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.

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.

Short-Term Elevation of Fine Particulate Matter Air Pollution and Acute Lower Respiratory Infection.

RATIONALE: Nearly 60% of U.S. children live in counties with particulate matter less than or equal to 2.5 µm in aerodynamic diameter (PM2.5) concentrations above air quality standards. Understanding the relationship between ambient air pollution exposure and health outcomes informs actions to reduce exposure and disease risk. OBJECTIVES: To evaluate the association between ambient PM2.5 levels and healthcare encounters for acute lower respiratory infection (ALRI). METHODS: Using an observational case-crossover design, subjects (n = 146,397) were studied if they had an ALRI diagnosis and resided on Utah's Wasatch Front. PM2.5 air pollution concentrations were measured using community-based air quality monitors between 1999 and 2016. Odds ratios for ALRI healthcare encounters were calculated after stratification by ages 0-2, 3-17, and 18 or more years. MEASUREMENTS AND MAIN RESULTS: Approximately 77% (n = 112,467) of subjects were 0-2 years of age. The odds of ALRI encounter for these young children increased within 1 week of elevated PM2.5 and peaked after 3 weeks with a cumulative 28-day odds ratio of 1.15 per +10 µg/m3 (95% confidence interval, 1.12-1.19). ALRI encounters with diagnosed and laboratory-confirmed respiratory syncytial virus and influenza increased following elevated ambient PM2.5 levels. Similar elevated odds for ALRI were also observed for older children, although the number of events and precision of estimates were much lower. CONCLUSIONS: In this large sample of urban/suburban patients, short-term exposure to elevated PM2.5 air pollution was associated with greater healthcare use for ALRI in young children, older children, and adults. Further exploration is needed of causal interactions between PM2.5 and ALRI.

Comparison of NHANES III and ERS/GLI 12 for airway obstruction classification and severity.

The diagnosis and severity categorisation of obstructive lung disease is determined using reference values. The American Thoracic Society/European Respiratory Society in 2005 recommended the National Health and Nutrition Examination Survey (NHANES) III spirometry prediction equations for patients in USA aged 8-80 years. The Global Lung Initiative 2012 (GLI 12) provided spirometry prediction equations for patients aged 3-95 years. Comparison of the NHANES III and GLI 12 prediction equations for diagnosing and categorising airway obstruction in patients in USA has not been made.We aimed to quantify the differences between NHANES III and GLI 12 predicted values in Caucasians aged 18-95 years, using both mathematical simulation and clinical data. We compared predicted forced expiratory volume in 1 s (FEV1) and lower limit of normal (LLN) FEV1/forced vital capacity (FVC) % for NHANES III and GLI 12 prediction equations by applying both a simulation model and clinical spirometry data to quantify differences in the diagnosis and categorisation of airway obstruction.Mathematical simulation revealed significant similarities and differences between prediction equations for both LLN FEV1/FVC % and predicted FEV1 There are significant differences when using GLI 12 and NHANES III to diagnose airway obstruction and severity in Caucasian patients aged 18-95 years.Similarities and differences exist between NHANES III and GLI 12 for some age and height combinations. The differences in LLN FEV1/FVC % and predicted FEV1 are most prominent in older taller/shorter individuals. The magnitude of the differences can be large and may result in differences in clinical management.

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.

Airway epithelial miRNA expression is altered in asthma.

RATIONALE: Changes in airway epithelial cell differentiation, driven in part by IL-13, are important in asthma. Micro-RNAs (miRNAs) regulate cell differentiation in many systems and could contribute to epithelial abnormalities in asthma. OBJECTIVES: To determine whether airway epithelial miRNA expression is altered in asthma and identify IL-13-regulated miRNAs. METHODS: We used miRNA microarrays to analyze bronchial epithelial brushings from 16 steroid-naive subjects with asthma before and after inhaled corticosteroids, 19 steroid-using subjects with asthma, and 12 healthy control subjects, and the effects of IL-13 and corticosteroids on cultured bronchial epithelial cells. We used quantitative polymerase chain reaction to confirm selected microarray results. MEASUREMENTS AND MAIN RESULTS: Most (12 of 16) steroid-naive subjects with asthma had a markedly abnormal pattern of bronchial epithelial miRNA expression by microarray analysis. Compared with control subjects, 217 miRNAs were differentially expressed in steroid-naive subjects with asthma and 200 in steroid-using subjects with asthma (false discovery rate < 0.05). Treatment with inhaled corticosteroids had modest effects on miRNA expression in steroid-naive asthma, inducing a statistically significant (false discovery rate < 0.05) change for only nine miRNAs. qPCR analysis confirmed differential expression of 22 miRNAs that were highly differentially expressed by microarrays. IL-13 stimulation recapitulated changes in many differentially expressed miRNAs, including four members of the miR-34/449 family, and these changes in miR-34/449 family members were resistant to corticosteroids. CONCLUSIONS: Dramatic alterations of airway epithelial cell miRNA levels are a common feature of asthma. These alterations are only modestly corrected by inhaled corticosteroids. IL-13 effects may account for some of these alterations, including repression of miR-34/449 family members that have established roles in airway epithelial cell differentiation. Clinical trial registered with www.clinicaltrials.gov (NCT 00595153).

The evolution of eProtocols that enable reproducible clinical research and care methods.

Unnecessary variation in clinical care and clinical research reduces our ability to determine what healthcare interventions are effective. Reducing this unnecessary variation could lead to further healthcare quality improvement and more effective clinical research. We have developed and used electronic decision support tools (eProtocols) to reduce unnecessary variation. Our eProtocols have progressed from a locally developed mainframe computer application in one clinical site (LDS Hospital) to web-based applications available in multiple languages and used internationally. We use eProtocol-insulin as an example to illustrate this evolution. We initially developed eProtocol-insulin as a local quality improvement effort to manage stress hyperglycemia in the adult intensive care unit (ICU). We extended eProtocol-insulin use to translate our quality improvement results into usual clinical care at Intermountain Healthcare ICUs. We exported eProtocol-insulin to support research in other US and international institutions, and extended our work to the pediatric ICU. We iteratively refined eProtocol-insulin throughout these transitions, and incorporated new knowledge about managing stress hyperglycemia in the ICU. Based on our experience in the development and clinical use of eProtocols, we outline remaining challenges to eProtocol development, widespread distribution and use, and suggest a process for eProtocol development. Technical and regulatory issues, as well as standardization of protocol development, validation and maintenance, need to be addressed. Resolution of these issues should facilitate general use of eProtocols to improve patient care.

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.

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?

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.

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.

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.

The Laboratory-Based Intermountain Validated Exacerbation (LIVE) Score Identifies Chronic Obstructive Pulmonary Disease Patients at High Mortality Risk.

Background: Identifying COPD patients at high risk for mortality or healthcare utilization remains a challenge. A robust system for identifying high-risk COPD patients using Electronic Health Record (EHR) data would empower targeting interventions aimed at ensuring guideline compliance and multimorbidity management. The purpose of this study was to empirically derive, validate, and characterize subgroups of COPD patients based on routinely collected clinical data widely available within the EHR. Methods: Cluster analysis was used in 5,006 patients with COPD at Intermountain to identify clusters based on a large collection of clinical variables. Recursive Partitioning (RP) was then used to determine a preferred tree that assigned patients to clusters based on a parsimonious variable subset. The mortality, COPD exacerbations, and comorbidity profile of the identified groups were examined. The findings were validated in an independent Intermountain cohort and in external cohorts from the United States Veterans Affairs (VA) and University of Chicago Medicine systems. Measurements and Main Results: The RP algorithm identified five LIVE Scores based on laboratory values: albumin, creatinine, chloride, potassium, and hemoglobin. The groups were characterized by increasing risk of mortality. The lowest risk, LIVE Score 5 had 8% 4-year mortality vs. 56% in the highest risk LIVE Score 1 (p < 0.001). These findings were validated in the VA cohort (n = 83,134), an expanded Intermountain cohort (n = 48,871) and in the University of Chicago system (n = 3,236). Higher mortality groups also had higher COPD exacerbation rates and comorbidity rates. Conclusions: In large clinical datasets across different organizations, the LIVE Score utilizes existing laboratory data for COPD patients, and may be used to stratify risk for mortality and COPD exacerbations.

Stability of Frequency of Severe Chronic Obstructive Pulmonary Disease Exacerbations and Health Care Utilization in Clinical Populations.

Rationale: Although chronic obstructive pulmonary disease (COPD) exacerbation frequency is stable in research cohorts, whether severe COPD exacerbation frequency can be used to identify patients at high risk for future severe COPD exacerbations and/or mortality is unknown. Methods: Severe COPD exacerbation frequency stability was determined in 3 distinct clinical cohorts. A total of 17,450 patients with COPD in Intermountain Healthcare were categorized based on the number of severe COPD exacerbations per year. We determined whether exacerbation frequency was stable and whether it predicted mortality. These findings were validated in 83,134 patients from the U.S. Veterans Affairs (VA) nationwide health care system and 3326 patients from the University of Chicago Medicine health system. Results: In the Intermountain Healthcare cohort, the majority (84%, 14,706 patients) had no exacerbations in 2009 and were likely to remain non-exacerbators with a significantly lower 6-year mortality compared with frequent exacerbators (2 or more exacerbations per year) (25% versus 57%, p<0.001). Similar findings were noted in the VA health system and the University of Chicago Medicine health system. Non-exacerbators were likely to remain non-exacerbators with the lowest overall mortality. In all cohorts, frequent exacerbator was not a stable phenotype until patients had at least 2 consecutive years of frequent exacerbations. COPD exacerbation frequency predicted any cause mortality. Conclusions: In clinical datasets across different organizations, severe COPD exacerbation frequency was stable after at least 2 consecutive years of frequent exacerbations. Thus, severe COPD exacerbation frequency identifies patients across a health care system at high risk for future COPD-related health care utilization and overall mortality.