CHEST

Background: Anxiety affects 22-56% of patients with COPD. It is independently associated with increased exacerbations, readmissions, and mortality. Medical hypnosis transiently alleviates state anxiety in severe COPD, and attenuates experimentally-induced dyspnoea in healthy volunteers. We aimed to assess the efficacy of hypnosis as adjunct therapy for anxiety during Pulmonary Rehabilitation (PR) versus an active comparator controlling for general motivation and relaxation. Methods. HYPNOBPCO_2 was a single-centre, phase 2, cluster-randomised, active-comparator, parallel-group, superiority trial done at Centre Hospitalier de Bligny, France. Adults +30 years with established COPD, mMRC dyspnoea grade +2, and +10 pack-years were eligible. Consecutive pulmonary rehabilitation cohorts (clusters) were randomly assigned (1:1) to medical hypnosis or structured relaxation, both adjunctive to a 4-week inpatient PR. The primary outcome was the six-item State-Trait Anxiety Inventory (STAI-6) at week 4, analysed in the intention-to-treat population. Secondary outcomes were sensory and affective dyspnoea (Multidimensional Dyspnea Profile sensory and affective sub-scales, COPD Assessment Test) and functional capacity (6-minute walk distance). A moderation analysis tested whether the hypnosis effect varied with baseline sensory and affective dyspnoea burden using Bayesian inference. This trial was registered prospectively (NCT04868357) and the protocol published. Findings. Between 27/09/2021 and 31/01/2024, 79 participants in 24 clusters were randomised (medical hypnosis n = 36, age 64.9 [8.3], 20 female; relaxation n = 43, age 67.4 [9.1], 23 female). Anxiety improved in both arms (deltaSTAI-6 = -5.72, posterior probability of reduction beyond MCID = 0.93). Medical hypnosis did not show an advantage over relaxation overall (deltaSTAI-6 = 0.95; posterior probability of reduction beyond MCID = 0.12). Medical hypnosis did show an advantage that scaled with baseline dyspnoea profile: in patients with high sensory and low affective burden, the predicted anxiety reduction relative to relaxation was larger and more probable (deltaSTAI-6 = -9.26; posterior probability of reduction beyond the 3-point MCID = 0.81). No clinically important safety issues were associated with either intervention and there were no deaths. Interpretation. Anxiety improved under both adjunctive mind-body interventions. The usefulness of hypnosis beyond relaxation was predicted by baseline dyspnoea profile, concentrating in patients with predominantly sensory burden. Future trials should focus on evaluating complementary interventions against burden phenotypes, ultimately paving the way for personalized interventions. Funding. Helebor Foundation; Agence Nationale de la Recherche.

We present our Stage-1 Registered Report as a full clinical trial article with all methods in past tense and including mock results, table and figures for the primary analysis. To remind the reader that this Stage-1 article is written before data collection, we highlight in color that these mock results are only for illustrative purposes and will be replaced by the actual results in the Stage-2 Registered Report. Background In patients experiencing out-of-hospital cardiac arrest, optimization of oxygen delivery during cardiopulmonary resuscitation is a critical. Although both positive end-expiratory pressure (PEEP) and zero end-expiratory pressure (ZEEP) are employed during CPR, their respective impacts on clinically relevant outcomes is yet to be clearly established. Methods This investigator-initiated, pragmatic, registry-based, multicenter, triple-blind randomized controlled superiority trial evaluates whether applying 8 cm H2O PEEP during cardiopulmonary resuscitation improves outcomes compared with ZEEP in adults with non-traumatic, non-drowning out-of-hospital cardiac arrest. Pre-randomized CPR kits (1:1 PEEP vs. sham) were used by ambulance sites during manual ventilation throughout the resuscitation process. The primary analysis was conducted in the principal stratum of patients who received either a supraglottic airway or endotracheal tube. The primary outcome was neurological status at hospital discharge measured by a utility-weighted score on the modified Rankin Scale. Secondary outcomes included prehospital return of spontaneous circulation, 30-day survival, and 6-month quality of life. The primary safety outcome was clinically significant pneumothorax.

ABSTRACT Background: Corticosteroids reduce mortality in severe COVID-19 requiring oxygen or invasive mechanical ventilation, yet emerging data suggest that SARS-CoV-2-associated acute lung injury is biologically heterogeneous and that treatment response may vary across molecularly defined disease states. Lung-derived molecular endotypes of severe COVID-19-associated acute lung injury have been described, but direct molecular profiling is not routinely available at the bedside. We evaluated whether a clinical predictor of previously defined lung molecular endotype identifies heterogeneity in corticosteroid treatment effect among mechanically ventilated patients with COVID-19. Methods: We utilized a single-center cohort of 5,000 patients with COVID-19 treated at the University of North Carolina Hospital between January 1, 2020, and December 31, 2022, to emulate a target trial assessing the effect of corticosteroid receipt on mortality, length of stay, and incident organ support. Confounding was addressed through inverse probability of treatment weighting (IPTW). Outcomes for severely ill patients requiring mechanical ventilation were compared to the RECOVERY trial results, with subsequent moderation analysis and stratified analysis by clinically predicted lung molecular endotype and vaccination status. The primary outcome was 28-day mortality. Secondary Outcomes were time to discharge alive and progression to additional organ support. Results: This emulated target trial showed a directionally favorable but non-statistically significant association between corticosteroid treatment and reduced 28-day mortality in patients requiring mechanical ventilation for SARS-CoV-2 infection. A clinical predictor of lung molecular endotype moderated the effect of corticosteroids on 28-day mortality (p-value for interaction 0.038) and identified distinct predicted endotype-specific treatment effect. Corticosteroid treatment was associated with lower 28-day mortality in the predicted Hyper-Inflammatory endotype (OR 0.62, 95% CI 0.39, 0.99) but not in the predicted Metabolic Dysregulation endotype (OR 1.15, 95% CI 0.82, 1.61). We did not detect significant effect modification by vaccination status (p-value for interaction 0.65), although inference was limited by the small, vaccinated subgroup (28-mortality OR 0.78, 95% CI 0.37, 1.65 in vaccinated vs 0.94, 95% CI 0.70, 1.26 in unvaccinated). Conclusions: In this target trial emulation of mechanically ventilated patients with severe COVID-19, corticosteroid treatment showed a directionally favorable but non-statistically significant association with reduced 28-day mortality in the overall cohort. However, a clinical predictor of lung molecular endotype identified significant heterogeneity in treatment effect, with benefit concentrated in the predicted Hyper-Inflammatory endotype and no apparent benefit in the predicted Metabolic Dysregulation endotype. These findings support prospective validation of clinically deployable endotype-guided corticosteroid treatment strategies in acute lung injury and ARDS.

Despite its high prevalence and the discovery of hundreds of genetic associations, the genetic determinants and heterogeneous manifestations of asthma remain incompletely understood. Incorporating polygenic risk scores (PRS) into asthma research offers a powerful approach to quantify inherited susceptibility, refine risk profiles, and advance mechanistic understanding of disease development. For this study, we leveraged whole-genome sequencing (WGS) data from two family-based cohorts of childhood asthma - the Genetics of Asthma in Costa Rica Study (GACRS) and the Childhood Asthma Management Program (CAMP) - to examine the transmission profiles of externally derived asthma PRS and their associations with clinical phenotypes in children with asthma. To further elucidate molecular mechanisms, we integrated large-scale external genome-wide association study (GWAS) summary statistics and genetic prediction models of protein abundance in a two-step proteome-wide association study (PWAS) of asthma. Our findings provide robust evidence supporting the validity of externally derived asthma PRS (asthma PRS association p-value p={10}^{-24} [GACRS and CAMP trios combined] for the Global Biobank Meta-analysis Initiative [GBMI]) and reveal consistent associations with spirometry measures and atopy markers across both studies, as 13 of 21 traits (62%) were significantly associated with the GBMI-PRS in the meta-analysis after multiple-testing correction. Moreover, the results of the integrative proteomic analysis implicate IL-1 signaling in the etiology of asthma, reinforcing the candidacy of IL1R1 antagonists for drug repurposing.

Background Hypercapnia may indicate a primary ventilatory syndrome, a complication of another illness, or an epiphenomenon of severe disease. The presenting context of hypercapnia is poorly quantified, limiting clinical interpretation and synthesis of epidemiologic studies. Methods We performed a retrospective cross-sectional study of Medical Information Mart for Intensive Care IV (MIMIC-IV) hospital admissions linked to an emergency department (ED) presentation from 2011 through 2019. Admissions were included if the triage chief complaint was not missing and at least one prespecified criterion for hypercapnia was met: an International Classification of Diseases (ICD) code for hypercapnic respiratory failure or obesity hypoventilation syndrome, arterial blood gas (ABG) PCO2 45 mmHg, venous blood gas (VBG) PCO2 50 mmHg, or indeterminate-source blood gas PCO2 50 mmHg. Triage chief-complaint text was classified by natural language processing (NLP) into 17 National Hospital Ambulatory Medical Care Survey reason-for-visit (RFV) categories using a multi-label framework. Primary analyses estimated admission-level RFV category prevalences; secondary analyses compared distributions by overlapping ascertainment indicator, age, and acidemia. Results The total cohort included 11,941 admissions: 1,542 (12.9%) met both blood-gas and ICD-code criteria, 9,958 (83.4%) met blood-gas criteria only, and 441 (3.7%) met ICD-code criteria only. Median age at admission was 68 years (IQR 56-78), and 6,423 admissions (53.8%) were for male patients. Respiratory RFV categories were most prevalent (30.2%), followed by administrative reasons (17.5%), digestive symptoms (14.0%), injuries and adverse effects (14.0%), and nervous-system symptoms (13.8%); categories were not mutually exclusive. Respiratory categories were more common in ICD-positive admissions (50.2%) than in VBG-defined (36.3%) or ABG-defined admissions (27.3%). Injuries and adverse effects were most prevalent among admissions for patients aged 18-39 years (34.4%), whereas respiratory categories increased from 13.7% among admissions for patients aged 18-39 years to 36.5% among admissions for patients aged 80 years. NLP-derived classifications showed mean set-F1 of 0.84 against adjudicated clinician labels in the full annotated benchmark sample. Conclusions Among ED-linked admissions with hypercapnia by diagnosis code, blood gas, or both, respiratory complaints were the most common chief-complaint category but represented fewer than one-third of admissions. Presentation context should be incorporated when defining, comparing, and interpreting hypercapnia cohorts, particularly those ascertained by blood-gas criteria.

Background: Chronic obstructive pulmonary disease (COPD) is a leading cause of global morbidity and mortality, and its heterogeneity demands better biomarkers of severity and progression risk. Extracellular vesicles (EVs) are promising blood-based biomarkers, but have not been examined for COPD severity and outcomes in a large multicentre cohort. Methods: We analysed 600 COSYCONET participants (up to 54 months of follow-up). EV surface markers were profiled with the MACSPlex EV Kit IO. Cross-sectional associations with severity (GOLD, FEV1) were primary (ordinal and linear regression); longitudinal trajectories and all-cause mortality were prespecified exploratory endpoints. Results: Six EV markers showed robust associations with cross-sectional severity: CD29, CD49e and CD31 increased with severity (a cell-adhesion/matrix-remodelling signal), whereas CD81 and CD8 decreased; HLA-ABC (increasing) was less specific. No marker was linked to FEV1 decline. After FDR correction, lower levels of three markers with higher 54-month mortality (all HR<1): CD25 (HR 0.77, 95% CI 0.65-0.90, q=0.018), CD56 (HR 0.75, 95% CI 0.63-0.89, q=0.018) and CD142 (HR 0.74, 95% CI 0.60-0.90, q=0.024). CD25 and CD142 also improved reclassification, CD56 did not; a CD25 + CD69 combination showed the largest incremental signal ({Delta}C 0.017, 95% CI 0.002-0.032, p=0.027). Conclusion: Circulating EV surface markers are associated with cross-sectional COPD severity. Exploratory analyses nominate CD25, CD142 and CD25 + CD69 as candidate prognostic markers requiring external validation, suggesting minimally invasive EV profiling could complement clinical assessment in COPD.

Background Agenda-setting is a fundamental patient-centered communication practice in which a clinician works with a patient to elicit, propose, and organize topics for discussion during a clinical encounter. Various agenda-setting interventions have been developed, including patient-facing tools and clinician training, but their effects have not been systematically evaluated. We aimed to determine the effects of these interventions on encounter, patient, care partner, and clinician outcomes. Methods We searched grey literature and seven databases, including PubMed, from inception through July 2025 for randomized and non-randomized comparative studies of interventions designed to promote or improve clinical visit agenda-setting. Two reviewers independently screened articles and extracted data, with a third reviewer resolving conflicts. We assessed risk of bias using RoB 2 for randomized studies and ROBINS-I for non-randomized studies. We conducted random effects meta-analyses when outcomes were sufficiently comparable, assessed heterogeneity using I2, and rated certainty of evidence using GRADE. Post hoc exploratory subgroup analyses examined study design, adjustment status, and intervention structure. Results Twenty-nine articles describing 22 unique studies met the inclusion criteria, including 13 randomized and nine non-randomized studies. Agenda-setting interventions increased the occurrence of agenda-setting (risk ratio 5.43, 95% confidence interval (CI) 2.06 to 14.28, I2=34.6%) and favored the intervention for concerns addressed when measured as a continuous outcome (standardized mean difference (SMD) 0.37, 95% CI 0.16 to 0.57, I2=65.3%) and overall clinician satisfaction (SMD 0.50, 95% CI 0.23 to 0.78, I2=0.0%). There were no clear differences in the number of concerns raised (mean difference (MD) 0.21, 95% CI -0.19 to 0.61, I2=59.6%), visit duration (MD 0.64 minutes, 95% CI -0.83 to 2.12, I2=51.4%), or overall patient satisfaction (SMD 0.05, 95% CI -0.05 to 0.15, I2=47.0%). Potentially important heterogeneity was present for four of these six outcomes. Post hoc exploratory subgroup analyses did not provide clear evidence that effects varied by study design, adjustment status, or intervention structure. Risk of bias was often high, serious, or critical, and certainty of evidence was low or very low for all pooled outcomes. Conclusions To our knowledge, this is the first comprehensive synthesis of clinical visit agenda-setting interventions. Such interventions may increase the occurrence of agenda-setting and the extent to which patient concerns are addressed without increasing visit length. However, the certainty of evidence was low or very low, and the available evidence does not establish a superior intervention structure.

Problem Authentic patient encounters are the raw material of clinical learning, yet the educational resources learners receive are rarely keyed to the diagnoses in front of them, creating temporal and cognitive gaps. Precision medical education (PME) proposes delivering the right resource to the right learner at the right moment, but practical implementation in the clinical learning environment remains limited. Approach We developed DxMentor, an electronic health record (EHR)-integrated platform that captures each learner's daily inpatient diagnostic exposures from documented International Classification of Diseases, Tenth Revision (ICD-10) codes. Artificial intelligence (AI) is used to match each diagnosis to an educator-curated formulary of micro-learning resources and board-style questions, and to PubMed-derived primary and synthesis literature converted into plain-language evidence summaries. A personalized email "nudge" is delivered before morning rounds, copying supervising attendings for residents, with engagement tracked longitudinally. We report implementation outcomes from July 2024-April 2026. Outcomes DxMentor evaluated 32,846 encounters from 335 medical students and 346 internal medicine residents, delivering 17,340 nudges containing 63,754 didactic resources, 17,038 question sets, and 23,594 summarized articles for approximately $390 in AI token costs. In a benchmarking sample, 91.5% (366/400) of diagnosis-resource pairs were rated relevant by physician-educators. Overall, 78.5% (12,393/15,793) of nudges were opened and 11.3% (1,955/17,340) had at least one click. Engagement was higher among residents than students (open: 80.7% vs. 65.8%; click-through: 12.7% vs. 3.1%; both P < .001), with substantial between-learner variability. Next Steps Email opens and clicks are engagement proxies rather than measures of learning. We are therefore linking nudges to educational outcomes, testing alternative recommendation strategies and timing, and expanding to additional specialties and ambulatory and surgical settings.

Background: The 2026 American Heart Association/American College of Cardiology (AHA/ACC) guidelines replaced the 2019 European Society of Cardiology (ESC) four-tier pulmonary embolism (PE) risk scheme with five clinical categories (A-E) and subcategories. These categories were set by expert consensus and have not been validated against outcomes. How patients are reclassified relative to ESC, or how the two systems compare prognostically, is unknown. Methods: We utilized three cohorts of patients with confirmed PE using structured electronic health record data, laboratory biomarkers, and large-language-model abstraction of radiology reports: Duke University Health System (n=12,992, drawn from 95,760 consecutive inpatient CT pulmonary angiography studies, 2014-2025, with no referral or registry enrollment step between imaging and cohort entry), INSPECT (Stanford; n=3,870), and MIMIC-IV (Beth Israel Deaconess; n=361). Patients were assigned AHA/ACC categories B through E, subcategorized where data allowed, and mapped to 2019 ESC risk strata. The primary outcome was 30-day mortality; discrimination was assessed with Harrell C-index. Results: Among 17,223 patients with confirmed PE, pooled 30-day mortality rose monotonically across categories: 1.5% (B), 8.9% (C), 15.5% (D), and 31.9% (E), with the ordering preserved in all three cohorts despite differing baseline mortality. Subcategory-level discrimination was reliable only at the high-acuity extreme (D2-E2); across subcategories C1 through D1, mortality did not order monotonically (9.2%, 10.8%, 8.1%, 10.9%), and adding subcategories to category C did not improve discrimination at Duke (C-index 0.699 vs 0.699). Category C patients lacking both echocardiography and biomarker testing (12.7% of category C) had mortality (10.4%) equal to or exceeding classified peers. Relative to ESC, the frameworks were concordant at the extremes, but 5.7%of ESC intermediate-risk patients were reclassified to category D, with modestly higher but non-significant 30-day mortality than those remaining in category C (10.8% versus 8.9%). Conclusions: Across a three-health-system cohort, the 2026 AHA/ACC framework produced a reproducible mortality gradient at the category level, with added subcategory granularity refining risk chiefly at the highest-acuity tiers. Discrimination across the broad intermediate band was limited, and reclassification from ESC fell almost entirely within this range.

Background Elexacaftor-tezacaftor-ivacaftor (ETI) has been demonstrated to improve lung function in clinical trials; however, evidence describing effects on trajectories and whether long-term improvements are sustained (>1-year) is lacking. We estimated within-person lung clearance index (LCI) trajectories before and after ETI initiation, assessing changes in level and rate of change, alongside acute LCI change, up to three years after ETI initiation. Methods Prospective observational study of children at a tertiary hospital. Children aged 3-17 years with [&ge;]2 LCI testing occasions (i) before and (ii) after starting ETI were used to describe lung function trajectories. Children with [&ge;]1 pre-ETI and [&ge;]1 post-ETI LCI occasion(s) were used to describe acute LCI change after ETI initiation. Age-adjusted LCI trajectories for time periods (i) before and (ii) after ETI initiation were estimated using linear mixed-effects models, and pre- and post-ETI LCIs were compared using paired Wilcoxon tests. Results Mean pre-ETI and post-ETI longitudinal changes in LCI were -0.007 (95% CI: -0.28, 0.27; n=35) and 0.12 (95% CI: -0.17, 0.41; n=20) turnovers per year, respectively. Before ETI initiation, 57% (30/53) of patients had an LCI[&ge;]7.1 turnovers (indicating impaired lung function), compared to 26% (14/53) post-ETI, with a median LCI difference of -0.70 (95% CI -0.84, -0.46; p<0.001) turnovers. Within-individual variability in LCI decreased post-ETI. Conclusions Our real-world data within a unique longitudinal study provide a comprehensive picture of ETI benefit by outlining not only acute improvement in LCI but maintained stability in LCI trajectories and improved LCI stability sustained up to three years post-initiation.

Introduction Aspiration events in hospitalized adults are common and linked to substantial morbidity, mortality, and healthcare burden. While antiemetics have been studied for aspiration prevention in specific settings, evidence for their broader preventive use in hospitalized adults is limited. We conducted a systematic review and meta-analysis to evaluate the effect of prophylactic scheduled antiemetics on aspiration events in adult inpatients. Methods: Ovid MEDLINE, Ovid Embase, CINAHL, and Cochrane Library (via Wiley) were searched in May 2025. We included randomized controlled trials (RCTs) and observational studies assessing prophylactic scheduled antiemetic use in hospitalized adults, with aspiration events as the primary outcome. Secondary outcomes were aspiration pneumonia, hospital length of stay, increased oxygen requirement, ICU admission, and mortality. Two investigators screened and independently extracted data in duplicate using standardized data collection forms. Extracted information included study characteristics, patient demographics and clinical characteristics, interventions, and outcomes. Results: Three RCTs met inclusion criteria (n = 515 patients; 237 antiemetic, 278 placebo). Pooled analysis of two RCTs demonstrated an 88% relative risk [RR] reduction of aspiration events; (2.8% [3/106] prophylactic antiemetic vs 27.9% [29/104] placebo; RR = 0.12, 95% confidence intervals [CI]: 0.02-0.73, p <0.0001, low certainty) in the antiemetic group. Pneumonia rates were also lower in the antiemetic group although they did not reach statistical significance (16.5% vs 32.4%; RR 0.44, 95% CI 0.15-1.28, P = 0.13, low certainty). ICU admission rates were lower in the antiemetic group (2.6% [2/76]) vs. placebo (23% [17/74]); RR = 0.11, 95% CI: 0.03-0.48, p=0.003, very low certainty). Mortality was similar between groups (35.0% vs 38.1%; RR 1.02, 95% CI: 0.84-1.24, P = 0.85, low certainty). No adverse events were reported among all studies. Conclusion: Prophylactic scheduled antiemetics were associated with a significant reduction in aspiration and ICU admission. There was a non-significant but favorable trend towards reduction of pneumonia among hospitalized adults. Larger, high-quality trials are needed to clarify their role in aspiration prevention.

Rationale Airway remodelling (AR) contributes to airflow limitation and poor symptom control in severe asthma. While anti-IL-5 therapy improves clinical outcomes in severe asthma, the cellular and molecular mechanisms underlying its effects on AR remain incompletely understood. Objectives. To determine whether IL-5 blockade directly modulates airway epithelial biology and contributes to attenuation of AR in severe asthma with eosinophilia (SAE). Methods. Patients with SAE underwent bronchoscopy before and after 24 weeks of anti-IL-5 therapy. Paired bronchial brushings (n=12) were analysed using single-cell RNA-sequencing. Histological features of AR were assessed in paired bronchial biopsies (n=16). Functional effects of IL-5 were investigated using wound healing assays in differentiated air-liquid interface (ALI) cultures. Measurements and Main Results. Anti-IL-5 treatment improved clinical outcomes without altering airway epithelial cellular composition. Differential gene expression was predominantly restricted to bronchial ciliated epithelial cells, which expressed IL5RA. ALI cultures showed IL-5R protein. Anti-IL-5 therapy induced a transcriptional signature in ciliated cells that opposed IL-5-responsive genes. Pseudotime analyses demonstrated preserved epithelial differentiation trajectories but altered programmes related to mucus regulation and ion transport. Cell-cell communication analyses revealed decreased T2-inflammatory processes alongside enrichment of epithelial repair and barrier integrity processes after treatment. Functionally, IL-5 directly impaired epithelial wound repair in ALI cultures. Histological assessment demonstrated increased epithelial E-cadherin expression and reduced sub-basement membrane thickness, extracellular matrix deposition and goblet cell hyperplasia in bronchial biopsies. Conclusions. IL-5 blockade modulates epithelial biology at transcriptional, functional and structural levels in SAE and is associated with improved epithelial integrity and reduced features of AR.

Background. A primary constraint on the capacity of EMS programs to meet industry demand is psychomotor instruction and verification, requiring direct observation of each student by a qualified evaluator. Whether AI video analysis can relieve it is untested; none has been applied to EMS skill examination or compared with human examiners. Objective. To quantify human EMS evaluator inter-rater reliability and evaluate an AI video-analysis platform against it. Methods. In a prospective, fully crossed study, five certified EMS evaluators and an AI platform independently scored identical video-recorded EMT performances of cervical collar application (n=15), bag-valve-mask (BVM) ventilation (n=14), and medical assessment (n=15) on dichotomous checklists with critical-failure criteria. Agreement was assessed at item, score, and decision levels using Fleiss' kappa, Krippendorff's alpha, Gwet's AC1, and ICC(2,1)/ICC(2,k). Results. Human item agreement was moderate (kappa 0.409 to 0.467), as was single-rater reliability (ICC(2,1) 0.539 to 0.694), against good panel reliability (ICC(2,k) 0.854 to 0.919). Recorded pass/fail agreement was fair (kappa 0.297 to 0.388) and critical-failure agreement near zero for two skills (kappa 0.028, 0.119). AI alignment tracked rubric observability rather than task complexity: r = 0.857 (collar, exceeding every human), -0.173 (BVM), 0.664 (medical), and it was most lenient on two skills. Conclusions. Human evaluators are an imperfect standard, especially on critical failures. The AI was a legitimate additional rater where checklist items were discrete and visually verifiable, but not where credit required judging continuous quantities such as ventilation rate, volume, or suction duration. Defensible uses are formative and archival, not summative. These results reflect an early, non-specialist configuration: a baseline, not a limit.

RATIONALE: Airway mucus plugging is a clinically relevant manifestation of airway pathology in chronic obstructive pulmonary disease (COPD) and is associated with increased mortality even in early disease; however, visual computed tomography (CT) assessment is subjective and labor intensive. OBJECTIVES: To develop an AI-based quantitative CT method for automated detection of airway mucus plugging and evaluate associations with physiologic impairment and clinical outcomes. METHODS: Inspiratory CT scans from 8,971 COPDGene Phase 1 (GOLD 0-4 and PRISm) participants were analyzed. An AI-based framework combining 3D airway segmentation discontinuities and convolutional neural network classification identified mucus plug obstructions, yielding mucus plug burden (total plug count). Associations with outcomes were evaluated using covariate-adjusted models. MEASUREMENTS AND MAIN RESULTS : Higher mucus plug burden was associated with lower post-bronchodilator FEV % predicted ({rho} = -0.41; P < 0.001), greater air trapping (LAA < -856 HU; {rho} = 0.33; P < 0.001), worse health status (SGRQ; {rho} = 0.31; P < 0.001), and shorter 6-minute walk distance ({rho} = -0.26; P < 0.001). Among GOLD 1-4 participants, mucus plug presence was independently associated with increased all-cause mortality (adjusted hazard ratio, 1.28; P < 0.005) and exacerbation frequency (adjusted incidence rate ratio, 1.32; P < 0.005). Plug presence was also associated with increased respiratory mortality across GOLD categories and cardiovascular mortality in GOLD 1-2. CONCLUSIONS: AI-based quantitative CT assessment of airway mucus plugging provides a scalable, reproducible measure associated with physiologic impairment and adverse outcomes in COPD, supporting its role in risk stratification and future therapeutic studies.

Objective: Patient-ventilator dyssynchrony (PVD) is a common and clinically consequential problem in critically ill patients receiving invasive mechanical ventilation. Yet automated identification of PVD subtypes at scale remains an unmet clinical need, owing to the lack of large annotated bedside waveform datasets. Methods: We developed and validated a semi-supervised algorithm for automated annotation of PVD. In two medical ICUs at a tertiary academic center, bedside devices continuously collected airway flow and pressure waveforms from the ventilators. We developed a software interface with an information retrieval system that grouped similar breaths for expert human review, yielding 1,542,296 labeled breaths across eight categories: 2 labels for breath delivery mode, 5 labels for PVD subtypes, and 1 label denoting a normal breath. Two pulmonary physicians with expertise in ventilator training and education provided the expert reference labels. We trained an initial classification model on a model-derivation set of 771,148 breaths (divided into training and validation) and evaluated it on a hold-out test set of 771,149 breaths A semi-supervised approach was utilized to extend labeling to an additional 12,965,000 unlabeled breaths. Results: The supervised model performed well across all labels, with Macro-F1 scores between 0.96 and 1.00. Semi-supervised learning across 12 rounds expanded the training set from 771,148 to 8,563,995 breaths without significant performance degradation. Conclusion: We developed a practical and scalable system for automated PVD annotation that performed well across all subtypes. This work provides a reproducible foundation for automated PVD labeling to support the development of machine-learning-based clinical decision support systems for identifying patient-level asynchrony.

Abstract Introduction In-hospital cardiac arrest carries high mortality despite standardized ACLS training. Educators face increasing time constraints in developing assessment tools for ACLS training. Two possible solutions to this problem are using pre-medical students or using artificial intelligence to generate test questions. This study compared the quality of pre-medical student-generated ACLS test questions vs. AI-generated ACLS test questions, testing the hypothesis that AI-generated questions are non-inferior to student-generated questions. Methods Ten pre-medical students created ACLS questions following predefined criteria, while an AI model (Northwell's Artificial Intelligence Hub) generated comparable questions. A blinded ACLS-certified physician evaluated questions on the qualities of Alignment, Clarity, Cognitive Level, and Question Design using a standardized rubric (Likert scale: 1 = poor quality, 5 = excellent). Student's T-test and Chi-square analysis were used to compare the quality of questions on different rubric domains within each arm (student vs. AI) and within one domain (eg, question Clarity) between arms. The Student's T test was used when 2 comparator groups were compared (eg, Clarity of student-generated vs. AI-generated questions) within one arm. The ANOVA test was used when comparing more than 2 comparator groups (eg, Alignment vs. Clarity vs. Cognitive Level) within one arm. Statistical significance was set as a priority at p <0.05. Results Both student-generated and AI-generated questions were of high quality. AI-generated questions achieved the maximum score in the domains of Alignment, Clarity, and Question Design, but fell short of perfect scores in the domain of Cognitive Level (8 of 50 questions were less than 5). Student-generated questions achieved less-than-perfect scores in each domain. No significant difference was found in overall mean question scores between groups (students = 4.79, AI = 4.81; p = 0.9). However, AI-generated questions had significantly-greater Clarity (students = 4.8, AI = 5; p = .0461), while Alignment, Cognitive level, and Question Design showed no significant differences. Conclusion AI-generated questions demonstrated overall quality comparable to those generated by pre-medical students, supporting the potential role of AI as a scalable tool in ACLS educational assessment development. Further studies are warranted to evaluate additional AI platforms and determine optimal integration of AI in medical education assessment design.

Background and Objective: Diabetes mellitus (DM) causes autonomic neuropathy, which may alter nocturnal respiratory rate (NRR). To test the association between DM and NRR, we analyzed elective polysomnograms of four large observational cohorts. Research Design and Methods: We performed cross-sectional analysis of over 25,000 individuals with polysomnograms (PSGs) from the Sleep Heart Health Study (SHHS), Hispanic Community Health Study/Study of Latinos (HCHS/SOL), Osteoporotic Fractures in Men Study (MrOS), and Wisconsin Sleep Cohort (WSC). Patient-level NRRs were derived from inductance plethysmography waveforms. DM status was determined by self-report, physician diagnosis, medication use, or laboratory values, depending on the cohort. We related DM and NRR (continuous and dichotomized) using logistic regression models and adjusted for potential confounders. Cohort-specific results were combined using random-effects meta-analysis. Results: Meta-analysis of unadjusted models showed a pooled odds ratio (OR) of 1.10 (95% CI:1.04-1.17) for each breath-per-minute (brpm) increase in NRR. This association remained significant after multivariable adjustment (OR:1.06, 95% CI:1.02-1.11). Dichotomized analyses similarly showed higher odds of DM across dichotomization thresholds ranging from 15 to 21 brpm. At a threshold of 18 brpm, the unadjusted pooled OR was 1.77 (95% CI:1.23-2.55, P=0.0022), and the adjusted OR was 1.49 (95% CI:1.10-2.02, P=0.0098). Conclusions: Clinically stable outpatients with elevated NRR have an increased prevalence of DM. Additional studies are needed to investigate whether the mechanism is autonomic neuropathy and whether monitoring NRR can detect early complications of DM.

Rationale: Pulmonary hypertension is defined by pulmonary hemodynamics, but diagnostic and prognostic biomarkers remain limited. Nuclear magnetic resonance (NMR) spectroscopy provides detailed insights, particularly in the lipid metabolism. Objectives: To explore circulating NMR-derived metabolites and lipoprotein-related parameters for their association with pulmonary hemodynamics and to analyse their prognostic properties in pulmonary arterial hypertension (PAH). Methods: Retrospective analysis of a PAH cohort with complete diagnostic workup including right heart catheterization and baseline serum samples, from the prospective GRaz Pulmonary Hypertension-Metabolism (GRAPH-M) registry. Measurements: NMR-derived metabolites and lipoprotein-related parameters were analyzed for their association with clinically relevant parameters of PAH. We defined PHIHDL, a score derived from high-density lipoprotein (HDL) related measures based on their strong association with pulmonary hemodynamics, and evaluated its prognostic value. Results: We included 100 patients with PAH treated at the PH clinic of LKH University Hospital, Medical University of Graz, between 2011 and 2021. Age was 61{+/-}15 years, female/male ratio 2.5, BMI 26 {+/-}7 kg/m2, mPAP 41{+/-}16 mmHg, PAWP 8.8{+/-}3.2 mmHg, PVR 8.0{+/-}4.9 WU, and median survival was 8.0 years. During follow-up, 46 patients died. We identified a cluster of 12 HDL-related measures that showed significant inverse association to pulmonary hemodynamics and derived PHIHDL from the reversed scaled average of these particles. PHIHDL was associated with all-cause mortality after adjustment for age and sex (HR 2.96, 95% CI 1.52-5.70), independent of the clinical risk scores COMPERA 2.0 and REVEAL Lite2. Conclusion: PHIHDL, a pulmonary hemodynamics-based metabolomic score, provides independent prognostic information beyond established risk scores in PAH.

In idiopathic pulmonary fibrosis (IPF), the lung is remodeled through coordinated epithelial, stromal, and immune-associated programs, but individual transcriptomic cohorts are often too small to separate shared disease signals from demographic and study-level variation. To increase statistical power while preserving study-aware interpretation, we integrated raw bulk lung RNA sequencing (RNA-seq) data from five well-annotated studies and analyzed 223 samples in a common framework that modeled sex, age, library layout and repeated sampling. IPF showed a broad and reproducible expression shift, with 2,443 genes meeting the differential-expression threshold of false discovery rate (FDR) <0.05 and absolute log_2 fold change at least 1. The dominant program combined extracellular matrix remodeling, stromal and epithelial activation, complement and B-cell-related pathways, cilium-associated processes, and relative depletion of oxidative phosphorylation and proteasome pathways. Sex-stratified analyses recovered a shared fibrotic core with smaller sex-skewed components, whereas age-related disease effects were weaker and centered on immune activation. A leave-one-study-out elastic-net analysis using fixed disease-gene panels classified IPF across held-out studies, supporting cross-study portability of the core signature. This integrated reanalysis strengthens evidence for a stable matrix-immune IPF program and reinforces the view that core disease-associated transcriptional programs are reproducible across heterogeneous cohorts.

Rationale. Racial disparities in outcomes among patients with acute respiratory failure are well-described, but the contributions of clinicians to these disparities have not been evaluated. Objectives. Among mechanically ventilated patients, we evaluated racial disparities in severity of illness trajectories and adapted value-added modeling to quantify nurse and physician relationships with these disparities. Methods. In a retrospective cohort of mechanically ventilated patients across five hospitals between 2018 and 2022, we used generalized estimating equations to model the change in Laboratory-based Acute Physiology Score version 2 (LAPS) from the start to end of intensive care unit admission ({Delta}LAPS). Consistent with value-added modeling, we randomly allocated the cohort into development and testing partitions, and fit separate multiple linear regression models of {Delta}LAPS using concurrent nurse and physician assignments (determined at 4-hour intervals), patient race, and clinician-race interaction terms as fixed effects. Clinician-specific and clinician-race interaction coefficients were extracted to determine race-specific value-add for each clinician. We defined the race-contextual value-add difference (RCVAD) as a clinician-level measurement of the difference in that clinician's value-add between Black and White patients in their care; a positive RCVAD indicates a more favorable severity of illness trajectory for Black relative to White patients and vice versa. Measurement and Main Results. Among 6,555 distinct patients, 7,247 clinical encounters, 405 nurses, and 70 physicians, Black patients accounted for 2,926 (40%) encounters. Overall, Black patients had significantly less improvement in {Delta}LAPS than White patients (difference in LAPS decline = 2.26 [0.23, 4.29], p=0.029). In the development partition, median nurse RCVAD was -0.10 (interquartile range [IQR]: -1.17, 1.14) with 191 (47%) nurses having a positive RCVAD; median physician RCVAD was -0.18 (IQR: -1.34, 0.56) with 29 (41%) having a positive RCVAD. Conclusions. Black mechanically ventilated patients experience less improvement in severity of illness during intensive care unit admission than White patients. While the majority of physicians and nurses were associated with disparities-exacerbating illness trajectories, many other clinicians were associated with disparities-mitigating trajectories. Future work to understand practices associated with disparities-exacerbating and disparities-mitigating care profiles could inform interventions to reduce disparities overall.