Compliance with recommended pneumococcal vaccination schedule in patients treated for rheumatoid arthritis: A retrospective cohort study in the Veterans Affairs population.

INTRODUCTION: Invasive pneumococcal disease (IPD) is a leading cause of death. Rheumatoid arthritis (RA) patients are at risk of IPD due to immunosuppressant medications. Up until 2022, two pneumococcal vaccines, the 13-valent Pneumococcal conjugate vaccine (PCV13) and pneumococcal polysaccharide vaccine (PPSV23), were recommended. Despite the recommendation change to give a single 20-valent PCV vaccine (PCV20), some still require multiple vaccinations. There is a need to identify barriers to vaccine uptake. METHODS: We conducted a retrospective cohort study to assess the on-time vaccination rates for PCV13 and PPSV23 in treated RA patients between 2010 and 2018 using national Veterans Affairs data. Patients > 18 years of age diagnosed with RA and newly initiated on RA treatment were included. Pneumococcal vaccine compliance was assessed by measuring on-time receipt of PCV13 and PPSV23 vaccinations. We identified factors using multivariate logistic regression and described the occurrence of these factors using descriptive statistics. RESULTS: A total of 39,243 patients were included in the study. Most patients were white (75.8 %), male (85.4 %), on methotrexate therapy (41.4 %). The average age was 62.3 years. The proportion of patients considered vaccine compliant is 43.9 %. The primary independent risk factors for vaccine non-compliance were black/African American race (Odds Ratio [OR] 1.26, 95 % Confidence Interval [CI] 1.19-1.34) or missing/unknown race (OR 1.45, 95 % CI 1.31-1.61), missing/unknown ethnicity (OR 1.21, 1.02-1.43), never married (OR 1.10, 95 % CI 1.02-1.19) or widowed (OR 1.23, 95 % CI 1.12-1.34), diagnosed with congestive heart failure (OR 1.10, 95 % CI 1.00-1.22), or dementia (OR 1.48, 95 % CI 1.16-1.91). The proportion of patients who were non-compliant in patients who were vaccine naïve was 32.1 % and the non-compliance rate for non-naïve patients was 65.3 %. CONCLUSIONS: Providers should identify barriers to pneumococcal vaccination in RA patients to improve compliance. Efforts to increase vaccination should be tailored to specific high-risk groups.

Transcriptomic responses in the blood and sputum of cigarette smokers compared to e-cigarette vapers.

RATIONALE: Electronic (e)-cigarettes are popular among youth and cigarette smokers attempting to quit. Studies to date have focused on the utility of e-cigarettes as a smoking cessation tool, but the biological effects are largely unknown. OBJECTIVES: To identify transcriptomic differences in the blood and sputum of e-cigarette users compared to conventional cigarettes smokers and healthy controls and describe biological pathways affected by these tobacco products. METHODS: Cross-sectional analysis of whole blood and sputum RNA-sequencing data from 8 smokers, 9 e-cigarette users (e-cigs) and 4 controls. Weighted gene co-network analysis (WGCNA) identified gene module associations. Ingenuity Pathway Analysis (IPA) identified canonical pathways associated with tobacco products. MAIN RESULTS: In blood, a three-group comparison showed 16 differentially expressed genes (DEGs); pair-wise comparison showed 7 DEGs between e-cigs and controls, 35 DEGs between smokers and controls, and 13 DEGs between smokers and e-cigs. In sputum, 438 DEGs were in the three-group comparison. In pair-wise comparisons, there were 2 DEGs between e-cigs and controls, 270 DEGs between smokers and controls, and 468 DEGs between smokers and e-cigs. Only 2 genes in the smokers vs. control comparison overlapped between blood and sputum. Most gene modules identified through WGCNA associated with tobacco product exposures also were associated with cotinine and exhaled CO levels. IPA showed more canonical pathways altered by conventional cigarette smoking than by e-cigarette use. CONCLUSION: Cigarette smoking and e-cigarette use led to transcriptomic changes in both blood and sputum. However, conventional cigarettes induced much stronger transcriptomic responses in both compartments.

Prospective predictors of electronic nicotine delivery system initiation in tobacco naive young adults: A machine learning approach.

The use of electronic nicotine delivery systems (ENDS) is increasing among young adults. However, there are few studies regarding predictors of ENDS initiation in tobacco-naive young adults. Identifying the risk and protective factors of ENDS initiation that are specific to tobacco-naive young adults will enable the creation of targeted policies and prevention programs. This study used machine learning (ML) to create predictive models, identify risk and protective factors for ENDS initiation for tobacco-naive young adults, and the relationship between these predictors and the prediction of ENDS initiation. We used nationally representative data of tobacco-naive young adults in the U.S drawn from the Population Assessment of Tobacco and Health (PATH) longitudinal cohort survey. Respondents were young adults (18-24 years) who had never used any tobacco products in Wave 4 and who completed Waves 4 and 5 interviews. ML techniques were used to create models and determine predictors at 1-year follow-up from Wave 4 data. Among the 2,746 tobacco-naive young adults at baseline, 309 initiated ENDS use at 1-year follow-up. The top five prospective predictors of ENDS initiation were susceptibility to ENDS, increased days of physical exercise specifically designed to strengthen muscles, frequency of social media use, marijuana use and susceptibility to cigarettes. This study identified previously unreported and emerging predictors of ENDS initiation that warrant further investigation and provided comprehensive information on the predictors of ENDS initiation. Furthermore, this study showed that ML is a promising technique that can aid ENDS monitoring and prevention programs.

SARS-CoV-2 Antibody Dynamics in Healthcare Workers after mRNA Vaccination.

Since the emergence of SARS-CoV-2, maintaining healthcare worker (HCW) health and safety has been fundamental to responding to the global pandemic. Vaccination with mRNA-base vaccines targeting SARS-CoV-2 spike protein has emerged as a key strategy in reducing HCW susceptibility to SARS-CoV-2, however, neutralizing antibody responses subside with time and may be influenced by many variables. We sought to understand the dynamics between vaccine products, prior clinical illness from SARS-CoV-2, and incidence of vaccine-associated adverse reactions on antibody decay over time in HCWs at a university medical center. A cohort of 296 HCWs received standard two-dose vaccination with either bnt162b2 (Pfizer/BioNTech) or mRNA-1273 (Moderna) and were evaluated after two, six, and nine months. Subjects were grouped by antibody decay curve into steep antibody decliners gentle decliners. Vaccination with mRNA-1273 led to more sustained antibody responses compared to bnt162b2. Subjects experiencing vaccine-associated symptoms were more likely to experience a more prolonged neutralizing antibody response. Subjects with clinical SARS-CoV-2 infection prior to vaccination were more likely to experience vaccination-associated symptoms after first vaccination and were more likely to have a more blunted antibody decay. Understanding factors associated with vaccine efficacy may assist clinicians in determining appropriate vaccine strategies in HCWs.

Metformin Use Is Associated With Lower Mortality in Veterans With Diabetes Hospitalized With Pneumonia.

BACKGROUND: Recent studies suggest that metformin use may be associated with improved infectious disease-related outcomes, whereas other papers suggest potentially worse outcomes in serious bacterial infections. Our purpose was to examine the association of prior outpatient prescription of metformin on 30- and 90-day mortality for older veterans with pre-existing diabetes hospitalized with pneumonia. METHODS: We conducted a retrospective cohort study using national Department of Veterans Affairs data of patients ≥65 years with a prior history of diabetes who were hospitalized with pneumonia over a 10-year period (fiscal years 2002-2012.) For our primary analysis, we created a propensity score and matched metformin users to nonusers 1:1. RESULTS: We identified 34 759 patients who met the inclusion criteria, 20.3% of whom were prescribed metformin. Unadjusted 30-day mortality was 9.6% for those who received metformin versus 13.9% in nonusers (P < .003), and 90-day mortality was 15.8% for those who received metformin versus 23.0% for nonusers (P < .0001). For the propensity score model, we matched 6899 metformin users to 6899 nonusers. After propensity matching, both 30-day (relative risk [RR]: .86; 95% confidence interval [CI]: .78-.95) and 90-day (RR: .85; 95% CI: .79-.92) mortality was significantly lower for metformin users. CONCLUSIONS: Prior receipt of metformin was associated with significantly lower mortality after adjusting for potential confounders. Additional research is needed to examine the safety and potential benefits of metformin use in patients with respiratory infections.

Effectiveness of Beta-Lactam plus Doxycycline for Patients Hospitalized with Community-Acquired Pneumonia.

BACKGROUND: Despite clinical practice guideline recommendations to use doxycycline as part of combination therapy for some patients hospitalized with pneumonia, there is minimal evidence supporting this recommendation. Our aim was to examine the association between beta-lactam plus doxycycline and mortality for patients hospitalized with community-acquired pneumonia. METHODS: We identified patients >65 years of age admitted to any US Department of Veterans Affairs hospital in fiscal years 2002-2012 with a discharge diagnosis of pneumonia. We excluded those patients who did not receive antibiotic therapy concordant with the 2019 American Thoracic Society/Infectious Diseases Society of America (ATS/IDSA) clinical practice guidelines. Using propensity score matching, we examined the association of doxycycline with 30- and 90-day mortality. RESULTS: Our overall cohort was comprised of 70533 patients and 5282 (7.49%) received doxycycline. Unadjusted 30-day mortality was 6.4% for those who received a beta-lactam plus doxycycline versus 9.1% in those who did not (P < .0001), and 90-day mortality was 13.8% for those who received a beta-lactam + doxycycline versus 16.8% for those who did not (P < .0001). In the propensity score matched models, both 30- (odds ratio 0.72, 95% confidence interval [CI], .63-.84) and 90-day (0.83, 95% CI, .74-.92) mortality were significantly lower for those who received doxycycline. CONCLUSIONS: In this retrospective observational cohort study, we found that doxycycline use, as part of guideline-concordant antibiotic therapy, was associated with lower 30- and 90-day mortality than regimens without doxycycline. While this supports the safety and effectiveness of antibiotic regimes that include doxycycline, additional studies, especially randomized clinical trials, are needed to confirm this.

E-Cigarette Use in Young Adult Never Cigarette Smokers with Disabilities: Results from the Behavioral Risk Factor Surveillance System Survey.

Young adult never cigarette smokers with disabilities may be at particular risk for adopting e-cigarettes, but little attention has been paid to these people. This study examines the associations between different types of disability and e-cigarette use in this population. Young adult never-smokers from the 2016-2017 Behavioral Risk Factor Surveillance System (BRFSS) survey who were either never or current e-cigarette users (n = 79,177) were selected for the analysis. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to select confounders for multivariable logistic regression models. Multivariable logistic regression models were used to determine the associations between current e-cigarette use and different types of disability after incorporating BRFSS survey design and adjusting for confounders. Young adult never-smokers who reported any disability had increased odds (OR 1.44, 95% CI 1.18-1.76) of e-cigarette use compared to those who reported no disability. Young adult never-smokers who reported self-care, cognitive, vision, and independent living disabilities had higher odds of e-cigarette use compared to those who reported no disability. There was no statistically significant difference in the odds of e-cigarette use for those reporting hearing and mobility disabilities compared to those who reported no disability. This study highlights the need for increased public education and cessation programs for this population.

Lactic acidosis incidence with metformin in patients with type 2 diabetes and chronic kidney disease: A retrospective nested case-control study.

Objective: Compare rates of lactic acidosis (LA) among metformin-exposed and unexposed patients with type 2 diabetes mellitus and varying degrees of chronic kidney disease (CKD). Research Design and Methods: Retrospective, nested case-control study using data from national VA Corporate Data Warehouse. All adult patients with type 2 diabetes and CKD newly dispensed any antihyperglycaemic medication during FY 2003-13 were included. The outcome was LA hospitalization or serum lactate >5 mEq/L. Exposure to metformin was evaluated in the three months prior to event. Estimates were adjusted for 31 covariates, including demographics, comorbidities and medications. Results: Overall, 320 882 patients were included, contributing a total of 1 331 784 person-years of follow-up. LA occurred in 2 665 patients, generating an overall incidence rate of 2.00 (95% CI 1.93-2.08) per 1000 person-years. Metformin exposure in the prior 3 months was associated with an elevated adjusted hazard of LA (HR 1.97, 95% CI 1.69-2.29). No association was evident in patients with CKD stage 1 or 2 (HR 1.05, 95% CI 0.71-1.57), but associations were present and progressively greater in patients with CKD stage 3a through 5: HR 3.09, 95% CI 2.19-4.35 in CKD 3a, HR 3.34, 95% CI 1.95-5.72 in CKD 3b, HR 7.87, 95% CI 3.51-17.61 in CKD stage 4&5. Conclusion: Metformin was not associated with an elevated risk of LA in persons with stage 1-2 CKD, but was associated with a progressively higher risk at more advanced stages of CKD.

Biomarkers of Toxicant Exposure and Inflammation Among Women of Reproductive Age Who Use Electronic or Conventional Cigarettes.

Background: Electronic cigarettes (e-cigarettes) generally have a more favorable toxicant profile than conventional cigarettes; however, limited information exists for women of reproductive age (WRA). Our aim was to compare biomarkers of toxicant exposure, inflammation, and oxidative stress among WRA who self-report exclusive e-cigarette use, exclusive cigarette smoking, or never tobacco use (controls). Methods: Multivariable linear regression models were used to compare the geometric means of urinary biomarkers of toxicant exposure and their metabolites, serum markers of inflammation [highly sensitive C-reactive protein, soluble intercellular adhesion molecule (sICAM), interleukin 6, fibrinogen], and a measurement of oxidative stress [prostaglandin F2a-8-isoprostane (F2PG2a)] among WRA from the Population Assessment of Tobacco and Health survey. Results: E-cigarette users had higher levels of lead, tobacco-specific nitrosamines, nicotine metabolites, and some volatile organic compounds (VOCs) than controls. Except for cadmium and lead, e-cigarette users had lower levels of the analyzed urinary toxicant biomarkers compared with cigarette smokers. Cigarette smokers had higher levels of all the biomarkers of toxicant exposure than controls. There were no significant differences in the levels of markers of inflammation and oxidative stress between e-cigarette users and controls. E-cigarette users and controls had lower levels of sICAM and F2PG2a than cigarette smokers. Conclusion: WRA who use e-cigarettes had lower levels of some of the evaluated urinary biomarkers of toxicant exposure and serum biomarkers of inflammation and oxidative stress than those who smoke cigarettes, but higher lead, nicotine metabolites, and some VOCs than controls, which can increase health risks.

Electronic Cigarettes Associated With Incident and Polysubstance Use Among Youth.

PURPOSE: Electronic cigarette (e-cigarette) use has increased exponentially among the youth in the United States and may increase the incidence of substance use. METHODS: Youth participants (12-17 years) were surveyed through the Population Assessment of Tobacco and Health study over a three-year time period. Youth with any baseline substance use or diagnosis of an attention deficit disorder were excluded from the analysis. Multivariable logistic regressions were used to assess the association between e-cigarette use at Wave 1 and incident substance use (marijuana, painkillers, sedatives, or tranquilizers and Ritalin/Adderall) and polysubstance use at Wave 2 or 3, and marijuana use in the electronic nicotine device at Wave 3. RESULTS: Baseline ever e-cigarette users who had no history of marijuana, nonprescribed drugs and illicit substance use in Wave 1 had increased odds of reporting incident use of marijuana (odds ratio 2.59, 95% confidence interval: 1.90-3.52), nonprescribed Ritalin/Adderall use (1.89, 1.09-3.28), or polysubstance use (2.09, 1.43-3.05) in Wave 2 or 3 compared to never e-cigarette users. They were also more likely to report use of marijuana in the electronic nicotine product (2.26, 1.56-3.27) in Wave 3 compared to never e-cigarette users. There was no statistically significant association between baseline e-cigarette use and incident use of painkillers, sedatives, or tranquilizers in Wave 2 or 3 (1.21, .79-1.87). CONCLUSIONS: E-cigarette use is associated with incident use of marijuana, marijuana in electronic nicotine devices, Ritalin/Adderall, and polysubstance use but not painkillers, sedatives, or tranquilizers. Results indicate that e-cigarettes are associated with subsequent additional risky health behaviors in youth.

The inflammatory biomarker YKL-40 is elevated in the serum, but not the sputum, of E-cigarette users.

METHODS: We conducted a cross-sectional study of adults between 18 and 55 years old. Inclusion criteria were: exclusive e-cigarette use or cigarette smoking for ≥ 1 year or no history of tobacco use. Participants with a history of pulmonary illness, atopy, medications (except birth control pills), marijuana, and illegal substance use were excluded. Custom Multiplex ELISA was used to measure YKL-40 and other biomarker levels in the serum and induced sputum of the participants. Multivariable linear regression was used to compare the levels of YLK-40 in healthy participants, e-cigarette, and cigarette users after adjusting for age, sex, and BMI. RESULTS: We recruited 20 healthy controls, 23 cigarette smokers, and 22 exclusive e-cigarette users. Serum YKL-40 (ng/ml) was significantly higher in e-cigarette users (Median 21.2 [IQR 12.1-24.0] ng/ml) when compared to controls (12.2 [IQR 8.7-18.1] ng/ml, p = 0.016) but comparable to cigarette smokers (21.6 [IQR 11.62-51.7] ng/ml, p = 0.31). No significant differences were found in the serum or sputum of the other biomarkers tested. CONCLUSION: The inflammatory biomarker, YKL-40 is elevated in the serum but not the sputum of e-cigarette users with no reported pulmonary disease. Further research is necessary to characterize this association.

Factors Associated with E-Cigarette Use in U.S. Young Adult Never Smokers of Conventional Cigarettes: A Machine Learning Approach.

E-cigarette use is increasing among young adult never smokers of conventional cigarettes, but the awareness of the factors associated with e-cigarette use in this population is limited. The goal of this work was to use machine learning (ML) algorithms to determine the factors associated with current e-cigarette use among US young adult never cigarette smokers. Young adult (18-34 years) never cigarette smokers from the 2016 and 2017 Behavioral Risk Factor Surveillance System (BRFSS) who reported current or never e-cigarette use were used for the analysis (n = 79,539). Variables associated with current e-cigarette use were selected by two ML algorithms (Boruta and Least absolute shrinkage and selection operator (LASSO)). Odds ratios were calculated to determine the association between e-cigarette use and the variables selected by the ML algorithms, after adjusting for age, gender and race/ethnicity and incorporating the BRFSS complex design. The prevalence of e-cigarette use varied across states. Factors previously reported in the literature, such as age, race/ethnicity, alcohol use, depression, as well as novel factors associated with e-cigarette use, such as disabilities, obesity, history of diabetes and history of arthritis were identified. These results can be used to generate further hypotheses for research, increase public awareness and help provide targeted e-cigarette education.

Comparison of patient-reported outcomes measurement information system and legacy instruments in multiple domains among older veterans with chronic back pain.

BACKGROUND: Chronic low back pain (cLBP) results in significant physical, psycho-social and socioeconomic burden. Identifying efficient and reliable patient reported outcome measures is critical for research and clinical purposes. The NIH's Patient Reported Outcomes Measurement Information System (PROMIS) instruments have not been compared to validated "legacy" instruments in older adults with cLBP. This study evaluates construct (convergent and discriminant) validity and time to complete (TTC) PROMIS as compared to legacy instruments. METHODS: We enrolled older Veterans (age 60+) with cLBP with/without leg pain scheduled for lumbar epidural steroid injections. Subjects completed PROMIS computer adaptive test item banks and corresponding legacy instruments in the following domains: pain intensity, interference, and behavior; functional status; depression and anxiety; fatigue; sleep and social functioning. Convergent and discriminant validity between PROMIS and legacy instruments was evaluated using Spearman rank order correlations; Mann-Whitney U tests compared TTC. RESULTS: Of the 71 Veterans recruited, the median (IQR) age was 67 (63-71) years old, 94% were men, 76% were White, 17% Black, and 96% were Non-Hispanic. Spearman correlations between PROMIS and legacy instruments showed moderate to very strong convergent validity in all domains (r = 0.4-1.0), except for social functioning and pain behavior (PROMIS Pain Behavior with Fear Avoidance Belief Questionnaire). The total median TTC for all PROMIS items was significantly shorter than legacy items, 8 min 50 s vs 29 min 14 s respectively, p < 0.001. CONCLUSIONS: Given time efficiency of using PROMIS, along with strong construct validity, PROMIS instruments are a practical choice for measuring multidimensional PROs in older Veterans with cLBP for both research and clinical purposes.

Statins in survivors of traumatic brain injury: a propensity score-matched analysis.

BACKGROUND: Several in-vitro and animal studies suggest that statins may have beneficial effects on clinical outcomes of traumatic brain injury (TBI), however, clinical data are scarce. OBJECTIVES: To examine the association of statin use with TBI clinical outcomes among patients with TBI. METHODS: A retrospective cohort study of Tricare beneficiaries who had a TBI diagnosis, as defined by the Barbell injury diagnosis matrix. Outcomes were defined using ICD-9 codes and included: post-concussion syndrome, neurological disorders, substance dependence or abuse, and psychiatric disorders. Statin-users and non-users were propensity score (PS)-matched using 103 baseline characteristics. RESULTS: Out of 1187 adult patients with a TBI diagnosis (172 statin-users and 1015 nonusers), we PS-matched 70 statin-users to 70 non-users. There were no statistically significant differences in the PS-matched cohort of statin-users in comparison to nonusers for post-concussion syndrome (odds ratio [OR]: 0.24, 95% confidence interval [CI]: 0.03-2.20), neurological disorders (OR: 0.60, CI: 0.31-1.16); substance dependence or abuse (OR: 0.80, CI: 0.40-1.60), or psychiatric disorders (OR 0.80, CI: 0.41-1.55). CONCLUSION: This study did not show benefit or harm for statins among survivors of TBI. Our findings do not support the evidence from some animal studies and small randomized controlled trials. Further studies utilizing larger sample sizes are warranted.

E-cigarette use is associated with a self-reported diagnosis of prediabetes in never cigarette smokers: Results from the behavioral risk factor surveillance system survey.

BACKGROUND: The use of e-cigarettes is increasing in the US but there is still a paucity of research on the metabolic effects of e-cigarette use. The goal of this work was to determine the association between e-cigarette use and self-reported prediabetes in adult never cigarette smokers. METHOD: The 2017 cross sectional Behavioral Risk Factor Surveillance System (BRFSS) survey data was used for the analysis. Current e-cigarette users reported daily or someday use of e-cigarettes and former e-cigarette users reported no current use of e-cigarettes. Participants who reported a history of diabetes, gestational prediabetes/ diabetes were excluded. Odds ratios were calculated to determine the association between e-cigarette use and self-reported prediabetes in never cigarette smokers after adjusting for potential confounders. RESULTS: There were a total of 154,404 participants that met the inclusion criteria. Of those participants, there were 143,952 never, 1339 current and 7625 former e-cigarette users. Current e-cigarette users had an increased odds of reporting a diagnosis of prediabetes 1.97 (95% CI 1.25-3.10) compared to never e-cigarette users. After stratifying by gender, men and women had an increased odds ratio of reporting a diagnosis of prediabetes 2.36 (95% CI 1.26-4.40) and 1.88 (95% CI 1.00-3.53) respectively when compared to never e-cigarette users. There was no association between former e-cigarette use and a self-reported diagnosis of prediabetes. CONCLUSION: Our findings show that e-cigarette use may be associated with self-reported prediabetes. Further evaluation is needed in prospective studies.

Association of atypical antipsychotics and mortality for patients hospitalised with pneumonia.

INTRODUCTION: Atypical antipsychotics are commonly used in patients with psychiatric conditions and dementia. They are also frequently used in patients being admitted with pneumonia; however, there are few safety data. The purpose of this study was to examine whether atypical antipsychotic use prior to admission is associated with increased mortality in patients with pneumonia. METHODS: We conducted a retrospective cohort study of hospitalised patients with pneumonia over a 10-year period. We included patients 65 years or older and hospitalised with pneumonia. For our primary analysis, we used propensity score matching to balance confounders between atypical antipsychotic users and nonusers. RESULTS: There were 102 897 patients and 5977 were taking atypical antipsychotics. After matching there were 5513 users and 5513 nonusers. Atypical antipsychotic use was associated with increased odds of 30-day (OR 1.20, 95% CI 1.11-1.31) and 90-day mortality (1.19, 1.09-1.30). CONCLUSION: In patients 65 years or older that are hospitalised with pneumonia, we found an association between atypical antipsychotic use and increased odds of mortality. This was particularly pronounced for patients with pre-existing psychiatric or cardiac conditions. We suggest closely monitoring patients who use these medications and minimising their use in older adult patients.

Adult E-Cigarettes Use Associated with a Self-Reported Diagnosis of COPD.

The use of electronic cigarettes (e-cigarettes) has increased in the US, but little is known about the effects of these products on lung health. The main purpose of this study was to examine the association between e-cigarette use and a participant's report of being diagnosed with chronic obstructive pulmonary disease (COPD) in a nationally representative sample of adults. Methods: The first wave of the Population Assessment of Tobacco and Health (PATH) survey adult data was used (N = 32,320). Potential confounders between e-cigarette users and non-users were balanced using propensity score matching. Odds ratios (OR) were calculated to examine the association between e-cigarette use and COPD in the propensity-matched sample, the entire sample, different age groups, and in nonsmokers. Replicate weights and balanced repeated replication methods were utilized to account for the complex survey design. Results: Of the 3642 participants who met the criteria for e-cigarette use, 2727 were propensity matched with 2727 non e-cigarette users. In the propensity-matched sample, e-cigarette users were more likely to report being diagnosed with COPD (OR 1.43, 95% confidence interval [CI] 1.12-1.85) than non-e-cigarette users after adjusting for confounders. The result was similar in the entire sample and in the different age subgroups. Among nonsmokers, the odds of reporting a COPD diagnosis were even greater among e-cigarette users (OR 2.94, 95% CI 1.73-4.99) compared to non-e-cigarette users. Conclusion: Our findings demonstrate that e-cigarette use was associated with a reported diagnosis of COPD among adults in the US. Further research is necessary to characterize the nature of this association and on the long-term effects of using e-cigarettes.