Citations

Abstract Rationale Secondhand exposure to electronic nicotine products is driven by exhaled emissions. Eliminating heat and combustion may reduce exhaled toxic carbonyls. Methods In a 4-day within-subject crossover, six adults each used four devices after 24-hour abstinence: an NHNC nebulization device (Bluesky), a coil-heated ENDS (RELX), a heated-tobacco device (IQOS), and a heated aerosol device (Marlboro). For each condition, paired pre-use exhaled blank and post-use exhaled samples were collected; 50 L of exhaled breath was captured post-use. Nicotine and 12 carbonyls were quantified (DNPH/activated-carbon with HPLC). Primary endpoint: within-subject change (Δ, post-pre) in total carbonyls (μg/50 L). Secondary: Δ acetaldehyde and Δ acrolein. Results The exhaled carbonyls(within-subject change, post-pre) in total differed markedly across devices: Bluesky (non-heated, non-combustion; NHNC) 0.85 ± 6.99, RELX 4.41 ± 2.58, IQOS 62.38 ± 21.77, Marlboro 80.73 ± 20.24 (p = 0.0015). Bluesky had significantly lower total exhaled carbonyls than IQOS (p = 0.0077) and Marlboro (p = 0.0021, μg/50 L; mean±SD), with a nonsignificant trend versus RELX (p = 0.945). For acetaldehyde, Bluesky was lower than all three (Bluesky 0.20 ± 0.16 vs. RELX 1.93 ± 0.86, p = 0.016; vs IQOS 43.08 ± 16.70, p = 0.0044; vs Marlboro 65.40 ± 13.69, p = 0.00025, μg/50 L). For acrolein, average exhaled volume was 0.54 ± 6.94 (Bluesky), 1.35 ± 2.05 (RELX), 7.94 ± 6.07 (IQOS), and −1.86 ± 5.09 (Marlboro); pairwise differences vs Bluesky were not significant after correction (p ≥ 0.37, μg/50 L). Conclusions In a controlled, within-subject comparison using exhaled breath as a proxy for secondhand aerosol, the NHNC nebulization device (Bluesky) produced near-zero average increment in total exhaled carbonyls, whereas heated devices—particularly heated-tobacco—showed order-of-magnitude higher increases. These descriptive data support the hypothesis that removing heat and combustion from nicotine aerosolization can materially reduce exhaled carbonyl burden relevant to secondhand exposure. Larger, randomized studies with standardized capture and enhanced nicotine quantification are warranted. This abstract is funded by: Pneuma Respiratory.Inc

Abstract Background Sleep disorders are increasingly recognized as important risk factors for cardiovascular disease (CVD), yet their contribution to cardiovascular mortality remains insufficiently examined at the population level. This study aimed to evaluate long-term trends in CVD mortality where sleep disorders were identified as contributing causes of death. Methods We analyzed U.S. national mortality data from 1999 to 2020 among individuals aged 15 to 84 years. Cases were selected where CVD (ICD-10: I11.0, I11.9, I20-I25, I48, I49.0, I49.9, I50.0, I50.1, I50.9) was the underlying cause and sleep disorders (ICD-10: G47.0-G47.3) were listed as contributing causes. Joinpoint regression was employed to assess temporal changes in age-adjusted mortality rates (AARs), with standard errors provided in the input data and model selection performed using Weighted BIC. APCs were estimated using the Empirical Quantile Method with 5001 resamples. Results A total of 118,440 deaths were included across 22 annual time points. Joinpoint regression identified two significant inflection points (2005 and 2018). From 1999 to 2005, AARs increased sharply (APC = 14.47%; 95% CI: 11.56-19.54; p = 0.0016), followed by a slower rise from 2005 to 2018 (APC = 6.62%; 95% CI: 4.23-10.83; p < 0.000001), and a renewed acceleration from 2018 to 2020 (APC = 11.54%; 95% CI: 7.01-14.12; p < 0.000001). Males had more than twice the AAR compared to females (3.00 vs. 1.31 per 100,000). Black individuals had the highest burden by race (AAR = 2.55), and geographic variation ranged widely from 0.70 in New York to 3.38 in Wyoming. Conclusions Over two decades, cardiovascular mortality with contributory sleep disorders has risen significantly, with widening demographic and geographic disparities. These findings reinforce that sleep disorders are not merely comorbidities but pivotal, modifiable drivers of cardiovascular morbidity and mortality. Untreated sleep conditions such as insomnia, obstructive sleep apnea, and circadian disruptions exacerbate autonomic dysfunction, inflammation, hypertension, and metabolic dysregulation. Addressing sleep health must become a core component of cardiovascular risk reduction strategies, both in clinical practice and public health policy. Failure to integrate sleep disorder screening, diagnosis, and management into CVD care pathways risks perpetuating a preventable and growing burden of disease. This abstract is funded by: None

Abstract Rationale Low-sodium oxybate (LXB; Xywav®) is FDA approved for treatment of cataplexy and excessive daytime sleepiness (EDS) in people ≥7 years of age with narcolepsy, and for idiopathic hypersomnia in adults. LXB Prescribing Information includes a Warning and Precaution for respiratory depression and sleep-disordered breathing; therefore, data on safety of LXB in people with obstructive sleep apnea (OSA; a common comorbidity among people with narcolepsy or idiopathic hypersomnia) are needed. This post hoc analysis of DUET (Develop hypersomnia Understanding by Evaluating low-sodium oxybate Treatment; NCT05875974), a prospective, open-label phase 4 study, evaluated respiratory parameters in participants taking LXB with or without comorbid OSA, in 3 cohorts: narcolepsy or idiopathic hypersomnia (LXB ≤9 g/night), or narcolepsy (LXB >9 g/night). Methods Participants underwent the following study periods: screening, 8-day baseline (BL; off-LXB for narcolepsy and idiopathic hypersomnia cohorts; on-LXB 9 g/night for >9 g cohort), 2-8-week dose titration, 2-week stable-dose, 8-day end-of-treatment (EOT; on optimized total nightly dosage; ≤12 g for the >9 g cohort), and 2-week safety follow-up. Participants with BL apnea-hypopnea index (AHI) >10 (treated/untreated OSA) were excluded from the study. Overnight polysomnography assessments conducted at BL and EOT included respiratory parameters: AHI, central apnea index (CAI), and percentage of total sleep time spent with oxygen saturation (SpO2) <90% (T90). Treatment-emergent adverse events (TEAEs) were assessed by OSA group. Least squares mean changes were adjusted for BL values. Results Fifty-five participants enrolled in the narcolepsy cohort, 9% (5/55) had comorbid OSA; 22% (10/46) and 31% (15/48) had comorbid OSA in the idiopathic hypersomnia and narcolepsy >9 g cohorts, respectively (3, 9, and 12 were on OSA treatment throughout the study). Most participants (narcolepsy, idiopathic hypersomnia, narcolepsy >9 g) were female (72.7%, 80.4%, 62.5%) and White (80.0%, 84.8%, 77.1%). No worsening of sleep-disordered breathing was observed during LXB treatment, as evidenced by respiratory parameters AHI, CAI, and T90 assessed at BL and EOT in either participants with or without OSA (Table 1). Percentages of participants with/without OSA reporting ≥1 TEAE were 60.0%/62.0% (narcolepsy), 80.0%/72.2% (idiopathic hypersomnia), and 66.7%/78.8% (narcolepsy >9 g). Most TEAEs were mild or moderate; 1 serious TEAE each occurred in the idiopathic hypersomnia cohort (with OSA) and the narcolepsy >9 g cohort (without OSA). Conclusions No worsening respiratory signals were observed with LXB treatment in participants with or without comorbid (mild or treated) OSA in the narcolepsy, idiopathic hypersomnia, or narcolepsy taking >9 g LXB dosage cohorts. This abstract is funded by: Jazz Pharmaceuticals

Abstract Inflammatory bowel diseases (IBD), principally Crohn’s disease (CD) and ulcerative colitis (UC), are common chronic disorders involving inflammation and often progressive tissue damage. Genome-wide association studies have mapped many risk signals, but the causal variants, effector genes and relevant cellular contexts remain difficult to resolve, limiting mechanistic interpretation and therapeutic translation. Here we performed a multi-ancestry GWAS meta-analysis of 125,992 individuals with IBD and more than 1.2 million controls, identifying 619 independent association signals (374 novel) at 420 IBD regions that account for 77–80% of SNP-based heritability. Fine-mapping resolved 81 high-confidence variants, 41 not previously reported. Although most signals were shared between CD and UC, 39% showed IBD subtype specificity, with UC signals showing stronger enrichment in functional annotations from intestinal epithelial, secretory and enteroendocrine cells, and CD showing stronger genetic correlations with circulating inflammatory biomarkers, including C-reactive protein and glycoprotein acetylation. Latent causal modelling supported a causal effect of decreased high-density lipoprotein on CD risk. By integrating bulk and single-cell eQTL and pQTL resources using colocalisation and Mendelian randomisation, together with coding-variant evidence from exome sequencing, we prioritised 664 candidate effector genes across 341 signals, including 390 newly implicated IBD genes, revealing new biological mechanisms and candidate therapeutic targets supported by human genetics.

Abstract Introduction Sickle cell disease (SCD) disproportionately affects African Americans(AA), comprising over 90% of cases. Acute pulmonary embolism (APE) is a serious complication in SCD patients due to increased thromboembolic risk from chronic inflammation, endothelial dysfunction, and hypercoagulability. Although recent studies have demonstrated sex-based differences in APE outcomes, data remain limited for SCD patients. We evaluated sex-based differences in outcomes among AA SCD patients with APE. Methods AA adults with SCD hospitalized for APE were queried from the 2016-2022 National Inpatient Sample. COVID-19 positive patients, patients younger than 18 years, and cases missing data were excluded. Demographics, treatment patterns, and in-hospital outcomes were compared between males and females using appropriate statistical tests with survey-weighted analysis. Results We studied 3635 SCD patients who were treated for APE, consisting of 60.66% (3635)females and 39.34%(2205) males. The overall mean age was 38.40 years, with no differences between the two sexes(mean age of 38.71 in males and 38.20 years in females, p = 0.620). While males reported a higher comorbidity burden with a Charlson Comorbidity Index(CCI) score of 1.03 (vs. 0.92 in females), it was not statistically significant(p = 0.345). In total, 23.43% of males and 22.68% of females had a prior history of PE(p = 0.815). Medicare constituted 31.82% of primary payers among males and 38.36% among females, while Medicaid and private insurance accounted for 32.52% and 24.83% of males, and 32.19% and 25.11% of females, respectively(p = 0.015). After adjusting for confounders, we found that females demonstrated higher odds of receiving transfusion to males. No statistically significant differences were seen for mortality, major cardiovascular complications including cardiac arrest, acute kidney injury, acute liver injury, ventricular tachycardia, or cardiogenic shock. In addition, treatment modalities such as mechanical ventilation, vasopressors or thrombolytic interventions(systemic thrombolysis, catheter-directed thrombolysis, mechanical thrombectomy) were comparable between males and females. We further did not find any differences in sepsis, bleeding events, acute ischemic stroke, or acute myocardial infarction(Table 1). Similarly, although females stayed longer(mean: 5.46 days vs. 4.90 days, p = 0.121), and had higher inflation-adjusted charges($61106 vs. $58810, p = 0.688), they were comparable. Conclusion Our study revealed that sex-based differences in outcome disparities among AA SCD patients admitted for APE are limited, with female transfusion requirements differing significantly, which warrants further investigation. This abstract is funded by: None

Abstract Introduction Chronic Lymphocytic Leukemia(CLL) is the most common leukemia in adults in the United States. CLL patients are at higher risk of bacterial infections, and Pseudomonas aeruginosa is a notable pathogen. Limited data is available comparing the demographics and outcomes of pseudomonas sepsis in CLL. Our study aims to analyze the patient characteristics and mortality between intensive care unit (ICU) and non-ICU admissions for pseudomonas sepsis among CLL patients. Methods Adults with active CLL admitted with a primary diagnosis code of pseudomonas sepsis(ICD-10 code: A41.52) were identified via the National Inpatient Sample(NIS)(2016-2022), excluding COVID-19 cases. Admissions to ICU were estimated if the patients required mechanical ventilation , vasopressors or central venous catheter placement, as per prior NIS-based studies. The predictors of ICU admissions were identified using multivariable regression models, with further analyses focused on estimating the in-hospital mortality. All analysis incorporated adjustments for weight, cluster, and strata, as advised by the data source. Results A total of 1,650 admissions were identified, of which 335 (20.3%) required intensive care. The intensive care cohort was younger (mean age: 73.19 vs. 76.86 years), yet age was not a significant predictor for the need for intensive care. Significant racial disparities were observed, with Black patients demonstrating significantly higher odds of intensive care use than White patients. In contrast, Hispanic patients had comparable odds to White patients. Sex, weekend admission status, private insurance coverage versus Medicare, and income quartiles did not significantly impact intensive care utilization. Among comorbidities, liver cirrhosis and palliative care encounters predicted higher ICU admission rates. Paradoxically, hypertension was associated with lower odds. Other comorbidities showed no significant association with intensive care admission (Table 1). Intensive care patients demonstrated an in-hospital mortality rate of 40.91% versus 8.75% in non-intensive care patients (aOR: 6.690, 95% CI: 2.648-16.906, p < 0.01). Furthermore, intensive care had a substantially greater resource utilization, longer stays (mean: 16.49 vs. 8.83 days, p < 0.01) and markedly higher hospitalization charges (mean: $314,311 vs. $89,614, p < 0.01). Conclusions Our study revealed that black race, comorbidities like liver cirrhosis and palliative care encounters were key predictors for ICU admissions. ICU utilization was associated with higher inpatient mortality, length of stay and hospitalization costs. These findings highlight the disparities and resource burden, and warrants strategic interventions to address them. This abstract is funded by: None

Abstract Rationale Septic shock patients require vasopressors to maintain adequate mean arterial pressure (MAP). The 2021 Surviving Sepsis Campaign Guideline recommends norepinephrine (NE) as first line, followed by vasopressin (VP). Early NE initiation is associated with faster achievement of MAP goals, lower fluid requirements, increased PaO2/FiO2 ratio, more mechanical-free ventilation days, and lower mortality. However, higher NE dosages can cause excessive vasoconstriction, impaired perfusion, lower Pa/Fi ratios, and increase in-hospital mortality. We tested the association between timing and cumulative dose of the NE with PaO2/FiO2 ratio, duration of invasive mechanical ventilation (IMV) and hospital length of stay (LOS). Methods We conducted a retrospective cohort analysis of adult septic shock patients treated with NE at Mayo Clinic Rochester Medical ICU between January 3, 2006, and April 17, 2018. Patients receiving other initial vasopressors were excluded. We developed linear regression models to assess how NE initiation time, defined as hours from sepsis identification, and cumulative dose, defined as total NE administered during ICU stay, affected median PaO2/FiO2 ratio, duration of IMV, and hospital LOS. We assessed for associations using: 1) an unadjusted model; 2) an adjusted model for baseline demographics and comorbidities (age, sex, weight, and Charlson Comorbidity Index); 3) an adjusted model for illness severity on day 1, using APACHE III and SOFA scores. Results Of 1,082 patients, 70% (n = 759) started NE as initial vasopressor. Timing of NE initiation was independently linked to shorter IMV and hospital LOS, but not to PaO2/FiO2 ratio. Across all models, earlier NE use significantly reduced IMV duration (β over 1.3992 ± 0.11 and p < 0.0001) and hospital LOS (average β 0.067 ± 0.01 and p < 0.0001). In contrast, a higher cumulative NE dose during the ICU stay was associated with a lower median PaO2/FiO2 ratio (β: -0.0053 ± 0.002, p = 0.0061), and remained significant in the adjusted models (β -0.0065 ± 0.002, p = 0.0013; and β -0.005 ± 0.002, p = 0.0132). Additionally, higher NE doses were significantly associated with longer IMV duration and hospital LOS in all models with p < 0.0001. Conclusion Although earlier initiation of vasopressor support with NE is associated with shorter durations of IMV and hospital LOS, higher cumulative doses are linked to the opposite effect. Increased NE doses were associated with lower PaO2/FiO2 ratios, delayed extubation and prolonged hospitalization. These findings highlight the importance of early NE administration and careful dose titration to optimize patient recovery. This abstract is funded by: None

Abstract Rationale Per the 2021 Sepsis Campaign, it is recommended that hospitals use a performance improvement program for sepsis screening, utilizing machine learning to improve specificity. Around 20% of sepsis at the Mayo Clinic, Rochester site is hospital acquired. As inpatient sepsis is usually detected by extreme physiologic derangement or clinical concern, we seek to leverage risk factors beyond traditional SIRS and sepsis criteria to create a machine and deep learning based risk stratification model to improve the precision of sepsis monitoring. Methods We designed a retrospective observational case control study, including patients diagnosed with sepsis as an inpatient at the Mayo Clinic, Rochester hospital and compared them to patients without a sepsis diagnosis over the last 7 years. Sepsis diagnosis was labeled by a combination of sepsis ICD codes and initial lactate elevation. We excluded transfers from outside hospitals, direct admissions for sepsis and patients diagnosed with sepsis in the emergency department. Data was extracted using Mayo Data Explorer, and data preparation and validation were performed using JMP Statistical Software and Python libraries. Feature selection was critical as we examined all data from previous contacts with healthcare, environmental factors, and dynamic trends of inpatient objective data; amongst 5,000 options of lab tests and vital measurements, we selected near 100 to reduce model complexity. We used XG Boost to train our model with a baseline cohort of 100 sepsis patients and 1000 patients without sepsis. Results We created a model that categorically classified patients into three sepsis risk level profiles (low-risk, medium-risk, high-risk) with performance metrics of a specificity of 97%, sensitivity of 65% and area under the receiver operating characteristic curve of 95%. Amongst laboratory data, lactate and creatinine had the highest feature importance (figure below). Our model also identified variables with the least importance to further refine our architecture. Conclusions Our model is one of the first sepsis risk stratification models whose algorithm is optimized for non-ICU inpatient wards, while the majority of similar studies were conducted on ICU and emergency department patients due to limited data availability. The model’s high specificity will allow for earlier sepsis recognition. By including our full cohort of 7,500 patients with sepsis and 35,000 patients without sepsis, we hope to improve class imbalance and increase sensitivity. By integrating transformer architecture, we seek to eliminate variables of low significance to create a model with more practical use, while maintaining high specificity. This abstract is funded by: None

Abstract Rationale Early diagnosis of sepsis continues to be a clinical challenge despite guideline-based early and serial assessments and integration of clinical and laboratory indices. Exhaled volatile organic compounds (VOC) have been shown to provide a rapid and non-invasive bedside diagnostic aid based on metabolism related to infection and the immune response. However, there is heterogeneous accuracy across different technological platforms. We hypothesized that a handheld electrochemical breath device could identify a VOC signature that would differentiate patients with sepsis from healthy controls. Methods We evaluated a handheld, non-invasive, bedside device that captures VOC signal in exhaled breath. We collected data from 20 patients with known sepsis secondary to pneumonia based on benchmark clinical and laboratory data, and 20 age- and sex-matched healthy controls in a pilot case-control design. The interactions between VOCs and the electrochemical sensor array within the device were measured over the course of one minute of breath collection from each subject. In this time, voltage was swept across the array periodically, with the capacitance of the sensor array changing with voltage and the VOC interactions. Several metrics were derived from the resulting capacitance-voltage curves, and ten were selected based on importance to be used as inputs into several unsupervised and supervised statistical learning methods. One of these methods was Principal Component Analysis (PCA), which is a dimensionality reduction technique that creates variables by linearly transforming the original inputs. These variables are known as components, and in this study, the majority of the original information was contained in the first two. These components were visualized in a 2-dimensional scatter plot, shown below (Figure 1). Results The generated PCA scatter plot showed distinct separation between sepsis and control subjects along the x-axis, or Principal Component 1 (Figure 1). Conclusion In this case-control pilot, a handheld electrochemical breath device showed biologically plausible separation between VOC signatures of patients with sepsis and healthy controls. More definitive diagnostic results would require a large cohort with sepsis mimics and head-to-head comparison with the standard of care (laboratory work-up and clinical scoring system) versus a hybrid approach of both. This abstract is funded by: milewski foundation

Abstract Introduction Sepsis, a dysregulated immune response to infection, accounts for nearly 11 million deaths worldwide each year and remains a major cause of hospital mortality. The absence of precision diagnostics limits efforts to characterize immune dynamics and predict clinical outcomes. We evaluated whether liquid biopsies collected at ICU admission could provide insight into sepsis biology and enable precision diagnostics. Methods We applied cell-free RNA (cfRNA) liquid biopsies as a noninvasive method to highlight signaling networks, identify tissue-specific injury, and predict immune exhaustion. We collected serial samples throughout hospitalization from a cohort of 100 patients admitted with likely sepsis to a medical ICU. Comprehensive clinical data, including inpatient laboratory values and key outcome measures such as survival and ventilator-free days, were curated. Circulating cfRNA was isolated and purified from these samples and prepared for sequencing. We generated data from 254 samples at a minimum sequencing depth of 30x. We then designed a novel deep-learning computational method to enable deconvolution to better analyze and interpret these data. Results In our cohort, a total of 84 patients were adjudicated to have sepsis by the Sepsis-3 criteria, and 25 patients died within 90 days. Differential analysis was performed comparing circulating cfRNA in these septic patients to that of healthy controls, stratified by mortality along with specified subgroups including shock on admission, ventilator dependence, and preexisting immunosuppression. We identified multiple differentially expressed transcripts between septic patients and healthy controls, with significant alterations in signaling cascades associated with mitochondrial signaling, including alterations in oxidative phosphorylation and fatty acid metabolism. Using defined ligand-receptor interaction databases, we identified key pathways associated with immune and endothelial dysfunction in sepsis. Specifically, our analysis identified numerous alterations in CXCL8 (IL-8)-associated signaling cascades (engaging CXCR1, CXCR2, SDC1-3, and ACKR). Our analyses also highlighted key tissue factor pathway inhibitor (TFPI)-associated signaling via interactions with tissue factor and low-density lipoprotein receptor-related protein 1 (LRP1). These analyses are corroborated by our new deep-learning augmented approach to deconvolution, where we demonstrate the identification of rare tissue- and cell-specific signals that are associated with increased mortality in our cohort. Conclusion Liquid biopsy approaches such as cfRNA profiling can provide insight into mechanisms underlying sepsis and may uncover underlying drivers of endothelial dysfunction. These findings support ongoing efforts to develop liquid biopsy-based diagnostics and personalized therapeutic strategies for patients at high risk for sepsis and related mortality. This abstract is funded by: NIH