Association of Short-Term Increases in Ambient Fine Particulate Matter With Hospitalization for Asthma or COPD During Wildfire Season and Other Time Periods.

BACKGROUND: Short-term increases in air pollution are associated with poor asthma and COPD outcomes. Short-term elevations in fine particulate matter (PM2.5) due to wildfire smoke are becoming more common. RESEARCH QUESTION: Are short-term increases in PM2.5 and ozone in wildfire season and in winter inversion season associated with a composite of emergency or inpatient hospitalization for asthma and COPD? STUDY DESIGN AND METHODS: Case-crossover analyses evaluated 63,976 and 18,514 patients hospitalized for primary discharge diagnoses of asthma and COPD, respectively, between January 1999 and March 2022. Patients resided on Utah's Wasatch Front where PM2.5 and ozone were measured by Environmental Protection Agency-based monitors. ORs were calculated using Poisson regression adjusted for weather variables. RESULTS: Asthma risk increased on the same day that PM2.5 increased during wildfire season (OR, 1.057 per + 10 µg/m3; 95% CI, 1.019-1.097; P = .003) and winter inversions (OR, 1.023 per +10 µg/m3; 95% CI, 1.010-1.037; P = .0004). Risk decreased after 1 week, but during wildfire season risk rebounded at a 4-week lag (OR, 1.098 per +10 µg/m3; 95% CI, 1.033-1.167). Asthma risk for adults during wildfire season was highest in the first 3 days after PM2.5 increases, but for children, the highest risk was delayed by 3 to 4 weeks. PM2.5 exposure was weakly associated with COPD hospitalization. Ozone exposure was not associated with elevated risks. INTERPRETATION: In a large urban population, short-term increases in PM2.5 during wildfire season were associated with asthma hospitalization, and the effect sizes were greater than for PM2.5 during inversion season.

Alveolar macrophages from EVALI patients and e-cigarette users: a story of shifting phenotype.

Exposure to e-cigarette vapors alters important biologic processes including phagocytosis, lipid metabolism, and cytokine activity in the airways and alveolar spaces. Little is known about the biologic mechanisms underpinning the conversion to e-cigarette, or vaping, product use-associated lung injury (EVALI) from normal e-cigarette use in otherwise healthy individuals. We compared cell populations and inflammatory immune populations from bronchoalveolar lavage fluid in individuals with EVALI to e-cigarette users without respiratory disease and healthy controls and found that e-cigarette users with EVALI demonstrate a neutrophilic inflammation with alveolar macrophages skewed towards inflammatory (M1) phenotype and cytokine profile. Comparatively, e-cigarette users without EVALI demonstrate lower inflammatory cytokine production and express features associated with a reparative (M2) phenotype. These data indicate macrophage-specific changes are occurring in e-cigarette users who develop EVALI.

Prospectively Assessed Long-Term Outcomes of Patients with E-Cigarette- or Vaping-associated Lung Injury.

Rationale: E-cigarette- or vaping-associated lung injury (EVALI) was first identified in 2019. The long-term respiratory, cognitive, mood disorder, and vaping behavior outcomes of patients with EVALI remain unknown. Objectives: To determine the long-term respiratory, cognitive, mood disorder, and vaping behavior outcomes of patients with EVALI. Methods: We prospectively enrolled patients with EVALI from two health systems. We assessed outcomes at 1 year after onset of EVALI using validated instruments measuring cognitive function, depression, anxiety, post-traumatic stress, respiratory disability, coronavirus disease (COVID-19) infection, pulmonary function, and vaping behaviors. We used multivariable regression to identify risk factors of post-EVALI vaping behaviors and to identify whether admission to the intensive care unit (ICU) was associated with cognitive, respiratory, or mood symptoms. Results: Seventy-three patients completed 12-month follow-up. Most patients were male (66.7%), young (mean age, 31 ± 11 yr), and White (85%) and did not need admission to the ICU (59%). At 12 months, 39% (25 of 64) had cognitive impairment, whereas 48% (30 of 62) reported respiratory limitations. Mood disorders were common, with 59% (38 of 64) reporting anxiety and/or depression and 62% (39 of 63) having post-traumatic stress. Four (6.4%) of 64 reported a history of COVID-19 infection. Despite the history of EVALI, many people continued to vape. Only 38% (24 of 64) reported quitting all vaping and smoking behaviors. Younger age was associated with reduced vaping behavior after EVALI (odds ratio, 0.93; P = 0.02). ICU admission was not associated with cognitive impairment, dyspnea, or mood symptoms. Conclusions: Patients with EVALI, despite their youth, commonly have significant long-term respiratory disability; cognitive impairment; symptoms of depression, anxiety, post-traumatic stress; and persistent vaping.

Blood Eosinophil Count and Hospital Readmission in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

Purpose: This retrospective, observational cohort study investigated the association of blood eosinophil counts within 1 week of hospitalization for acute exacerbation of COPD (AECOPD) with subsequent risk of all-cause and COPD-related readmission from a large integrated health system. Patients and Methods: Electronic medical records were extracted for index hospitalization for AECOPD at all Intermountain Healthcare hospitals. The primary outcome was the relationship of blood eosinophil count to 30-day all-cause readmission; secondary outcomes were 60-day, 90-day, and 12-month all-cause readmission, COPD-related readmission, and empiric derivation of the eosinophil count with the highest area under the curve (AUC) for predicting 30-day all-cause readmission. Results: Of 2445 included patients, 1935 (79%) had a blood eosinophil count <300 cells/µL and 510 (21%) had a count ≥300 cells/µL. Using a 300-cells/µL threshold, there was no significant difference between high and low eosinophil groups in 30-day (odds ratio [OR]=1.05, 95% confidence interval [CI]=0.75-1.47) or 60-day (OR=1.15, 95% CI=0.88-1.51) all-cause readmissions. However, patients with greater (versus lesser) eosinophil counts had increased 90-day and 12-month all-cause readmissions (OR=1.35, 95% CI=1.06-1.72, and OR=1.32, 95% CI=1.07-1.62). COPD-related readmission rates were significantly greater for patients with greater (versus lesser) eosinophil counts at 30, 60, and 90 days and 12 months (OR range=1.52-1.97). A total of 70 cells/µL had the most discriminatory power to predict 30-day all-cause readmission (highest AUC). Conclusion: Eosinophil counts in patients with COPD were not associated with a difference in 30-day all-cause readmissions. However, greater eosinophil counts were associated with increased risk of all-cause readmission at 90 days and 12 months and COPD-related readmission at 30, 60, and 90 days and 12 months. Patients with eosinophils <70 cells/µL had the lowest risk for 30-day all-cause readmission. Blood eosinophils in patients hospitalized with AECOPD may be a useful biomarker for the risk of hospital readmission.

Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST).

BACKGROUND: The National Lung Screening Trial (NLST) demonstrated that annual screening with low dose CT in high-risk population was associated with reduction in lung cancer mortality. Nonetheless, the leading cause of mortality in the study was from cardiovascular diseases. PURPOSE: To determine whether the used machine learning automatic algorithms assessing coronary calcium score (CCS), level of liver steatosis and emphysema percentage in the lungs are good predictors of cardiovascular disease (CVD) mortality and incidence when applied on low dose CT scans. MATERIALS AND METHODS: Three fully automated machine learning algorithms were used to assess CCS, level of liver steatosis and emphysema percentage in the lung. The algorithms were used on low-dose computed tomography scans acquired from 12,332 participants in NLST. RESULTS: In a multivariate analysis, association between the three algorithm scores and CVD mortality have shown an OR of 1.72 (p = 0.003), 2.62 (p < 0.0001) for CCS scores of 101-400 and above 400 respectively, and an OR of 1.12 (p = 0.044) for level of liver steatosis. Similar results were shown for the incidence of CVD, OR of 1.96 (p < 0.0001), 4.94 (p < 0.0001) for CCS scores of 101-400 and above 400 respectively. Also, emphysema percentage demonstrated an OR of 0.89 (p < 0.0001). Similar results are shown for univariate analyses of the algorithms. CONCLUSION: The three automated machine learning algorithms could help physicians to assess the incidence and risk of CVD mortality in this specific population. Application of these algorithms to existing LDCT scans can provide valuable health care information and assist in future research.

The Summit Score Stratifies Mortality and Morbidity in Chronic Obstructive Pulmonary Disease.

Introduction: Tobacco use and other cardiovascular risk factors often accompany chronic obstructive pulmonary disease (COPD). This study derived and validated the Summit Score to predict mortality in people with COPD and cardiovascular risks. Methods: SUMMIT trial subjects (N=16,485) ages 40-80 years with COPD were randomly assigned 50%/50% to derivation (N=8181) and internal validation (N=8304). Three external COPD validations from Intermountain Healthcare included outpatients with cardiovascular risks (N=9251), outpatients without cardiovascular risks (N=8551), and inpatients (N=26,170). Cox regression evaluated 40 predictors of all-cause mortality. SUMMIT treatments including combined fluticasone furoate (FF) 100µg/vilanterol 25µg (VI) were not included in the score. Results: Mortality predictors were FEV1, heart rate, systolic blood pressure, body mass index, age, smoking pack-years, prior COPD hospitalizations, myocardial infarction, heart failure, diabetes, anti-thrombotics, anti-arrhythmics, and xanthines. Combined in the Summit Score (derivation: c=0.668), quartile 4 vs 1 had HR=4.43 in SUMMIT validation (p<0.001, 95% CI=3.27, 6.01, c=0.662) and HR=8.15 in Intermountain cardiovascular risk COPD outpatients (p<0.001, 95% CI=5.86, 11.34, c=0.736), and strongly predicted mortality in the other Intermountain COPD populations. Among all SUMMIT subjects with scores 14-19, FF 100µg/VI 25µg vs placebo had HR=0.76 (p=0.0158, 95% CI=0.61, 0.95), but FF 100µg/VI 25µg was not different from placebo for scores <14 or >19. Conclusion: In this post hoc analysis of SUMMIT trial data, the Summit Score was derived and validated in multiple Intermountain COPD populations. The score was used to identify a subpopulation in which mortality risk was lower for FF 100µg/VI 25µg treatment. Trial Registration: The SUMMIT trial is registered at ClinicalTrials.gov as number NCT01313676.

Laboratory-based Intermountain Validated Exacerbation (LIVE) Score stability in patients with chronic obstructive pulmonary disease.

BACKGROUND: The Laboratory-based Intermountain Validated Exacerbation (LIVE) Score is associated with mortality and chronic obstructive pulmonary disease (COPD) exacerbation risk across multiple health systems. However, whether the LIVE Score and its associated risk is a stable patient characteristic is unknown. METHODS: We validated the LIVE Score in a fourth health system. Then we determined the LIVE Score stability in a retrospective cohort of 98 766 patients with COPD in four health systems where it was previously validated. We assessed whether LIVE Scores changed or remained the same over time. Stability was defined as a majority of surviving patients having the same LIVE Score 4 years later. RESULTS: The LIVE Score separated patients into three LIVE Score risk groups of low, medium, and high mortality and LIVE Score stability. Mortality ranged from 6.2% for low-risk LIVE to 45.8% for high-risk LIVE (p<0.001). We found that low-risk LIVE groups were stable and high-risk LIVE groups were unstable. Low-risk LIVE group patients remained low risk, but few high-risk LIVE group patients remained high risk (79.0% high vs 48.1% medium vs 8.8% low, p<0.001 for all pairwise comparisons). CONCLUSION: The LIVE Score identifies three major clinically actionable cohorts: a stable low-risk LIVE group, an unstable high-risk LIVE group with high mortality rates, and a medium-risk LIVE group. These observations further our understanding of how existing data used to calculate the LIVE Score may target interventions across risk cohorts of patients with COPD in a health system.

Diagnosis of EVALI: General Approach and the Role of Bronchoscopy.

A 23-year-old man arrives at the ED with a 3-week history of dyspnea, dry cough, fevers, and night sweats. Two weeks previously, he was evaluated in an outpatient clinic and given a course of azithromycin for presumed infectious pneumonia. His symptoms did not improve, and he was seen 1 week later in an urgent care center and given a prescription for doxycycline, which he has been taking without improvement. He states that he feels miserable, has severe nausea and vomiting, and has not eaten in several days. His only medical history is childhood asthma. He reports no surgeries and takes no medications. He has no risk factors for HIV, does not smoke combustible cigarettes or use IV drugs, and has not recently traveled. Examination shows a room air saturation of 89%, a temperature of 38.3°C, and a respiratory rate of 22 breaths/min. Results of his examination are normal, and there are no rales or wheezing heard in the lungs. Chest radiograph shows bilateral, consolidative opacities. WBC count is 14,000, with left shift. Results of biochemistries are normal. Erythrocyte sedimentation rate is 104, and procalcitonin is 0.08. Urine toxicology screen is positive for tetrahydrocannabinol (THC). Asked specifically about vaping and e-cigarette use, he reports that he recently began using THC "carts" that his friend gets from an unknown supplier. What is the diagnosis and what additional steps are necessary to confirm it? Is bronchoscopy indicated?

Clinical presentation, treatment, and short-term outcomes of lung injury associated with e-cigarettes or vaping: a prospective observational cohort study.

BACKGROUND: An ongoing outbreak of lung injury associated with e-cigarettes or vaping (also known as E-VALI or VALI) started in March, 2019, in the USA. The cause, diagnosis, treatment, and course of this disease remains unknown. METHODS: In this multicentre, prospective, observational, cohort study, we collected data on all patients with lung injury associated with e-cigarettes or vaping seen in Intermountain Healthcare, an integrated health system based in Utah, USA, between June 27 and Oct 4, 2019. Telecritical care, based in Salt Lake City, UT, USA, was used as the central repository for case validation, public reporting, and system-wide dissemination of expertise, which included a proposed diagnosis and treatment guideline for lung injury associated with e-cigarettes or vaping. We extracted data on patient presentation, treatment, and short-term follow-up (2 weeks after discharge) from chart review and interviews with patients undertaken by the Utah Department of Health (Salt Lake City, UT, USA). FINDINGS: 60 patients presented with lung injury associated with e-cigarettes or vaping at 13 hospitals or outpatient clinics in the integrated health system. 33 (55%) of 60 were admitted to an intensive care unit (ICU). 53 (88%) of 60 patients presented with constitutional symptoms, 59 (98%) with respiratory symptoms, and 54 (90%) with gastrointestinal symptoms. 54 (90%) of 60 were given antibiotics and 57 (95%) were given steroids. Six (10%) of 60 patients were readmitted to an ICU or hospital within 2 weeks, three (50%) of whom had relapsed with vaping or e-cigarette use. Of 26 patients who were followed up within 2 weeks, despite clinical and radiographic improvement in all, many had residual abnormalities on chest radiographs (ten [67%] of 15) and pulmonary function tests (six [67%] of nine). Two patients died and lung injury associated with e-cigarettes or vaping was thought to be a contributing factor, but not the cause of death, for both. INTERPRETATION: Lung injury associated with e-cigarettes or vaping is an emerging illness associated with severe lung injury and constitutional and gastrointestinal symptoms. Increased awareness has led to identification of a broad spectrum of severity of illness in patients who were treated with antibiotics and steroids. Despite improvement, at short-term follow-up many patients had residual abnormalities. Lung injury associated with e-cigarettes or vaping remains a clinical diagnosis with symptoms that overlap infectious and other lung diseases. Maintaining a high index of suspicion for this disease is important as work continues in understanding the cause or causes, optimal therapy, and long-term outcomes of these patients. FUNDING: Intermountain Healthcare.