Annals of the American Thoracic Society

Background: Aging has a critical role in lung changes and the outcome of lung disease. Several lung aging equations have been proposed to measure deviation from physiological aging of the respiratory system. In this study, we aimed to develop a single measure of accelerated lung aging and show its application as a measure of lung aging. Method: We used a pre-bronchodilator pulmonary function test (PFT) from NHANES adult participants recruited from 2007 to 2011. We applied Klemera-Dubal Method (KDM) to four PFT measurements, FEV1, FVC, FEF25-75, and PEF, to calculate a measure of lung biological aging. Physiological Aging of the Respiratory System (PARS) was calculated from the residual method vs. chronological age. We tested the construct validity of PARS by measuring its association with risk factors of lung health. The prognostic validity was measured using a survival analysis. Sampling weights were applied to all analyses. Results: In 14,123 adult participants, the mean (SD) of accelerated lung age (PARS) was 0 (8.2) years. Participants with a history of asthma and emphysema had 4- and 10-year higher PARS. Cigarette smoking, lower socioeconomic status, black race, higher serum cadmium, and lower serum selenium and magnesium were associated with higher PARS. During 116 months of follow-up, PARS was associated with a higher mortality (HR = 1.06, 95%CI: 1.05-1.07 per year). Females with higher PARS had a higher risk of death (P for interaction < 0.001). Results were consistent across different subgroups and sensitivity analyses. Conclusion: PARS is a noninvasive lung aging marker and can be applied as a single measure of lung accelerated aging in the adult population. Its strong construct and predictive validity support its future application among different populations with and without lung disease.

Open air burn pits were used extensively during military operations in Iraq and Afghanistan, potentially exposing millions of US Veterans to toxic airborne hazards. Many of the airborne toxins released have been shown to induce lung inflammation and lung injury and are mutagenic. This is the first large-scale study of associations between self-reported burn pit exposures and the development of cancer. Using data from the Airborne Hazards and Open Burn Pit Registry, we found that Veterans reporting burn pit exposures are associated with a higher odds of developing cancer. However, investigations into the development of specific type of cancer and into a burn pit exposure dose-response effect were inconclusive.

Background: Nitrogen dioxide (NO2) is a surrogate for traffic and industrial air pollution associated with adverse respiratory outcomes. Whether elevated NO2 and temperature jointly influence adult-onset asthma (AOA) risk is unclear, especially among subgroups with varying lifestyle and exposure profiles. We investigated further in the prospective All of Us research program. Methods: Among 596,926 U.S. participants who consented to electronic health record release, annual average NO2 concentrations from satellite data were linked to residential locations for 376,535 individuals. We used multivariable Cox regression to estimate associations between NO2, temperature, and incident AOA, adjusting for co-pollutants and potential confounders. We analyzed 4-category cross-classification variables between NO2 (high>75th percentile vs. low<=75th percentile) and maximum or average temperature (high>median vs. low<=median). We also stratified by sex, age, income, and smoking status. Additive interactions were estimated using Relative Excess Risk due to Interaction, Attributable Proportion, and Synergy Index. Results: We identified 10,413 incident AOA cases over an average 4-year follow-up. Participants with the highest categories of NO2 and temperature exposure had significantly higher risk compared to those with the lowest (HRHigh NO2 x High Max. Temp.=1.37, 95%CI:1.26-1.49; HRHigh NO2 x High Average Temp.=1.49, 95%CI:1.38-1.61). The joint association of high NO2 and high maximum temperature was more pronounced among ever-smokers (HR=1.59, 95%CI:1.40-1.81) than never-smokers (HR=1.26, 95%CI:1.13-1.41). Interaction analyses supported super-additive interactions of high NO2 and high average temperature on AOA risk, particularly among ever smokers, lower-income participants, and younger adults. Conclusion: Our findings highlight the respiratory health threat of long-term joint exposure to elevated NO2 and average temperature, particularly among vulnerable subgroups.

Clonal hematopoiesis of indeterminate potential (CHIP) represents the age-related expansion of hematopoietic stem cells with preleukemic mutations. However, its association with all-cause and cause-specific mortality has not been well characterized in older adults. We aimed to evaluate whether CHIP is associated with all-cause and cause-specific mortality in a population of older women in the United States. Our study included 6,704 participants in the Women?s Health Initiative Long Life Study (WHI-LLS) without hematologic malignancy. The co-primary exposures were any CHIP (variant allele frequency [VAF] [&ge;] 2%) and large CHIP (VAF [&ge;] 10%), and the primary outcome was all-cause mortality. Multivariable-adjusted Cox proportional hazards models tested the associations of CHIP and CHIP subtypes with all-cause and cause-specific mortality. Any CHIP and large CHIP were independently associated with all-cause mortality, with multivariable-adjusted hazard ratios (aHRs) of 1.12 (95% confidence interval [CI] 1.04-1.21; P = 0.003) and 1.28 (95% CI 1.15-1.43; P < 0.001), respectively. In gene-specific analyses, non-DNMT3A CHIP was associated with all-cause mortality (aHR: 1.22 [95% CI: 1.12-1.34], P < 0.001), while DNMT3A CHIP was not (aHR: 1.07 [95% CI: 0.98-1.18], P = 0.13). Furthermore, large CHIP was associated with cardiovascular (aHR: 1.29 [95% CI: 1.08-1.55], P = 0.006), cancer (aHR: 1.49 [95% CI: 1.11-2.02], P = 0.009), and neurologic (aHR: 1.40 [95% CI: 1.07-1.84], P = 0.02) death. In this cohort of older women, CHIP, particularly large clones and non-DNMT3A CHIP, was associated with all-cause and cause-specific mortality. These findings suggest that clonal size and subtype may differentially influence mortality risk.

ObjectiveTo test whether machine learning (ML) models trained on tidal breathing flow time series can discriminate between individuals with and without respiratory disease and predict lung function indices obtained from conventional pulmonary function testing. BackgroundAccurate assessment of respiratory function in infants and young children is challenging because conventional pulmonary function testing requires sophisticated equipment and/or active patient cooperation. Tidal breathing measurements, in contrast, can be obtained non-invasively with little or no patient cooperation and at low cost, yet their clinical utility has been limited. We hypothesized that sufficiently long tidal breathing flow time series contain clinically relevant information that can be extracted using a recurrent neural network known as a long short-term memory (LSTM) network. ApproachWe evaluated LSTM models in two scenarios within the Basel-Bern Infant Lung Development cohort. First, we assessed the ability of a model trained on flow and derived volume time series to detect bronchopulmonary dysplasia (BPD) in 329 infants. Second, we examined whether a model trained on tidal breathing flow alone could predict forced expiratory volume in one second (FEV1) in 135 school-age children. Signals were filtered and normalized prior to model training, and performance was evaluated on held-out test datasets. Main resultsFor BPD detection, the model achieved 97.0% accuracy, 100% specificity, 91.7% sensitivity, 100% precision, and an F1-score of 95.7%. For FEV1 prediction, Bland-Altman analysis showed a mean bias of -0.009 L (95% CI -0.091 to 0.074), with limits of agreement of -0.416 L and 0.399 L. The mean relative prediction error was 13.7%. SignificanceThese findings demonstrate that temporal patterns in tidal breathing flow signals contain diagnostically and functionally relevant information. ML applied to tidal breathing measurements may provide a low-burden, minimal-cooperation approach for early respiratory disease detection and functional assessment across early life stages.

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.

ObjectivesRising temperatures are a major climate-related hazard for U.S. workers, increasing heat-related illness and a broad range of occupational injuries through indirect pathways often overlooked in economic evaluations. We examined the association between temperature and occupational injury and illness and quantified heat-attributable injuries (including illnesses) and costs in New York State. MethodsWe conducted a time-stratified case-crossover study of 591,257 workers compensation (WC) claims during the warm season (2016-2024). Daily maximum temperature was linked to injury date and county and modeled using natural cubic splines, with effect modification by industry and worker characteristics. ResultsInjury risk increased with temperature, becoming statistically significant at approximately 78{degrees}F. Relative to 65{degrees}F, injury odds increased to 1.06 (95% CI: 1.01-1.10) at 80{degrees}F, 1.12 (1.07-1.18) at 90{degrees}F, and 1.17 (1.11-1.23) at 95{degrees}F. Overall, 5.0% of claims (2,322 annually) were attributable to heat. At temperatures [&ge;]80{degrees}F, an estimated 1,729 excess injuries occurred annually, generating approximately $46 million in WC costs. An estimated $3.2 million to $36.1 million in medical expenditures were associated with incomplete claims, likely borne outside the WC system. ConclusionsThese findings demonstrate substantial economic costs not fully captured within WC and support workplace heat protections as a cost-containment strategy that can reduce health care spending and strengthen workforce resilience.

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: Heart failure (HF) is a major contributor to inpatient hospital utilization, with persistently high 30-day readmission rates. Existing prediction tools are frequently restricted to primary-diagnosis HF admissions, potentially excluding clinically relevant HF-related hospitalizations. Objectives: To develop and validate risk prediction models using machine learning (ML)-based risk prediction models to predict 30-day readmissions among patients with HF using the Kansas Health Information Network, a statewide health information exchange. Methods: This retrospective cohort study analyzed HF hospitalizations using predictors including demographics, comorbidities, laboratory results, medications, clinical quality metrics for diabetes and kidney disease management, and prior healthcare utilization. Five ML models, including regularized logistic regression, random forest, extreme gradient boosting, categorical boosting, and deep neural network, were trained using stratified 5-fold cross-validation. Model performance was evaluated on an independent test set using the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), misclassification rate (MCR), and Brier score. Results: Among 2,734 HF patients, the 30-day readmission rate was 27%. The XGBoost model achieved the best discrimination (AUROC=0.75; AUPRC=0.58; MCR=0.21). Patients in the highest-risk decile had a positive predictive value of 76%, accounted for approximately one-third of all 30-day readmissions, and had a 3.3-fold enrichment compared with baseline risk. The key predictors included prior hospital utilization, diabetes and kidney disease management indicators, and comorbidity burden. Conclusions: Risk stratification using routinely collected clinical data identified a subgroup at elevated risk for 30-day readmission. These findings support the potential role of data-driven risk prediction to inform targeted transitional care.

BACKGROUND Transthyretin amyloid cardiomyopathy (ATTR-CM) is a progressive, life-threatening disease. Sociodemographic factors may influence time to treatment initiation and resulting clinical outcomes, yet these relationships are poorly characterized. OBJECTIVE Assess the effects of sex and race on tafamidis initiation and subsequent outcomes and their interaction with factors such as ATTR-CM type and social deprivation measures. METHODS A retrospective cohort analysis was conducted using the US Komodo Healthcare Map (01/2016-06/2024) among patients with amyloidosis, identified by ICD-10-CM diagnosis codes. Cumulative incidence of treatment initiation and survival probabilities for cardiovascular-related hospitalization (CVH) or death were estimated by Kaplan-Meier, stratified by sex and race. Cox proportional hazards models were fitted for both endpoints to estimate hazard ratios, adjusting for demographics and clinical characteristics. RESULTS Of 11,311 patients identified, White and Black patients (n=9,223) were included in subsequent analyses. Within 12 months of diagnosis, White women had the lowest cumulative incidence of tafamidis initiation (11.4%), followed by Black women (22.0%), Black men (26.7%), and White men (31.0%). Event-free survival at 12 months was lowest in Black women (42.9%), followed by Black men (46.8%), White women (48.6%), and White men (54.4%). Median (95% CI) time to CVH or death was shortest for Black women (8.0 months [6.8-10.0]) followed by Black men (9.9 months [8.8-12.0]), White women (11.0 months [9.6-13.0]), and White men (15.0 months [14.0-16.0]). CONCLUSIONS In this large, real-world cohort of US patients with ATTR-CM, sex and race contributed to disparities in tafamidis initiation and survival, underscoring compounded disparities in both access and outcomes.

Background World Symposium on Pulmonary Hypertension (WSPH) Group 2 pulmonary hypertension (PH) is a clinically integrated phenotype attributed to left heart disease, whereas pre- versus post-capillary classification is operationalized primarily by pulmonary capillary wedge pressure (PCWP). Although current recommendations emphasize contextual interpretation and provocative testing for intermediate PCWP values, the relationship between PCWP-based classification and underlying phenotype has not been systematically evaluated. We aim to quantify phenotype-hemodynamic discordance across the PCWP spectrum and evaluate a staged physiology-guided framework incorporating inhaled nitric oxide (iNO), ventricular geometry, and provocative testing. Methods We studied 1,032 participants from the NHLBI-sponsored PVDOMICS cohort with multidisciplinary adjudicated phenotypes integrating clinical, imaging, physiologic, and hemodynamic data. Stage-specific PCWP thresholds classified pre- versus post-capillary physiology at rest, during iNO, and during provocation (fluid challenge or invasive cardiopulmonary exercise testing [iCPET]). Echocardiographic right ventricular-to-left ventricular (RV/LV) ratio was evaluated as a marker of ventricular interdependence. Restricted cubic spline and staged concordance analyses defined certainty-based PCWP ranges and incremental diagnostic yield. Results Adjudicated Group 2 phenotype was present in 37.0% of participants. Resting PCWP demonstrated good discrimination (AUC 0.86), but substantial bidirectional phenotype-hemodynamic discordance persisted across intermediate PCWP ranges. At a resting PCWP of 12 mmHg, 25% of participants classified as pre-capillary had adjudicated Group 2 PH, whereas at 18 mmHg, 35% classified as post-capillary remained discordant non-Group 2. Concordance did not approach 90% until PCWP values were <9 mmHg or >24 mmHg. Dynamic testing incrementally improved concordance within these overlap zones. Nearly half of adjudicated Group 2 PH participants (46.5%) were not identified by resting PCWP alone; incorporation of iNO and provocative testing increased cumulative Group 2 identification by 63.4% and improved sensitivity from 79.9% to 83.7%. Model discrimination improved from an AUC of 0.863 to 0.908 (likelihood-ratio P<0.001). iNO increased PCWP in discordant Pre/G2 participants, unmasking latent left-sided limitation, while lowering PCWP in discordant Post/NonG2 participants, consistent with ventricular interdependence. RV/LV ratio [&ge;]0.94 reduced discordant Post/NonG2 classification by 70.5%, and incorporation of PCWP/cardiac output slope improved physiologic specificity during exercise. Conclusions Group 2 PH is a dynamic, load-dependent phenotype inadequately characterized by resting PCWP alone. Intermediate PCWP values represent continuous probabilities of bidirectional discordance rather than discrete diagnostic states. A staged physiology-guided approach integrating iNO, ventricular geometry, and provocative testing improves concordance between hemodynamic classification and clinically integrated phenotype assignment.

BackgroundPolycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs) are combustion-derived pollutants linked to cardiovascular disease. Prior NHANES analyses have evaluated these chemicals individually, failing to capture the correlated co-exposure structures that characterize real-world environmental burden, thereby underscoring the need for application. In this study, we applied an unsupervised machine learning pipeline to urinary biomarker data to identify multi-chemical exposure clusters and quantify their differential cardiovascular risk profiles in a nationally representative US sample. MethodsWe analyzed 2,979 participants from NHANES between 2017-2018, representing an estimated 36.8 million US adults after complex survey weighting. Twenty-five urinary biomarkers (6 PAH, 19 VOC metabolites) were log-transformed, imputed using Multivariate Imputation by Chained Equations (MICE), and standardized. Uniform Manifold Approximation and Projection (UMAP) was used for dimensionality reduction, followed by Gaussian Mixture Model (GMM) clustering. Survey-weighted prevalence estimates with 95% confidence intervals (CIs) were calculated for hypertension and high total cholesterol within each cluster. Weighted multivariable logistic regression was used to estimate odds ratios (OR) for hypertension, adjusting for age, sex, race/ethnicity, and income. ResultsFour exposure clusters were identified with a mean assignment probability of 0.948. The High combustion cluster (n=370; estimated 5.1 million US adults) exhibited the highest multi-chemical burden and a weighted hypertension prevalence of 39.3% (95% CI 37.2-41.4%), compared to 28.7% (95% CI 21.9-35.5%) in the Low exposure reference group. After demographic adjustment, High combustion cluster membership was independently associated with 38.4% higher odds of prevalent hypertension (OR 1.38). The prediction model achieved a cross-validated area under the receiver operating characteristic curve (AUC) of 0.849 (SD 0.017). Non-Hispanic Black participants constituted approximately 40% of the High combustion cluster, exceeding their representation in lower-risk clusters. ConclusionsMulti-chemical exposome profiling identifies four cardiovascularly distinct subpopulations in the US adult population. Membership in the High combustion exposure cluster was associated with higher odds of prevalent hypertension and disproportionately affected Non-Hispanic Black participants. These findings support the use of multichemical approaches over single-pollutant analyses and highlight the relevance of environmental exposure patterns for making policy and targeted cardiovascular risk stratification.

AimCystic fibrosis (CF) care has been transformed by CFTR modulator therapies, yet most efficacy data arise from clinical trials with restrictive eligibility criteria. Real-world registry data can capture treatment outcomes in broader, more diverse patient populations. We used the Cystic Fibrosis Foundation Patient Registry (CFFPR) data to evaluate longitudinal clinical outcomes, and care benchmarking at a single Adult CF Program Center over a decade. MethodsA retrospective, descriptive analysis of CFFPR data (2011-2022) was performed to assess trends in modulator use, lung function (ppFEV1), body mass index (BMI), respiratory microbiology, and pulmonary exacerbations (PEx). Comparative Effectiveness Research (CER) methods were applied to compare outcomes across peak modulator eras: pre-modulator (2011), ivacaftor (2015), mixed-modulator (2019), and elexacaftor/tezacaftor/ivacaftor (ELE/TEZ/IVA) (2021). Program-level outcomes were benchmarked against national network metrics to assess adherence to guideline-based care. ResultsOver ten years, median ppFEV1 improved from 63.4% (2011) to 78.8% (2021), and BMI increased from 22.3 to 24.8 kg/m2. The proportion of adults experiencing more than one PEx annually declined from 39.7% to 19.5%, while Pseudomonas aeruginosa (P.a.) culture positivity decreased from 79% to 47%. ELE/TEZ/IVA therapy was associated with greatest clinical improvements. Program-level performance remained comparable to national network benchmarks, reflecting high adherence to standard care metrics. ConclusionRegistry-based CER provides valuable real-world insights into CF care effectiveness and quality improvement. This decade-long analysis demonstrates significant clinical gains associated with modulator therapies and highlights the importance of patient registries in monitoring outcomes, benchmarking care, and informing global CF care models and standards for rare disease management. Key Messages{square} Real-world registry data enables decade-long evaluation of CFTR modulator effectiveness. {square}Elexacaftor/tezacaftor/ivacaftor demonstrates the greatest clinical benefit among modulator therapies. {square}Benchmarking Adult CF Program performance against the Network of Adult CF Programs facilitates quality improvement and standard care guideline adherence. {square}Patient registries provide insights for personalized care, program-level decision-making, and international standards for rare disease management.

Background: Respiratory rate (RR) predicts short-term mortality in acute care settings, yet its prognostic significance in clinically stable outpatients remains poorly defined. Objectives: To determine whether the median and variability of nocturnal respiratory rate (NRR) are independently associated with long-term cardiovascular and all-cause mortality in outpatients with cardiovascular disease. Methods: We analyzed overnight chest belt waveforms from elective polysomnography in 5,679 older adults with cardiovascular disease enrolled in the Sleep Heart Health Study (SHHS). NRR was quantified at 30-second resolution, and per-subject median NRR and within-night variability (standard deviation) were derived. Kaplan-Meier survival analysis and Cox proportional hazards models were used to evaluate associations with cardiovascular and all-cause mortality over 3-year and 15-year follow-up periods, adjusting for demographic characteristics, cardiopulmonary comorbidities, and sleep apnea severity. Results: Higher median NRR and greater NRR variability were each associated with increased cardiovascular and all-cause mortality. Combining these metrics identified a high-risk group characterized by elevated median and high variability of NRR, with approximately five-fold higher 3-year all-cause mortality compared with a low-risk group; this association remained significant in Cox models (unadjusted HR: 2.61; 95% CI: 1.65, 4.14; p<0.001; adjusted HR: 2.15; 95% CI: 1.30, 3.55; p=0.003). Conclusions: Both the baseline level and variability of NRR independently predict mortality in clinically stable outpatients with cardiovascular disease. Densely profiled NRR represents a promising, underutilized biomarker for long-term risk stratification.

ABSTRACT: BACKGROUND: Cardiac arrest(CA) and acute respiratory failure(ARF) are collectively at high risk of causing deaths among adults aged 25 and older in the United States. However, long-term trends to prevent these two coexisting conditions among adults are not well defined. OBJECTIVES: The objective of this study was to analyse mortality trends for CA with ARF among U.S. adults aged 25 years and older from 1999 to 2023. METHODS: Using the CDC WONDER Multiple Cause of Death database, we conducted a retrospective analysis of death certificates listing relevant ICD-10 codes for CA (I46) and ARF (J80, J96) among adults aged 25 years and older. Age-adjusted mortality rates (AAMRs) per 100,000 persons and the annual percentage change (APC) were calculated and stratified by demographics and geography. Trends were assessed using Joinpoint regression to estimate annual percentage change with 95% confidence intervals. RESULTS: From 1999 to 2023, 807,236 deaths were recorded. The overall AAMR showed a significant upward trend (AAPC: 4.06%), rising sharply to a peak in 2021 (28.56) before declining. Males consistently had higher AAMRs than females. Both of them increased till 2021 and later decreased. Racial differences were observed in that Non-Hispanic (NH) Black individuals had the highest average AAMR, while NH Whites had the lowest. Geographically, the Western census region had the highest AAMR, increasing to 37.5 in 2021 (APC: 23.92; 95% CI: 16.21 to 28.35; p=0.0004), and rural areas demonstrated higher mortality than urban areas(13.45 vs 10.53). Adults aged 65 and older showed the highest AAMR, with a sudden rise to 96.7 in 2021 (APC: 17.4; 95% CI: 11.7 to 20.7, p<0.000001), followed by a subsequent decline, compared with the other age groups. CONCLUSIONS: There was a marked AAMR due to CA and ARF over the past 24-year period, with a surge around the COVID-19 pandemic. Significant differences were observed by sex, race, and geography. These findings highlight that efforts are needed to prevent and manage mortalities by interventions among high-risk populations who have both HF and ARF.

IntroductionAlthough temporal variation is the hallmark of asthma, recommended diagnostic approaches largely rely on single clinic-based measurements. Ambulatory monitoring captures diurnal and day-to-day variability and may therefore enhance diagnostic accuracy. We evaluated the clinical feasibility and potential utility of home spirometry and fractional exhaled nitric oxide (FeNO) monitoring in asthma diagnosis. MethodsSymptomatic, untreated adults with GP-suspected asthma underwent diagnostic tests including bronchodilator reversibility, in-clinic FeNO, blood eosinophil counts and bronchial challenge. Participants measured spirometry and FeNO four times daily over one week; during the second week spirometry were measured twice daily. The reference standard was provided (asthma/not-asthma) by an expert panel of at least two asthma specialists based on clinical history and the results of all in-clinic testing; home spirometry (except for peak expiratory flow) and FeNO measurements were blinded to the panel. ResultsOf 67 eligible participants, 51(76%) were recruited, and 38 had asthma confirmed or excluded by the panel. 1058 home spirometry measurements were obtained from 37(73%) participants; 848 home FeNO readings were obtained from 39(76%) participants. Among those completing at least one home measurement, median (IQR) adherence was 66.7(58.6-97.6)% for spirometry and 78.5(51.8-103.6)% for FeNO. Collection of health impact data for economic evaluation was feasible. In participants with a confirmed diagnostic outcome who completed home measurements (FeNO: n=32; spirometry: n=28), the putative home-testing metrics demonstrated high sensitivities at [&ge;]90% specificity, and outperformed peak expiratory flow diurnal variability. Incorporating home testing into the BTS/NICE/SIGN 2024 diagnostic pathway had the potential to reduce reliance on bronchial challenge testing by 57%. ConclusionsHome spirometry and FeNO testing and the prospective collection of health-economic data in the diagnostic setting were feasible. Home-based testing strategy showed early potential to improve asthma diagnosis and pathway efficiency. These findings support further evaluation through an adequately powered diagnostic accuracy study and health-economic assessment. Key messagesO_LIWhat is already known on this topic: Asthma can be difficult to diagnose, as objective tests may be normal when assessments are performed during periods of minimal or intermittent symptoms. C_LIO_LIWhat this study adds: Our data suggest that home spirometry and FeNO monitoring could be successfully implemented within a diagnostic accuracy trial. Participants were able to perform these tests reliably in the home environment. C_LIO_LIHow this study might affect research, practice or policy: The early findings suggest that home-based physiological monitoring may offer additive diagnostic value beyond standard clinic-based assessments and could reduce reliance on bronchial challenge testing. These results provide a clear rationale for larger diagnostic accuracy trials and for undertaking early health-economic modelling to assess the potential impact on clinical pathways and resource utilisation. C_LI

BackgroundTBX4 variants are a recognised cause of paediatric pulmonary hypertension (PH), often associated with interstitial lung disease (ILD). Evidence for ILD-directed therapy in this group is lacking. MethodsWe conducted a retrospective study of children ([&le;]18 years) with TBX4-associated PH at a national centre (2001-2025). ILD was defined using ChILD-EU criteria. Patients treated with pulsed intravenous methylprednisolone were assessed for response using ChILD-EU categories. Secondary outcomes included respiratory severity score (RSS), functional class (FC), echocardiographic measures, and NT-proBNP. ResultsOf 21 children, 11 (52%) had ILD; 9 received corticosteroids. Median age at treatment was 0.8 years. A clear or best response occurred in 7/9 (78%). RSS improved in 6/9 (p=0.02), with all children on respiratory support showing partial or complete weaning. Functional class improved in all with FC III/IV at baseline (p=0.02). Right ventricular function improved (TAPSE z-score +1.65, p=0.04), and elevated NT-proBNP normalised. Key clinical milestones included ECMO weaning, transplant delisting, and discontinuation of prostacyclin therapy. No significant adverse effects were observed. Untreated children showed no early improvement. ConclusionsCorticosteroids were associated with meaningful improvements in respiratory and PH outcomes in TBX4-associated PH with ILD. Prospective evaluation is warranted.

Purpose: Population-level lung cancer screening programs require denominators that reflect age, smoking history, geography, and changing eligibility over time. We estimated annual prevalent and 20-year cumulative unique low-dose computed tomography screening eligibility for Maryland residents under alternative screening criteria. Methods: We built a deterministic cohort-cell stock-flow simulation using Maryland county-equivalent jurisdiction projections by age, sex, and race/ethnicity, with ACS socioeconomic/nativity covariates and smoking-history priors for ever-smoked status, pack-years, and quit-years. Scenarios included USPSTF 2013 legacy, USPSTF 2021, ACS 2023/2024, a risk-model-expanded sensitivity, and ever-smoked-only capacity stress tests. Cumulative unique eligibility counted people once at first eligibility rather than summing annual prevalent person-years. Results: Under USPSTF 2021, an estimated 238,346 Maryland residents were eligible in 2026 and 245,326 in 2045. The 20-year cumulative unique denominator was 768,668, whereas naively summing annual prevalent counts produced 4,850,735 person-years, a 6.31-fold overcount. ACS 2023/2024 expanded annual eligibility to 314,616 in 2026 and cumulative unique eligibility to 902,796 by adding remote former smokers. Ever-smoked-only adult eligibility was 1,957,699 in 2026 and 3,383,683 cumulative unique over 20 years. Conclusion: A Maryland statewide screening initiative should plan from cumulative unique eligibility and county-equivalent jurisdiction-specific burden rather than annual prevalence alone. Explicit pack-year and quit-year modeling materially changes statewide and county allocation compared with current-smoking proxy models.

Background. Diagnosis and risk stratification in rare hematologic malignancies such as myeloproliferative neoplasms (MPNs) - polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF) - require expert review of longitudinal, heterogeneous clinical records. This process is cognitively demanding, inconsistently applied, and difficult to scale beyond tertiary centers. No automated phenotyping workflow currently exists for hematologic malignancies. Methods. A HIPAA-compliant large language model (LLM) framework for phenotyping MPN was developed to integrate (i) rule-based retrieval of bone marrow biopsy reports, clinical notes, and structured laboratory results from the electronic health record (EHR); (ii) zero-shot extraction of diagnostic and prognostic variables from unstructured text using GPT-4 Turbo; (iii) a clinician-informed source-prioritization algorithm to reconcile conflicting multi-source data; (iv) WHO/ICC-criteria-based diagnostic classification; and (v) NCCN-based risk stratification using the conventional risk model for PV, IPSET-thrombosis for ET, and DIPSS, DIPSS-plus, and MIPSS70/MIPSS70+ v2 for MF. Patients were identified via MPN-related ICD-9/10 codes; cases met 2017 WHO criteria or had a hematologist-documented diagnosis, and controls did not. The cohort was split into a prompt-development set (n = 60) and a held-out test set (n = 450; 75 cases and 75 controls per disease). Ground truth was established by independent dual-clinician chart review with consensus adjudication. LLM performance was evaluated against the ground truth: variable-level extraction using accuracy, F1 score, and Cohen's kappa; patient-level diagnostic classification using sensitivity, specificity, and Cohen's kappa; and prognostic risk stratification (among confirmed cases) using accuracy, weighted F1 score, and quadratic-weighted Cohen's kappa. Wilson 95% confidence intervals (CIs) were used for proportions and bootstrap 95% CIs with 500 resamples for F1 scores. Results. The held-out test set included 450 patients (PV: 150; ET: 150; MF: 150) with pathology reports and structured laboratory results, and 172 patients (PV: 52; ET: 55; MF: 65) with clinical notes. From pathology reports, overall variable extraction accuracy and F1 score were 99% (95% CI, 98-100) and 1.00 (0.99-1.00) for PV, 100% (99-100) and 0.99 (0.96-1.00) for ET, and 100% (99-100) and 0.99 (0.97-1.00) for MF. From clinical notes, overall accuracy and F1 score were 96% (91-100) and 0.94 (0.85-1.00) for PV, 100% (100-100) and 1.00 (1.00-1.00) for ET, and 100% (99-100) and 0.98 (0.95-1.00) for MF. Diagnostic sensitivity was 100% (95% CI, 95.1-100.0) for PV, ET, and MF; specificity was 98.7% (92.8-99.8) for PV and 100% (95.1-100.0) for both ET and MF, with Cohen's kappa of 0.99 for PV and 1.00 for ET and MF. Risk stratification accuracy was 100% with weighted F1 score of 1.00 and quadratic-weighted Cohen's kappa of 1.00 across all three diseases. A pre-specified source-ablation analysis showed that pathology reports alone were sufficient for diagnosis (sensitivity 98.7% for PV, 100% for ET, 96.0% for MF; specificity 100% across all three subtypes) but inadequate for prognostication (accuracy 69.3% for PV, 93.3% for ET, 77.3% for MF). Adding clinical notes to pathology reports recovered full prognostic accuracy of 100% across all three diseases. Conclusions. This first-in-class automated framework achieved expert-level performance for MPN diagnosis and risk stratification from real-world EHR data, establishing a foundation for scalable, standardized phenotyping in rare hematologic malignancies. Prospective, multi-site validation is warranted before clinical deployment.

Background: The importance of lactate trajectory during the first day of cardiogenic shock is increasingly recognized. We aimed to assess the association between admission-day lactate trajectory and in-hospital mortality, and to identify same-day interventions predictive of lactate clearance. Methods: We analyzed adult patients admitted with cardiogenic shock between October 2015 and June 2023, using the Vizient(R) Clinical Data Base. Early lactate clearance was defined as lactate <2.5 mmol/L by the end of the admission day. We used multivariable logistic regression to assess the association between lactate change and in-hospital mortality, and to identify interventions associated with lactate clearance. Results: Among 40,434 patients with cardiogenic shock, 30.1% achieved same-day lactate normalization, which was associated with lower in-hospital mortality (aOR 0.51; 95% CI 0.48-0.54). Lactate change showed the greatest prognostic importance, with observed mortality exceeding 80% among those with lactate increase >5 mmol/L regardless of baseline values. After adjustment, lactate change showed a positive exponential relationship with mortality, with aORs ranging from 0.25 (95% CI 0.23-0.27) for a -10 mmol/L change to 3.99 (95% CI 3.58-4.40) for a +10 mmol/L change. The intervention most strongly associated with early lactate clearance was pulmonary artery catheter (PAC; aOR 1.28 [95% CI 1.19-1.37]). Conclusions: Nearly 1 in 3 patients with cardiogenic shock achieved early lactate clearance, which was associated with lower mortality. The magnitude of lactate change had profound prognostic implications regardless of the initial value. Among day 1 interventions, PAC use had the strongest association with lactate clearance.