Annals of the American Thoracic Society

Rationale: Fibrosing interstitial lung diseases (ILDs), including idiopathic pulmonary fibrosis (IPF), have heterogeneous postdiagnosis courses. Existing prognostic tools often rely on pulmonary function testing, imaging, or laboratory data that may not be uniformly available and rarely provide individualized, time-updated forecasts of multiple clinically relevant trajectory events. Objectives: To determine whether longitudinal healthcare claims can generate test-free, time-updated forecasts of clinically actionable postdiagnosis trajectory events in patients with fibrosing ILD and IPF. Methods: Using de-identified longitudinal administrative claims from the Merative MarketScan Commercial Claims and Encounters and Medicare Supplemental and Coordination of Benefits databases, we constructed code-based digital twins (ZeBRA) encoding each patient's evolving diagnosis, pharmacy, and procedure history. Horizon-specific models forecast seven claims-observable events: supplemental oxygen escalation, pulmonary hypertension, acute respiratory failure/ARDS composite, nausea, diarrhea, liver injury, and gastrointestinal bleeding. The analytic cohort included 345,918 patients with fibrosing ILD, including 17,284 with IPF. Predictions were evaluated in a time-updated follow-up setting at 1-month, 6-month, and 1-year horizons. Results: Predictive discrimination was consistent across events and horizons. In fibrosing ILD, AUC ranged from 0.691 for liver injury at 1 year to 0.912 for oxygen dependence at 1 month, with PPV ranging from 0.189 to 0.714. At 1 month, oxygen dependence achieved an AUC of 0.912 +/- 0.005 with PPV of 0.473 +/- 0.005, and pulmonary hypertension achieved an AUC of 0.881 +/- 0.005 with PPV of 0.539 +/- 0.005. The IPF subcohort showed analogous horizon-dependent performance, with AUC ranging from 0.687 to 0.855 and PPV from 0.245 to 0.817. At 1 month in IPF, PPV was 0.753 +/- 0.015 for oxygen dependence and 0.817 +/- 0.011 for pulmonary hypertension. Conclusions: A test-free digital-twin framework derived from routine longitudinal claims can provide individualized, time-updated forecasts of actionable fibrosing ILD and IPF trajectory events without imaging, pulmonary function tests, laboratory data, clinical notes, or patient-facing data collection. These forecasts may support low-burden reassessment, anticipatory care planning, and earlier recognition of elevated near-term risk for respiratory deterioration or management-altering complications.

Objectives: Acute hypercapnic respiratory failure (AHRF) is a common cause of hospitalization among adults with chronic respiratory and sleep-related disorders. We evaluated whether admission to hospitals with an on-site American Academy of Sleep Medicine (AASM)-accredited sleep facility was associated with length of stay (LOS) and hospitalization cost among adults admitted with AHRF. Methods: We conducted a retrospective cohort study using the Healthcare Cost and Utilization Project New York State Inpatient Database from 2017 to 2021. Adults admitted to hospitals outside New York City were included because hospital density, referral patterns, and access to specialty services differ from those in New York City. Hospitals were classified by the presence of an on-site AASM-accredited sleep facility, used as a structural proxy for institutional sleep medicine capacity. LOS and hospitalization cost were log10-transformed before analysis. We used bivariate analyses and hierarchical multivariable linear regression models adjusting for demographic, clinical, socioeconomic, and hospital-level covariates. Results: A total of 3,247 adults met inclusion criteria. In unadjusted analyses, admission to hospitals with an on-site AASM-accredited sleep facility was associated with shorter LOS and lower hospitalization cost. After adjustment, sleep facility status was not independently associated with either outcome and did not improve model fit. Greater comorbidity burden was the strongest independent predictor of both longer LOS and higher cost. Housing instability and race categorized as other than White were also associated with higher resource use. Chronic obstructive pulmonary disease was independently associated with shorter LOS and lower cost. Conclusions: Among adults hospitalized with AHRF, LOS and hospitalization cost were more strongly associated with comorbidity burden and socioeconomic disadvantage than with the presence of an on-site AASM-accredited sleep facility. These findings suggest that accreditation status alone may not capture inpatient sleep medicine processes most relevant to acute respiratory care.

Background: Racial disparities in incident heart failure (HF) are well documented, yet the extent to which systemic inflammatory burden-shaped by structural determinants of environmental exposure-accounts for these disparities remains unquantified in multi-ethnic prospective cohorts. Methods: Among 6785 participants in the Multi-Ethnic Study of Atherosclerosis (enrolled 2000-2002; 4 racial/ethnic groups) followed for approximately 16 years, we estimated associations of 4 prespecified baseline inflammatory and hemostatic biomarkers (interleukin-6 [IL-6], C-reactive protein [CRP], fibrinogen, and D-dimer; per 1-SD increment) with incident HF (485 events) using Cox proportional hazards models. A composite inflammatory burden index was derived by principal components analysis. Race x biomarker multiplicative interactions were tested with Holm correction. Sequential biomarker adjustment quantified the percentage of the Black-White log-hazard difference explained relative to a clinical-only model. Robustness to ambient air pollution (PM2.5, NO2) was assessed in a geocoded subcohort. Results: All 4 biomarkers were independently associated with incident HF (IL-6: hazard ratio [HR], 1.20 [95% CI, 1.08-1.34]; D-dimer: 1.18 [1.06-1.30]; CRP: 1.14 [1.02-1.27]; fibrinogen: 1.13 [1.02-1.24]). The composite index (first principal component, 53.7% of variance explained) yielded an HR of 1.25 (1.12-1.39) per 1-SD increase. No multiplicative race x biomarker interaction was detected (all Holm-corrected P=1.0), indicating that the per-SD inflammatory hazard was directionally consistent across groups. Sequential biomarker adjustment reduced the Black-White log-hazard difference by 57.5%, a pattern consistent with-but not sufficient to prove-attenuation by inflammatory pathways. Associations were robust to PM2.5/NO2 co-adjustment. Conclusions: Inflammatory and hemostatic burden partially explains the Black-White disparity in incident HF. The null multiplicative interaction pattern indicates that per-unit biological risk is equitable across groups, consistent with differential structural exposure-rather than differential susceptibility-as a primary driver of disparity. Key Words: heart failure; inflammation; health equity; structural determinants; MESA; biomarkers

Study Question. COPD exacerbations with respiratory failure have an outsized impact on morbidity, mortality, and healthcare costs. Physicians treat these severe events with high doses of corticosteroids out of concern for intrinsic corticosteroid resistance. This study was designed to determine whether people who suffer from exacerbations with respiratory failure have intrinsic steroid resistance that could affect that decision. Patients and Methods. A matched, case-control study was performed at University of Colorado. Subjects were enrolled into the Exacerbation group if they were hospitalized for an exacerbation requiring ventilation, or into the Stable COPD group if they had no inpatient exacerbation within 12 months. Stable COPD subjects were frequency-matched to Exacerbation subjects for age, smoking status and FEV1%. Corticosteroid sensitivity was assessed ex vivo and in vivo >45 days following the last exacerbation during a period of relative quiescence. The primary outcome was the group difference in methylprednisolone IC50 for LPS-stimulated IL-8 release by mononuclear cells. Measurements and Main Results. The Exacerbation group (N=8) had more exacerbations in the prior year (6.0 vs. 0.5; p<0.01) and had higher baseline blood lymphocytes (p<0.01) versus Stable controls (N=8). Ex vivo, methylprednisolone equally suppressed IL-8, IL-6, TNFalpha and IL-1bets release by mononuclear cells and whole blood across groups. In vivo, methylprednisolone decreased plasma mediators and mononuclear cells in both groups but had a small differential effect on mononuclear cell gene expression. Answer to the Question. Exacerbations with respiratory failure have persistent lymphocytosis, an altered gene response to corticosteroids, but no corticosteroid resistance to suppress inflammation.

Background: Children spend more than 90% of their time indoors, and early childhood education settings (ECEs) are an understudied, high-occupant-density indoor microenvironment where exposure to volatile organic compounds, particulate matter, and other toxicants has been documented. Limited knowledge exists on ECE-specific exposures affecting young children and how they compare to exposures in the home. Methods: This prospective, repeated-measures pilot study targeted enrollment of 44 preschool-aged children and 8 ECE staff across two geographically and sociodemographically distinct ECEs in metropolitan Atlanta, Georgia. Paired silicone wristbands, one home-designated and one ECE-designated, were exchanged between settings across three consecutive days and nights beginning at enrollment to characterize microenvironment-specific exposure. A single spot urine sample was also collected from each child. Continuous indoor air quality monitoring was conducted in two classrooms per site. Caregivers and ECE staff completed structured questionnaires assessing home and ECE environmental characteristics, child respiratory risk, and protocol feasibility and acceptability. Feasibility was evaluated using eight pre-specified indicators spanning recruitment and enrollment, wristband wear duration and loss by microenvironment, urine sample collection completeness, and survey completion by instrument and respondent group. Conclusion: This pilot will establish feasibility and acceptability parameters for a paired, multi-matrix silicone wristband protocol across home and ECE microenvironments. Findings will inform the design, sample size, and power calculations for a subsequent study testing indoor air interventions and pediatric respiratory outcomes in ECEs. Feasibility outcomes are reported in a companion manuscript.

BackgroundEarly-life air pollution exposure has been associated with childhood asthma, but its relative contribution is poorly characterised in cohorts with repeated indoor measurements. Short sampling windows and seasonal bias limit how well any single measurement can represent cumulative exposure. ObjectiveTo evaluate the association between early-life indoor and outdoor pollutant exposure from birth to 18 months and asthma development at ages 7, 12, and 18 years, while testing potential exposure-exposure and gene-environment interactions. MethodsIn the COPSAC2000 birth cohort (n = 411), indoor PM2.5, black carbon, NO2, NOx and VOCs, and modelled outdoor PM2.5, NO2 and NOx, were assessed at 6, 12 and 18 months of age. Indoor metrics were corrected for pump-flow drift and seasonal bias via a Gaussian process with a periodic kernel. Hierarchical Bayesian logistic regression(HBLR) and calibrated random forests (CRF) were evaluated using stratified nested cross-validation for discrimination using AUC-ROC, Calibration using integrated calibration index (ICI), and Brier skill scores. Exposure-exposure and gene-environment interactions were quantified via Shapley interaction indices. ResultsDiscrimination was weak at all endpoints with test AUC-ROC: 0.58-0.67, BSS near zero (0.012 to 0.05) and ICI: 0.043-0.061 for random forest and AUC-ROC 0.53-0.61, BSS equal to zero and ICI: 0.054-0.067 for hierarchical Bayesian logistic regression (HBLR). No pollutant reached a highest density interval excluding OR = 1. The polygenic risk score(PRS) was the only term non-null at all three ages in the adjusted models. While gene-environment interactions were detected, effect sizes were negligible and statistically indistinguishable from zero. SignificanceWhere ambient pollution is low, cumulative early-life exposure adds little to long-term asthma prediction beyond genetic and contextual factors, and an improved exposure correction does not uncover an effect. ImpactRepeated bedroom measurements across infancy are rare, and short sampling windows make them hard to read as cumulative exposure. We corrected measured concentrations for pump-flow drift and for seasonal sampling bias on the pollutants and used two complementary machine learning models to predict interaction and risk. In this low-exposure Danish cohort, genetic risk and residential context dominated, and the measured pollutants added almost nothing to the asthma risk at 7,12 and 18 years. These null results indicate that early cumulative exposures of indoor and outdoor air pollution contribute little to nothing to asthma up to 18 years.

Purpose To evaluate the implementation characteristics of a commercially available chest radiography artificial intelligence (AI) system in a large real-world health check-up cohort using workflow-level, lesion-specific, and exploratory retrospective lung cancer case analyses. Methods This retrospective single-centre study included 298,991 consecutive health check-up chest radiographs from 114,866 individuals obtained between 2019 and 2023 and interpreted under routine double reading by board-certified radiologists. A commercially available AI system was evaluated using two prespecified thresholds: positivity in any of ten findings for the all-score analysis and positivity for nodule or mass for the nodule-focused analysis, both at a manufacturer-recommended score threshold of 15. Because routine radiologist judgement rather than universal CT or pathologic verification served as the reference framework, the primary analyses were interpreted as radiologist-referenced operational concordance analyses. Results Radiologist-referenced sensitivity and specificity were 72.0% and 79.6%, respectively, in the all-score analysis and 87.1% and 91.8%, respectively, in the nodule-focused analysis. Negative predictive values were 99.0% and 100.0%, respectively. Among 48 histopathologically confirmed lung cancer cases, retrospective timeline analyses showed earlier AI positivity than routine radiologist positivity in a subset of cases. These findings should be interpreted as exploratory observations and do not establish prospective clinical benefit. Conclusion In a large health check-up cohort, chest radiography AI demonstrated stable concordance with routine radiologist judgement and high sensitivity for radiologist-reported pulmonary nodules and masses. Exploratory retrospective analyses showed earlier AI positivity in a subset of histopathologically confirmed lung cancer cases, supporting further prospective evaluation of AI-assisted health check-up workflows.

Rationale: Obstructive sleep apnea (OSA) is highly prevalent yet largely under-diagnosed. Current screening strategies rely on effortful questionnaires with modest accuracy, and prior machine learning models often require resource-intensive inputs and lack external validation. Objectives: To develop and validate machine learning models to predict OSA (apnea-hypopnea index [AHI4%][&ge;]5) and moderate-severe OSA (AHI4%[&ge;]15) using only routinely collected electronic health record (EHR) data, test cross-system transferability and compare performance with clinical screeners and a Bayesian risk-updating framework. Methods: Three tree-ensemble families (XGBoost, random forests, and histogram-based gradient boosting) were trained on an adult cohort with sleep-study results at Kaiser Permanente (KPSC), using full (106-feature) and minimal (age, sex, body-mass index, race/ethnicity) predictor sets and tuned by nested cross-validation. XGBoost models were selected, internally and temporally validated, and externally validated at University of Kansas Medical Center (KUMC). Measurements and Main Results: On our internal hold-out set (n=53,048), the full XGBoost model reached a ROC-AUC of 0.791 for any OSA and 0.768 for moderate-severe OSA. The minimal model retained most performance (0.764 and 0.736). Temporal performance was stable. Externally, frozen models showed lower AUCs (0.718 and 0.690 for full models; 0.725 and 0.706 for minimal models) but similar to KUMC-native models and improved further with transfer learning. The models significantly outperformed STOP-BANG (AUC difference 0.06-0.09 for predicting any OSA; p<0.001). Bayesian updating with select patient-reported items further improved discrimination. Conclusions: Machine learning models based on EHR data can predict OSA probability that outperform existing screeners, transfers across systems, and offers potential for EHR implementation.

Background: Observational studies have linked air pollution to otitis media, but confounding and reverse causation preclude causal inference. We used two-sample Mendelian randomization (MR) to assess genetic causal effects of six air pollutants on non-suppurative otitis media, represented by otitis media with effusion (OME). Methods: Exposure GWAS for PM2.5, PM2.5 absorbance, PM2.5-10, PM10, NO2 and NOx were obtained from UK Biobank (MRC-IEU), and the outcome was FinnGen R13 H8_NONSUPPNAS (12,397 cases, 464,237 controls). Inverse-variance weighting was primary, with MR-Egger, weighted median and mode, MR-PRESSO, leave-one-out and Steiger analyses, reverse MR and exploratory multivariable MR (MVMR). Asthma, allergic rhinitis and chronic rhinosinusitis served as positive controls, and three suppurative otitis media phenotypes served as negative controls. Results: After false-discovery-rate correction, none of the six pollutants was significantly associated with OME; the sole nominal signal was PM10 (OR=1.555, 95% CI 0.947-2.553, P=0.081), which reversed with the 88-SNP pooled set (OR=0.64, 0.24-1.69, P=0.365). At 80% power, minimum detectable ORs ranged widely from 1.69 to 32.09; only PM2.5-10 and PM10 had values near 2, so moderate effects (OR 1.2-1.5) cannot be excluded. Confirmatory positive controls using phenotype-specific instruments were strongly positive, whereas negative-control outcomes showed no associations (all FDR>0.85). Every nominal reverse-MR signal had a significant MR-Egger intercept (the PM2.5 absorbance signal also showed significant heterogeneity and MR-PRESSO tests), indicating horizontal pleiotropy rather than reverse causation. MVMR was exploratory only, as conditional F statistics were below 10. Conclusions: We found no evidence for large-effect genetic causal associations between the six air pollutants and OME. These null findings argue against large, lifetime-average causal effects, and the associations reported in observational studies may instead reflect residual confounding, shared comorbidity or differences in exposure windows.

Background and Objective: Lung function reference equations are essential for interpreting spirometry and related modalities, yet existing tools are fragmented, modality- and language-specific (predominantly R), and lack integrated severity classifiers. We present PySpiro, an open-source Python library unifying 23 spirometry, 1 multiple breath washout, 2 diffusing capacity, 1 static lung volume, and 2 oscillometry reference equations under a single API, with 10 clinical severity classifiers. Methods: PySpiro was implemented in Python 3 using NumPy and pandas, with all equations coded directly from literature. The unified API exposes predicted medians, z-scores, limits of normal (LLN/ULN), and raw Lambda-Mu-Sigma (LMS) triplets per parameter, plus a vectorised compute() method for batch processing at the DataFrame level. Unit-tests covering every equation and classifier verify agreement with published values and confirm correct boundary, out-of-range, and missing-input handling. Results: PySpiro covers spirometry equations from 1971 to 2022 across Caucasian, Asian, Indian, and race-neutral global populations, plus non-spirometry modalities (multiple breath washout, diffusing capacity, static lung volumes, oscillometry). Classifiers span COPD, interstitial lung disease, pattern and severity grading, bronchodilator reversibility, and primary ciliary dyskinesia. Compared with rspiro (5 equations, 4 spirometry) and the only prior Python package (spiref, 2 equations, no z-scores or % predicted), PySpiro offers substantially broader coverage, multi-modality support, a richer output API, and 10 classifiers absent from both. Conclusions: PySpiro is freely available (PyPI: pyspiro; doi:10.5281/zenodo.15519193) and provides a comprehensive, validated, and extensible platform for lung function data analysis in research pipelines.

Background: Chronic obstructive pulmonary disease (COPD) is characterized by airway remodeling, which may extend to the central airways and alter tracheal morphology. Whether tracheal shape relates to disease severity, quality of life, functional capacity, or survival is not established. Objective: To determine whether CT-derived tracheal lumen eccentricity is associated with cross-sectional and longitudinal clinical outcomes in COPD. Methods: We analyzed 8,383 participants from the multicenter COPDGene study. At each axial cross-section of the trachea, lumen eccentricity ({epsilon}) was computed from the major and minor axis lengths, and the participant-level value was taken as the arithmetic mean across all tracheal slices; {epsilon} = 0 denotes a circular lumen and values approaching 1 denote progressively elongated ellipses. Baseline outcomes were spirometry, 6-minute walk distance (6MWD), St. George's Respiratory Questionnaire (SGRQ) total score, and modified Medical Research Council (mMRC) dyspnea score. Longitudinal outcomes were annualized change in FEV1 and all-cause mortality. Multivariable linear and Cox proportional hazards models were adjusted for [age, sex, race, BMI, smoking status, pack-years, scanner model]. Results: Tracheal eccentricity rose monotonically with severity of airflow obstruction (0.60{+/-}0.07, 0.61{+/-}0.07, 0.62{+/-}0.07, 0.64{+/-}0.08, and 0.64{+/-}0.08 in GOLD stages 0 through 4, respectively). Higher eccentricity was independently associated with lower FEV1 ({beta} = -0.30 L, 95% CI -0.47 to -0.14; p < 0.001), lower FEV1/FVC ({beta} = -0.06, 95% CI -0.09 to -0.04; p < 0.001), shorter 6MWD ({beta} = -15.7 m, 95% CI -25.2 to -6.2; p = 0.001), higher SGRQ score ({beta} = 16.9, 95% CI 11.2 to 22.5; p < 0.001), higher mMRC dyspnea score ({beta} = 0.4, 95% CI 0.1 to 0.6; p = 0.007), and accelerated lung function decline ({beta} = -23.8 mL/year, 95% CI -45.13 to -2.48; p = 0.029). Eccentricity was also associated with all-cause mortality (adjusted HR 1.81, 95% CI 1.01 to 3.26; p = 0.047). Conclusions: Tracheal lumen eccentricity is associated with worse quality of life, reduced functional capacity, accelerated lung function decline, and mortality in COPD, supporting central airway morphology as a candidate imaging biomarker.

Abstract Background Fibrotic interstitial lung disease (F-ILD) has high mortality. Evidence suggests short telomere causality and sex hormone interactions. STARSHIP aimed to assess feasibility for future F-ILD sex hormone trials. Methods Leukocyte telomere length (LTL), complete blood count, sex hormone (testosterone and oestrogen), sex hormone binding globulin (SHBG) and albumin concentrations were determined in 102 F-ILD outpatients (age 49-89, male N=80 [78%]) and age/sex-matched controls (ASMCs). Patients undertook routine pulmonary function tests, 93 (91%) participated in bespoke telephone interviews. Survival was assessed at median 33 (28-39) months. Results 77/79 (97.4%) male patients had haemoglobin and haematocrit below the upper reference limit. Mean LTL was shorter for patients than ASMCs (4.57kb [95%CI:4.46-4.69] vs 4.78kb [95%CI:4.67-4.89]; p<0.006). SHBG concentrations were higher for patients. Mean bioavailable testosterone was lower for N=80 male patients than ASMCs (4.95nmol/L [95%CI:4.50-5.41] vs 6.40nmol/L [95%CI:5.82-6.98]; p<0.0001). Post-menopausal oestrogen concentrations were low for female patients and controls. Mean free androgen index (FAI) was low for female patients but not ASMCs (mean 0.51 [95%CI:0.35-0.67] vs 1.23 [95%CI:0.77-1.69]; p=0.0036, N=22). Age/BMI-adjusted bioavailable testosterone concentration in male patients correlated with both DLCO% (=3.31, p=2.4x10-4) and FVC% (=2.76, p=0.0030). FVC% associated with FAI in females (=34.3, p=0.0029). In all-confounder-adjusted Cox analysis, low free testosterone associated with mortality (HR=2.66, p=0.023, N=77) in male patients. Lower FAI (adjusted for age/lung function) suggested similar effects but more studies needed for females (HR=3.59, p=0.22, N=18). Conclusions ILD patients have low sex hormones concentration(s), which associated with reduced lung function and survival. Sex hormone supplementation studies are needed.

Background: Glucagon-like peptide 1 receptor agonists (GLP-1 RA) are indicated for weight reduction and offer cardiometabolic health benefits, yet there is little real-world evidence regarding their association with healthcare resource utilization (HCRU) and costs for Medicare Advantage (MA) beneficiaries with heart failure and obesity. Methods: We used a prevalent new-user study design and the Humana Healthcare Research database to identify MA beneficiaries with heart failure (HF) and obesity receiving standard HF therapy or HF therapy + newly initiating GLP-1 RA between January 1, 2022, and December 31, 2023. We observed adjusted, one-year mean difference in all-cause and heart failure-related HCRU. Results: In our cohort of 4,677 matched pairs (mean age 72 years, male: 41%), one-year, adjusted risk ratio (RR) for HF therapy + GLP-1 RA vs HF therapy was 0.89 (95% CI: 0.84 ? 0.93) for all-cause inpatient utilization, 0.88 (95% CI: 0.82 ? 0.94) for avoidable hospitalizations, and 0.99 (95% CI: 0.95 ? 1.03) for emergency department visits. For individuals receiving HF therapy + GLP-1 RA vs HF therapy, the mean difference was 30.6% (95% CI: 26.7% ?34.7%) for all-cause total costs, 105.9% (95% CI: 99.1% ?112.9%) for pharmacy costs, and ?4.7% (95% CI: ?8.7% to ?0.6%) for medical costs. HF-related HCRU measures were lower among beneficiaries augmenting HF therapy with GLP 1 RA vs individuals receiving HF therapy alone. Conclusions: Among MA beneficiaries with heart failure and obesity, the addition of GLP-1 RA to standard heart failure therapy reduced the likelihood of inpatient admissions or avoidable hospitalizations compared with HF therapy alone.

Background: Primary malignant cardiac tumors (PMCTs) are rare and histologically heterogeneous. Objective: To compare demographics, specific ICD-O-3 morphologies, first-course treatment patterns, annual registered case counts, and unadjusted overall survival between soft-tissue and hematologic PMCTs. Methods: We identified 730 PMCT cases diagnosed from 2000 to 2021 in SEER 18 (ICD-O-3 topography C38.0). Histologic lineage was assigned from ICD-O-3 morphology. Comparative analyses included soft-tissue (n=458) and hematologic (n=212) tumors. First-course variables were primary-site surgery, chemotherapy (yes versus no/unknown), and radiotherapy (radiation versus none/unknown). Groups were compared with chi-square tests. Overall survival was estimated with Kaplan-Meier methods; follow-up was truncated at 120 months. Results: Soft-tissue PMCTs occurred predominantly at ages 45-64 years (67.9%), whereas hematologic PMCTs occurred predominantly at age [&ge;]65 years (63.2%; p<0.001). Men comprised 59.9% of hematologic and 49.3% of soft-tissue cases (p=0.014). The leading soft-tissue morphology was hemangiosarcoma/angiosarcoma (ICD-O-3 9120/3; 201/458, 43.9%); synovial sarcoma accounted for 20/458 cases (4.4%). Diffuse large B-cell lymphoma, NOS, accounted for 131/212 hematologic tumors (61.8%). Any primary-site surgery was recorded in 66.6% of soft-tissue versus 15.6% of hematologic cases (p<0.001). Chemotherapy was recorded in 67.5% versus 51.1% (p<0.001), and radiotherapy in 9.0% versus 20.5% (p<0.001). In exploratory Kaplan-Meier analyses, hematologic patients with recorded chemotherapy had higher unadjusted 120-month overall survival than those without recorded chemotherapy (42.0% versus 12.2%; log-rank p=7.5x10-). Radiation-associated survival differences were not statistically significant in either lineage. Conclusions: Soft-tissue and hematologic PMCTs have distinct age distributions, named histologies, and first-course treatment patterns in SEER. These findings describe registry coding and do not establish treatment effectiveness or population incidence.

Background: Individuals undergoing lung cancer screening (LCS) represent a population at high risk for atherosclerotic cardiovascular disease (ASCVD), yet opportunities for cardiovascular prevention during screening encounters may be underutilized. While prior studies have examined whether statins are prescribed in eligible patients, little is known about the timing of statin initiation following LCS, particularly among statin-naive individuals. Methods: We conducted a retrospective cohort study using electronic health record data from a large academic health system in Missouri. Adults aged 50-80 who underwent LCS between January 1, 2015, and December 31, 2023, were statin-naive, and met 2019 ACC/AHA criteria for primary prevention were included. The primary outcome was time-to-statin initiation following LCS. Kaplan-Meier methods and Cox proportional hazards models were used to evaluate timing and predictors of statin initiation across demographic, clinical, and socioeconomic subgroups. Results: Among 3,100 statin-eligible, statin-naive individuals who had undergone LCS, only 27.3% were prescribed a statin within one year of LCS. Uptake accrued gradually (10.5% by 90 days; 17.8% by 180 days; 23.2% by 270 days; 27.1% by 360 days). In adjusted models, earlier statin initiation was independently associated with a higher ASCVD risk category, a cardiology visit in the year preceding LCS, and former (versus current) smoking; older age and male sex were associated with slower initiation. Race, insurance type, and area deprivation were not independently associated with time-to-statin initiation. Conclusions: Despite high ASCVD risk, most statin-eligible patients undergoing LCS did not receive timely statin therapy. Earlier initiation tracked calculated ASCVD risk and specialty (cardiology) contact rather than race, sex, insurance, or area deprivation. Because most patients at high calculated risk still went untreated, integrating cardiovascular risk assessment and preventive decision support into LCS workflows may help reduce missed opportunities for ASCVD prevention.

Background: Delayed diagnosis of immunoglobulin light-chain cardiac amyloidosis (AL-CA) worsens prognosis, partly because AL-CA and wild-type transthyretin cardiac amyloidosis (ATTRwt-CA) are difficult to distinguish at the initial cardiology visit. We developed and validated a practical score to triage AL-CA from ATTRwt-CA. Methods: We retrospectively analyzed 541 consecutive patients with cardiac amyloidosis (91 AL-CA, 450 ATTRwt-CA) at our institution's amyloidosis center, randomly divided into derivation (n=378) and validation (n=163) cohorts. Candidate first-visit variables underwent LASSO selection after multiple imputation, with estimates pooled by Rubin's rules. Performance was assessed by bootstrap validation, calibration, and decision curve analysis. The model was converted into a simplified point-based score. Results: Seven variables were retained: age, absence of atrial fibrillation, absence of carpal tunnel syndrome, low serum albumin, proteinuria ([&ge;]1+), low voltage, and thinner left ventricular posterior wall thickness. Areas under the curve (AUC) were 0.97 in the derivation cohort and 0.99 in the validation cohort; the bootstrap optimism-corrected AUC was 0.96. The model provided net benefit across threshold probabilities of 0.01-0.50. Risk tiering categorized the validation cohort into low (0-5 points; AL-CA 0%), intermediate (6?9 points; 26%), and high (10-13 points; 95%) probability groups. Discrimination remained high for AL-CA versus monoclonal protein-positive ATTRwt-CA at a cutoff of [&ge;]8 points (AUC 0.90). Adding this score to monoclonal protein testing significantly improved diagnostic performance compared with monoclonal protein testing alone. Conclusions: This simple first-visit score may help cardiologists rapidly triage suspected AL-CA and prioritize urgent hematology referral and subtype-specific confirmatory testing.

Background: Environmental noise and air pollution are both shaped by road traffic and the built environment, and exposure assessment increasingly folds them into composite indices or proxies both by traffic exposure. Whether the two share a social distribution has rarely been tested against direct measurement of several exposures in the same communities, and community noise is almost always characterized by A-weighted levels alone, which discount low-frequency energy. Methods: At 176 sites across Rhode Island, spanning the contiguous urban area of Providence, Central Falls, and Pawtucket together with four rural municipalities, we measured the acoustic environment under A- and C-weighting (LAeq, LCeq), fine particulate matter (PM2.5), night-time illuminance, and relative humidity across four session types over roughly one year (704 site-sessions). Exposures were linked to census-tract composition (American Community Survey), and mixed-effects models were fitted for each of eight area-level markers of disadvantage, adjusting for campaign and session. Relative humidity was carried through the identical model as a negative control. Results: A-weighted noise was consistently higher in more disadvantaged tracts, rising with non-White, poverty, renter, and no-vehicle shares and falling with income and older-resident share (six of eight markers significant; 1.3 to 1.8 dBA per standard deviation; 6.6 dBA between the least and most racially diverse neighborhoods). C-weighted levels followed the same gradient on every marker and exceeded their A-weighted counterparts at block-group scale for renter occupancy and vehicle absence. Night-time illuminance was also socially patterned, whereas short-term PM2.5 was roughly an order of magnitude weaker and relative humidity showed no gradient. The acoustic gradient persisted within the urban core alone. Conclusions: Measured burden was carried by the acoustic environment, including its low-frequency component, and by night-time light, not by short-term particulates. The exposure metric and the averaging time determine which disparities are visible at all.

Background: Sleep-disordered breathing (SDB) is an established adverse prognostic factor in heart failure (HF). Sleep apnea-specific hypoxic burden (SASHB), which reflects the duration and depth of respiratory event-related oxygen desaturation, has shown stronger prognostic value than the apnea-hypopnea index (AHI) in general populations and patients with coronary artery disease. However, its clinical utility in patients hospitalized due to acute HF remains unclear. Objectives: This study evaluated the prognostic value of SASHB in patients hospitalized for acute HF and compared its performance with AHI for risk stratification and identification of patients who may benefit from positive airway pressure (PAP) therapy. Methods: This post hoc analysis included 230 patients from a prospective single-center observational cohort of adults hospitalized for acute HF. The primary analysis included 178 patients who did not receive PAP treatment. Associations of SASHB and AHI with the composite endpoint of cardiovascular death or rehospitalization for worsening HF were evaluated using Cox proportional hazards models. Model improvement after adding SASHB or AHI to a model including established clinical risk factors was assessed using changes in the C index and Brier score, reflecting changes in model discrimination and prediction error, respectively. In the full cohort, the interaction between PAP treatment and SDB metrics was evaluated using the g-formula. Results: During a median follow-up of 3.7 years, 58 of 178 patients (32.6%) reached the composite endpoint. Both SASHB and AHI were independently associated with the composite outcome after multivariable adjustment. However, only SASHB consistently predicted outcomes across analyses and improved model performance beyond established prognostic factors (bootstrap {Delta} C index, 0.020 [95% CI: 0.008 - 0.031]; bootstrap {Delta} Brier score, - 0.007 [95% CI: - 0.014 to - 0.001]), whereas AHI did not. In the analysis including PAP-treated patients, both SASHB and AHI showed interaction with PAP treatment. Conclusions: In patients hospitalized for acute HF, SASHB showed a consistent independent association with adverse clinical outcomes and provided additional prognostic information beyond AHI. SASHB may improve risk stratification and may help identify patients who are more likely to benefit from PAP therapy.

IMPORTANCE: CD4+ T helper (T) 1, T2 and T17 cells have helped identify asthma endotypes in predominantly non-Hispanic White adults. Identifying asthma endotypes in diverse subgroups should help develop personalized medicine in asthma. OBJECTIVE: To characterize asthma endotypes and their association with selected variables and asthma severity/control in adults. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional and longitudinal analyses of nasal samples from the SOL-Asthma study of Puerto Rican and Dominican adults with (cases, n=313) and without (controls, n=371) asthma in the Bronx (NY) and Chicago (IL), with replication of selected findings in 376 adults of African ancestry in CAAPA. MAIN OUTCOMES AND MEASURES: Our primary outcome was asthma endotypes identified through nasal expression of "signature genes" for 3 T2, 5 T1, and 5 T17 pathways. Multinomial logistic regression was used for the analysis of asthma endotypes (with controls as the reference outcome category) at a baseline visit, as well as for the analysis of severe asthma exacerbations (SAEs) at baseline and during a 1-year follow-up. We attempted to replicate the identified profiles in CAAPA. RESULTS: In SOL-Asthma, cases were more likely to be female, Puerto Rican, and current/former smokers, and to have physician-diagnosed COPD than controls. Five transcriptomic profiles were identified in cases: T2HIGH (n=16 [5.1%]), T1HIGH (n=71 [22.7%]), T17HIGH (n=96 [30.7%]), T1HIGH/T17HIGH (n=53 [16.9%]), and T2LOW/T1LOW/T17LOW (n=77 [24.6%]). In a multivariable analysis, Puerto Ricans were more likely to have a T17HIGH profile than Dominicans (odds ratio [OR]=2.48, 95% confidence interval [CI]=1.08-5.74) and female sex was associated with T1HIGH (OR=3.44, 95% CI=1.33-8.88), T1HIGH/T17HIGH and T2LOW/T1LOW/T17LOW profiles, while COPD was associated with profiles other than T2HIGH or T1HIGH. The T1HIGH profile was associated with [&ge;]1 SAE in the year prior to baseline and during the one-year follow-up (OR=4.31, 95% CI=1.26-14.77). Each profile had unique differentially expressed genes (DEGs), with substantial replication of the profile distribution and DEGs in CAAPA. CONCLUSIONS AND RELEVANCE: Nasal transcriptomics identified profiles corresponding to five asthma endotypes in a cohort of Puerto Rican and Dominican adults. Puerto Rican background, female sex, and physician-diagnosed COPD were associated with non-T2HIGH (T2LOW) asthma endotypes, and T1HIGH asthma was strongly associated with SAEs.

Background: The Lung Transplant Frailty Scale (LT-FS) is a validated binary measure of frailty in lung transplant candidates. We aimed to refine the LT-FS Base and Body Composition measures by developing a three-category classification to improve clinical risk stratification with serum albumin as a more clinically practical frailty biomarker. Methods: To develop the refined LT-FS, we applied a 4-step measure development method to a multicenter prospective cohort study of lung transplant candidates. Low albumin (<3.5 g/dL) replaced high serum C-reactive protein ([&ge;]10 mg/L) as the LT-FS biomarker. Cutpoints that balanced discrimination, risk prediction, and calibration were identified to define ''frail'', ''pre-frail'', and ''not frail'' categories. Next, we evaluated associations between the refined LT-FS and exercise capacity, patient-reported outcomes, and mortality using multivariate linear and Cox regression. Results: Among 419 participants, the refined LT-FS identified a graded increase in mortality risk across frailty categories. For example, compared with candidates who were not frail, pre-frailty and frailty by the LT-FS Body Composition were associated with a 2.9-fold (HR 2.9, 95% CI 1.2-6.9) and 7-fold (HR 6.9, 95% CI 2.6-18.2) higher risk of waitlist delisting or death, respectively. Pre-frailty and frailty by LT-FS Body Composition were associated with 2-fold (HR 2.1, 95% CI 1.2-3.8) and 3.6-fold (HR 3.6, 95% CI 1.8-7.3) higher risk of mortality after transplant. Relationships with exercise capacity and patient-reported disability were less consistent. Conclusions: A refined Lung Transplant Frailty Scale incorporating serum albumin demonstrates strong associations with waitlist and post-transplant mortality. The addition of a pre-frail category better captures the continuum of frailty and improves clinical risk stratification of lung transplant candidates.