfied with the initiative's implementation. CONCLUSION: Our study highlights the impact of a multimodal approach in improving the process of ICU transitioning patients. We were able to improve the primary team identification with posted signage in the ICU.Using computer template-based dot phrases, we were also able to successfully improve satisfaction with the sign out process at time of transition out of the ICU level of care.

Abstract RATIONALE: Airway-to-lung ratio (AirLR), calculated as the mean of airway lumen diameters at standard anatomic locations divided by the cube-root of total lung volume, is associated with COPD risk regardless of smoking status, and we have previously shown an association between total-pulmonary-vascular-volume-to-lung-size relationship with AirLR. [PMCID: PMC11284327] Using dual energy computed tomography (DECT), we recently developed a deep learning-based algorithm for pulmonary arterial segmentation to compute pulmonary-arterial-to-lung ratio (ArtLR) which correlated significantly with AirLR and markers COPD. Here we automate image processing in a larger cohort to estimate ArtLR, introduce an alternative ArtLR standardization and correlate it to COPD-related measures of lung structure and function. METHODS: Using a SPIROMICS sub-cohort (110 participants), imaged via contrast enhanced DECT at functional residual capacity (FRC), an automatic deep learning pipeline segmented the arteries from the pulmonary vascular tree. Another pipeline automatically extracted the centerlines and calculated average arterial segment diameters. A paired non-contrast total lung capacity (TLC) scan was registered to the DECT FRC scan to transfer airway segment labels from the TLC to FRC domain. AirLR was calculated as the mean of airway lumen diameters at standard anatomic locations (trachea-to-subsegments) divided by cube root of lung volume [TLC or FRC]. A simple Long Short-Term Memory (LSTM) network was used to find corresponding anatomic arterial segments. Associations between ArtLR and %Emphysema, AirLR, pre- and post-bronchodilator FEV1/FVC, and a texture-based (AMFM) measure of %broncho-vascular bundles was assessed using linear regression to adjust for age, sex and BMI. RESULTS: In adjusted analyses, a 1-SD decrement in ArtLR-TLC was associated with 4.198 units increase in %Emphysema-910 (95%CI: 1.360-7.037; p = 0.0041), and 0.8198 units decrease in %Bronchovascular (95%CI: 0.5037-1.136; p < 0.0001). A 1-SD increment in ArtLR-TLC was associated with 0.2515 SD increase in AirLR-Outer (95%CI: 0.04947SD-0.4536SD; p = 0.0152), and 0.02083 units increase in PreBronch-FEV1FVC (95%CI: 0.001814-0.03984; p = 0.0321). Sex and BMI show significant associations with ArtLR-TLC, where female is associated with 1.068 SD decrease in ArtLR, and a unit increase in BMI is associated with 0.05788 SD increase in ArtLR (both p-values < 0.0001), and age was not association with ArtLR. CONCLUSIONS: An automated pipeline for pulmonary arterial tree segmentation and standardization from contrast enhanced DECT FRC scans demonstrates a significant relationship between ArtLR and AirLR as well as between ArtLR and %emphysema, and FEV1/FVC. A standardized method of arterial tree size assessment provides for expanded exploration of vascular vs airway disease etiologies.

Abstract Rationale: Application of single cell RNAseq (scRNAseq) in idiopathic pulmonary fibrosis (IPF) and multiple murine models has revealed two unique disease associated fibroblast subsets, the Cthrc1+ fibrotic population, and a population expressing inflammatory markers whose function is unclear. We, and others, have demonstrated that inflammatory fibroblasts are derived from homeostatic fibroblasts and can differentiate to Cthrc1+ fibroblasts. There is also data in mice suggesting that TGFβ inhibition prevents the emergence of Cthrc1+ fibrotic fibroblasts without impacting the inflammatory fibroblast population. Using our inducible genetic murine model of PF, reductionist organoid systems, and scRNAseq from IPF we present evidence and mechanism for inflammatory fibroblasts as a potential regenerative population in the alveolar niche. Methods: Tamoxifen administration to SftpcI73T conditional allelic knock-in mice, induces expression of mutant protein and promotes an inflammatory cascade followed by fibrogenesis. ScRNA-seq and population RNA-seq of bleomycin and SftpcI73T murine models were compared with publicly available data sets from IPF to identify population specific surface marker expression and potential epithelial ligand-receptor pairs. Flow cytometry approaches developed to isolate fibroblast populations were applied for in-vitro organoid modeling and validation of signaling pathways. In-vivo murine intervention in TGFβ signaling was further applied to confirm functional biology of inflammatory fibroblasts. Results: Informatic analysis of human and mouse inflammatory fibroblasts identifies expression of multiple BMP antagonists that have previously been associated with epithelial proliferation. Furthermore, human inflammatory fibroblasts also express key epithelial growth factors including FGF2 and FGF7. Murine organoid modeling confirms that inflammatory fibroblasts support alveolar organoid formation through the inhibition of BMP signaling. As was previously demonstrated in bleomycin, the inhibition of TGFβ signaling in SftpcI73T does not alter the inflammatory fibroblast population, rather this population is sustained, and alveolar epithelial proliferation increases. Additionally, we did not find any evidence for increase inflammation in the mouse lung due to inflammatory fibroblasts preservation. Finally, human data suggests that two populations of inflammatory fibroblasts are present in the lung with only one subset found to express the BMP antagonists and growth factors required to promote alveolar epithelial proliferation. Conclusions: Our data identifies that inflammatory fibroblasts in the alveolar niche inhibit BMP signaling and allow for epithelial expansion. We also determine differences between murine and human inflammatory fibroblasts suggesting that human inflammatory fibroblasts have a greater potential to drive epithelial expansion. These data shed light on the functional role of inflammatory fibroblasts, further refining our understanding of fibroblast heterogeneity in IPF.

Abstract RATIONALE: Understanding co-isolation patterns between fungi and other potentially pathogenic microorganisms in the airways of bronchiectasis patients is important for uncovering possible microbial interactions and informing treatment. Although numerous organisms have been identified in respiratory cultures, the specific patterns of their co-isolation are underexplored. OBJECTIVES: To examine the patterns of co-isolation between fungi and bacteria or mycobacteria in respiratory samples from patients with bronchiectasis across a large national health system. METHODS: We reviewed 58,170 respiratory culture tests from 8,194 patients with bronchiectasis (identified using ICD-10-CM codes J47.0, J47.1, and J47.9) across Mayo Clinic. These tests were analyzed for fungal, bacterial, and mycobacterial growth, focusing on co-isolation from the same sample. Chi-square statistics were used to compute p-values. RESULTS: Of all 18,983 samples cultured for fungi, 59% were positive. Of these, 72% yielded yeasts and 40% molds. Among the 11,372 samples cultured for both fungi and bacteria, 681 (6%) showed co-isolation, representing 54% of positive bacterial cultures. The odds of bacterial co-isolation with fungi were 1.4 (95% CI: 1.3-1.6; p < 0.01), driven by yeasts (OR: 1.5, 95% CI: 1.3-1.7; p < 0.01), rather than molds (OR: 1.0, 95% CI: 0.9-1.2; p = 0.8). Pseudomonas species, the most common bacterial isolate, had a higher likelihood of co-isolation with fungi (OR: 1.6, 95% CI: 1.3-1.9; p < 0.01), particularly yeasts (OR: 1.6, 95% CI: 1.4-2.0; p < 0.01). Molds, including those from genera such as aspergillus and penicillium, did not show a significant association with the isolation of pseudomonas. On the other hand, among the 15,859 samples cultured for both fungi and mycobacteria, 1352 (9%) showed co-isolation, representing 62% of positive mycobacterial cultures. Odds of co-isolation were 1.7 (95% CI: 1.5-1.8; p < 0.01). Molds showed a stronger association with isolation of mycobacteria (OR: 1.7, 95% CI: 1.5-1.9; p < 0.01) compared to bacteria, while yeasts also had elevated odds (OR: 1.4, 95% CI: 1.2-1.5). CONCLUSIONS: Distinct patterns of fungal co-isolation with bacteria and mycobacteria have been observed in bronchiectasis, which may influence key aspects of the disease, such as inflammation and mucociliary dysfunction. Advanced metagenomic and immunoprofiling techniques could provide deeper insights into these co-isolation patterns while considering other factors like clinical demographics, previous antibiotic exposure, and disease severity. Understanding whether altering the mycobiome could modify these aspects and improve outcomes remains an important avenue for research.

Abstract Introduction: Cystic fibrosis (CF) is a genetic disorder characterized by defective chloride ion transport, leading to thick mucus production, chronic respiratory infections, and other multisystem involvement. Although CF is often diagnosed in childhood, the condition can be missed or misdiagnosed in adults. Description of Case: We present the case of a 60-year-old male from India who was diagnosed with CF after a prolonged period of sinopulmonary symptoms. He initially presented in 2014. His medical history was pertinent for asthma, and multiple episodes of clinically and radiographically confirmed pneumonia and polypoid sinusitis requiring IV antibiotics and sinus surgery. He carried a prior diagnosis of allergic bronchopulmonary aspergillosis treated with itraconazole and steroids, as well as elevated IgE levels. His CT chest was notable for extensive bronchiectasis, bronchial wall thickening, and mucus plugging of both lungs. He had no known family history of CF. Sweat chloride testing was in the intermediate range (44, 47 mmol/L; normal <30 mmol/L, intermediate 30 to 59 mmol/L, abnormal >59 mmol/L). Given high suspicion for CF, cystic fibrosis transmembrane conductance regulator (CFTR) full gene analysis was pursued. Sequence analysis and multiplex ligation-dependent probe amplification of the CFTR gene detected heterozygous sequence changes c.1717-2A>T, classified as likely deleterious, and c.1367T>C (p.V456A), variant of uncertain significance. He was thus initially diagnosed as a CF carrier. He re-presented in 2024 with decline in pulmonary function testing and continued sinopulmonary infections. Genetic testing results from 2014 were re-analyzed. Between initial presentation and present, his V456A variant was upgraded to pathogenic. He met diagnostic criteria for CF with two pathogenic CFTR variants, a repeated intermediate sweat chloride (47 mmol/L) suggestive of CFTR protein dysfunction, and disease that could be attributed to CFTR dysfunction. He subsequently started TRIKAFTA® (elexacaftor/tezacaftor/ivacaftor and ivacaftor) and airway clearance therapy. Discussion: The diagnosis of CF in adults can be challenging, particularly in individuals without a known family history, intermediate sweat chloride testing, and with inconclusive genetic testing. Our understanding of CF in Asian populations is limited. CF is suspected to be underreported in patients with Southeast Asian ancestry in part due to genetic heterogeneity. The interpretation of certain genetic variants can evolve over time. A variant of unknown significance may later be reclassified as pathogenic, revealing its true role in disease development. This highlights the critical importance of regularly re-evaluating genetic test results.

Abstract RATIONALE: Absolute Blood Eosinophil Counts (BEC) in bronchiectasis patients offer insights into inflammatory patterns and potential treatments. In non-cystic fibrosis bronchiectasis (NCFB), BEC≥300 cells/μL characterizes Eosinophilic Bronchiectasis (EB), a type-2 inflammation endotype estimated in 20% of patients. Guidance on BEC assessment strategy (i.e., number, frequency and timing of BEC≥300 defining this endotype) is unclear. We hypothesize that EB incidence varies by BEC≥300 assessment strategy. We also investigate eosinophilic inflammation in CF for comparison. Objectives: Assess BEC≥300 incidence in NCFB and CF cohorts. METHODS: From January 2023 to October 2024, BEC were measured in 9,953 stable bronchiectasis patients across Mayo Clinic, including 9,806 with NCFB (J47.9; 66,780 CBCs) and 147 with CF (E84.0; 1,405 CBCs). Incidence of BEC≥300 was evaluated in relation to CBC frequency and timing (i.e., BEC≥300 on first, second, last, any, any two, first two simultaneously) and the number of CBCs per patient. RESULTS: In the NCFB cohort, median age was 74 years (IQR:66-82), with 59.5% female. Median CBCs/patient was 3 (IQR:1-7). Incidence of BEC≥300 on the first CBC was 19.8%. Among patients with ≥2 CBCs (n=7,075), incidence was 20.1% on the first, 19.8% on the second, and 20.0% on the last. This incidence rose to 36.3% when considering any CBC/patient. BEC≥300 on at least two CBCs was 29.3%, decreasing to 11.8% when considering consecutive BEC≥300 on both first and second CBCs. The incidence of BEC≥300 increased linearly with the number of CBCs obtained: 24.6% for those with 1-3 CBCs, up to 64.6% for >12 CBCs. In the CF cohort, median age was 36 years (IQR:27-52), with 55.1% female. Median CBCs/patient was 4 (IQR:2-8). BEC≥300 was present in 22.9% of first CBCs, rising to 36.3% when considering any CBC and 29.3% when present on at least two CBCs. Similar to the NCFB cohort, incidence increased with the number of CBCs: 26.5% for 1-3, up to 77.3% for >12. CONCLUSIONS: The incidence of BEC≥300 in our NCFB cohort remained steady at 20% at any specific measurement point, consistent with prospective literature. However, nearly half of those with BEC≥300 on the first or second CBC did not meet this threshold on both. Incidence significantly increased when any CBC was considered, and more CBCs were available. Similar observations were made in the CF cohort. Clearer BEC assessment strategies are needed to define clinically significant eosinophilic inflammation in bronchiectasis, to better identify patients who may most benefit from type 2 inflammation-targeted treatments.

Abstract Purpose: Frail and malnourished patients with bronchiectasis have worse outcomes. This study examines frailty and malnutrition as predictors of 30-day readmission after bronchiectasis exacerbation (BE). Methods: We utilized the 2018 Nationwide Readmissions Database to analyze hospitalizations for BE. Patients with BE were identified through principal and secondary ICD-10 diagnosis codes J47.0 and J47.1. Among those who survived the index hospitalization, only individuals discharged to home were included in the analysis. The primary objective was to identify predictors of 30-day readmission, with a specific focus on frailty and malnutrition. Frailty was measured using the validated Hospital Frailty Risk Score, as described by Gilbert et al. (Lancet, 2018), while malnutrition was identified using ICD-10 codes E43, E44.0, E44.1, and E46. Comorbidity burden was categorized using the Charlson Comorbidity Index: mild (score 0-2), moderate (3-5), and severe (≥6). A multivariate logistic regression model was employed to calculate adjusted odds ratios (ORs) for readmission, with statistical significance defined as p < 0.05. Results: Among 20,742 patients discharged home following bronchiectasis exacerbation, 4% (830) were readmitted within 30 days. Patients with readmission were younger (median age 63 vs. 69 years, p<0.01) and more likely to be treated at urban hospitals (84.9% vs. 80.0%, p=0.01). They also had higher rates of frailty (52.6% vs. 46.5%, p=0.01), malnutrition (21.0% vs. 14.7%, p<0.01), and Pseudomonas pneumonia (5.9% vs. 3.9%, p=0.03). The comorbidity burden was not different (p=0.29). After adjusting for age, malnutrition demonstrated a trend toward higher odds of readmission (OR 1.31, 95% CI 0.99-1.73, p=0.059), though this did not reach statistical significance. In contrast, frailty was significantly associated with increased readmission (OR 1.36, 95% CI 1.12-1.66). The presented Table describes the demographic characteristics and outcomes of ALL hospitalized patients with BE (n = 40, 789) stratified by frailty and malnutrition. Conclusions: Frailty is a significant predictor of 30-day readmission following BE. Targeted interventions addressing frailty in hospitalized patients with BE may help reduce readmission rates.