Radiation-induced lung injury (RILI) is a consequence of therapeutic thoracic irradiation (TR) for many cancers, and there are no FDA-approved curative strategies. Studies report that 80% of patients who undergo TR will have CT-detectable interstitial lung abnormalities, and strategies to limit the risk of RILI may make radiotherapy less effective at treating cancer. Our lab and others have reported that lung tissue from patients with idiopathic pulmonary fibrosis (IPF) exhibits metabolic defects including increased glycolysis and lactate production. In this pilot study, we hypothesized that patients with radiation-induced lung damage will exhibit distinct changes in lung metabolism that may be associated with the incidence of fibrosis. Using liquid chromatogra-phy/tandem mass spectrometry to identify metabolic compounds, we analyzed exhaled breath condensate (EBC) in subjects with CT-confirmed lung lesions after TR for lung cancer, compared with healthy subjects, smokers, and cancer patients who had not yet received TR. The lung metabolomic profile of the irradiated group was significantly different from the three nonirradiated control groups, highlighted by increased levels of lactate. Pathway enrichment analysis revealed that EBC from the case patients exhibited concurrent alterations in lipid, amino acid, and carbohydrate energy metabolism associated with the energy-producing tricarboxylic acid (TCA) cycle. Radiation-induced glycolysis and diversion of lactate to the extracellular space suggests that pyru-vate, a precursor metabolite, converts to lactate rather than acetyl-CoA, which contributes to the TCA cycle. This TCA cycle defi-ciency may be compensated by these alternate energy sources to meet the metabolic demands of chronic wound repair. Using an "omics" approach to probe lung disease in a noninvasive manner could inform future mechanistic investigations and the de-velopment of novel therapeutic targets.NEW & NOTEWORTHY We report that exhaled breath condensate (EBC) identifies cellular metabolic dysregulation in patients with radiation-induced lung injury. In this pilot study, untargeted metabolomics revealed a striking metabolic signature in EBC from patients with radiation-induced lung fibrosis compared to patients with lung cancer, at-risk smokers, and healthy volunteers. Patients with radiation-induced fibrosis exhibit specific changes in tricarboxylic acid (TCA) cycle energy metabolism that may be required to support the increased energy demands of fibroproliferation.

Introduction: SARS-COv-2, the novel coronavirus responsible for COVID19 causes a wide range of pathology. While some patients may experience mild or asymptomatic infection, others will progress to respiratory failure and death. Although some clinical parameters have been shown to predict patient outcomes, the role of cytokine measurements is controversial. The aim of the study was to determine whether admission cytokine levels can predict the clinical course of patients with COVID19. Methods: Blood was collected at admission from 41 patients with COVID19 at Virginia Commonwealth University from April-July 2020. A panel of 27 pro-inflammatory cytokines was measured in serum by multiplex assay. 20 patients were selected for analysis;10 with moderate disease (hospital admission, <4L O2 need) and 10 severe COVID patients (ICU admission);patients with active malignancy were excluded. Multivariate principal component and correlation analysis (PCA) was performed. Patient severity (ICU admission, max O2 requirement, duration of hospital stay), patient demographics (gender, race, BMI), and serum cytokine levels were analyzed. Results: The only significant correlation with disease severity was duration of stay with TNF-α (0.5772,p=0.0097, Fig. 1A). IL-6 was not correlated with severity. PCA clustered severe patients together, with more variability being observed in the moderate cases (Fig.1B). Disease severity parameters cluster together with limited association with the cytokine and demographics parameters (Fig.1C). PCA identified 2 main clusters of cytokines, but neither was associated with severity. TNF-α and IL-8 were separate from the other cytokines (Fig.1C). Discussion: In this small series of COVID19 patients from an urban academic medical center, PCA revealed correlation between admission TNF-α levels and the development of severe COVID19. No correlation was noted between admission IL-6 levels and disease severity. An association between TNF-α and outcomes has recently been described in a large cohort from the United States, but we were not able to determine other predictors of outcomes despite an extensive cytokine panel. The discrepancy with prior studies may be attributed to the high percentage of African-American subjects and high rates of comorbidities in our cohort. Our findings show low levels of key cytokines when compared to previous studies in non-COVID ARDS suggesting a difference in the pathophysiology of severe COVID19. The lack of IL-6 association with severe COVID19 is consistent with recent negative trials of IL-6 blockade in COVID19. Larger studies are needed to explore the role of TNF-α in the development of severe COVID19 and its potential as a therapeutic target.

BACKGROUND: Many conditions have been associated with severe COVID-19 disease. To date, the risk associated with pre-existing hypothyroidism remains unclear. Hypothyroidism affects the innate immune system. Patients with hypothyroidism have higher circulating inflammatory markers, which are associated with increased mortality in COVID-19. A prior study did not find a significant difference in the risk of hospitalization or death in patients with pre-existing hypothyroidism. This study aims to investigate a possible association between pre-existing hypothyroidism and death from COVID-19. METHODS: We performed a retrospective cohort study of adult inpatients diagnosed with SARS-CoV-2 infection in a tertiary, academic referral center in Richmond, Virginia. We analyzed the unadjusted and adjusted association of patients with a past medical history of hypothyroidism and all-cause hospital mortality. We performed adjusted logistic regressions adjusting for age, gender, race, the month at presentation (an adaptation of the health system), and the remaining 30 individual diagnostic categories of the Elixhauser comorbidity index. RESULTS: Fifty-three (8.2%) of the 649 COVID-19 inpatients had hypothyroidism. Patients with hypothyroidism were, on average, 15.3 years older (95% CI 10.3 to 20.4 years). The unadjusted mortality of patients with hypothyroidism was 22.6% compared with 7.4% in patients without hypothyroidism. The unadjusted mortality OR was 3.5 (95% CI 1.7 to 7.2, P=0.001). The adjusted OR for death was 3.6 (95% CI 1.4 to 9.3, P=0.007, abstract figure). The average adjusted mortality was 18.6% for patients with hypothyroidism compared with 7.8% in patients with equivalent age, gender, race, remaining comorbidities, and month of presentation. CONCLUSION: Our results suggest that pre-existing hypothyroidism is associated with a three-fold risk of death in patients hospitalized with COVID-19. There are conflicting reports in the literature on the association between hypothyroidism and severe COVID-19. Earlier descriptive studies did not report rates of thyroid disease in their cohorts. Further research is needed on the pathophysiology and effects of SARS-CoV-2 infection in hypothyroid individuals.

RATIONALE: Studies have demonstrated racial disparities in COVID-19 outcomes, with black Americans having higher rates of infection, hospitalization, and death. Similarly, CDC data has shown higher Influenza-related mortality in the black American population. While COVID-19 is a deadlier viral respiratory illness, a comparison between influenza and COVID-19 can provide insight into racial disparities and clarify if there is excess disease burden of COVID-19 on black American communities compared with another viral pneumonia. METHODS: We performed a four-year retrospective cohort study (2016-2020) of adult inpatients tested with SARS-CoV-2 or Influenza (A or B) infection in a tertiary, academic referral center in Richmond, Virginia. We compared the unadjusted and adjusted positivity rate, and mortality between black and non-black patients. We performed multiple logistic regression to adjust for age and gender and applied the models to estimate and compare the predicted adjusted mortality. RESULTS: The proportion of black patients admitted for Influenza from 2016-2020 was significantly greater than the proportion of black patients admitted with COVID-19, 66.6% vs. 57.5% (p <0.01). The unadjusted mortality for Influenza + patients was 1.6% (31). The unadjusted mortality for SARSCoV- 2 + patients were 5.6% (125). Black patients had lower unadjusted OR for death for influenza (0.6 95% CI 0.6-0.64, p<0.001) and OR of death for SARS-CoV-2 (0.84, 95% 0.73-0.96, p=0.01). The findings persisted after adjusting for age and gender in influenza patients (OR 0.68 95% CI 0.64-0.74, p<0.001) but not in SARSCoV- 2 patients (OR 0.91 95% CI 0.8-1.05, p=0.2). CONCLUSION: In our predominantly black American cohort, we found no significant association between race and in-hospital adjusted mortality related to COVID-19. Our findings are contrary to larger cohorts and CDC data which shows increased mortality in the black American population. The higher proportion of black patients with Influenza than COVID-19 also indicates that in our population there is not an excess burden from COVID-19 compared to previous Influenza data, although for both COVID-19 and Influenza black patients are overrepresented compared to demographics of VCU's catchment area. The reason for these findings is not clear. Our cohort was composed predominantly of black Americans as is Richmond, VA. It is possible that in this setting the provision of community health or outreach regarding COVID-19 disease prevention to black communities was more effective, reducing excess COVID-19 disease burden. Further research to identify how structural racism and social determinants of health affect vulnerable communities and factors that mitigate these effects is necessary.

RATIONALE: The Center for Disease Control has reported that racial and ethnic groups are more susceptible to COVID-19 with worse outcomes. Inequalities in social determinants of health, particularly income, access to healthcare, and housing, may play a role in these differences. Health insurance has been shown to affect health outcomes for acute and chronic conditions. Uninsured and Medicaid recipients face worse outcomes for conditions like pneumonia, myocardial infarction, and lung cancer. Health insurance has also been described as a surrogate marker for social determinants of health. We set out to investigate these parameters in COVID-19 hospitalized patients in central Virginia. METHODS: We performed a retrospective cohort study of adult inpatients diagnosed with SARS-CoV-2 infection in a tertiary, academic referral center in central Virginia. We analyzed unadjusted and adjusted patient demographics like age, gender, race, ethnicity, insurance primary payer, and Elixhauser comorbidities with hospital all-cause mortality. We calculated adjusted and unadjusted mortality rates, odds ratios, and confidence intervals. We constructed a geospatial analysis of the adjusted mortality by zip code. RESULTS: Black patients constituted 56.1% of the cohort (276 patients out of 492). Hispanic patients 17.7%. Average age was 55.7 (SD 17) years. Majority of patients had Medicare (35.8%), followed by Medicaid (19.3%), no insurance specified or uninsured 15.7%, private insurance 14.8%, state/ prison insurance 11.8% and military insurance 2.6%. When adjusted for comorbidities, age, gender, race and ethnicity was not associated with mortality. Private insurance and unspecified insurance status were associated with both unadjusted lower mortality OR 0.09 (95% CI 0.014 - 0.63, p=0.01) and 0.04 (95% CI 0.004 - 0.63, p=0.01) and adjusted OR 0.07 (95% CI 0.01- 0.90, p =0.04) and 0.04 (95% CI 0.002 - 0.73, p=0.03) respectively. These findings persisted after removing the prison population (p=0.02). CONCLUSION: Despite nationwide trends indicating worse outcomes for specific racial groups affected by COVID-19, in our diverse cohort race was not associated with a significant difference in mortality. Private insurance was associated with lower mortality versus public insurance. This finding persisted when adjusting for confounders and removing the prison population.In central Virginia, health insurance status is a predictor of COVID-19 outcomes and may serve as a surrogate for health disparities. Uninsured/public insured individuals may have lower socioeconomic status or reside in medically underserved areas, limiting access to care. Further investigation is needed to elucidate the largest risk factors and design interventions to curtail the impact of COVID19 on this population.

BACKGROUND: Over 790,000 patients in the United States are currently living with or are in remission from lymphoma. It is established that lymphoma patients are at greater risk for both bacterial and viral infections. While there is limited research examining the risk of COVID-19 infection in patients with an active malignancy, even fewer studies have examined those with active lymphoma. This study aimed to examine the all-cause mortality of COVID-19 patients with active lymphoma compared to hospitalized COVID-19 control patients. METHODS: We performed a retrospective case-control and cohort study of adult inpatients diagnosed with COVID-19 infection in a tertiary, academic referral center in Richmond, Virginia. We analyzed the unadjusted and adjusted association of patients with active lymphoma diagnosis and all-cause hospital mortality. We performed multiple logistic regressions adjusting for age, gender, race, the month at presentation, which captures the health system's adaptation, and the remaining 30 individual diagnostic categories of the Elixhauser comorbidity index. We externally validated our findings using compiled data from 657 institutions across the United States on patients with lymphoma hospitalized for COVID-19. RESULTS: Among 628 inpatients with COVID-19, 1.1% (7) had active lymphoma. The unadjusted mortality of patients with lymphoma was 57.1% compared to 8.4% of the corresponding patients without lymphoma. The unadjusted OR for hospital death was 15.6 (95% CI 3.2 to 67, P=0.001). The adjusted OR of death in patients with lymphoma was 79.5 (95% 6.4 to 983, P= 0.001). The average adjusted mortality in patients with lymphoma was 65% compared with 8.4% among patients of equivalent age, gender, race, month of presentation and comorbidities. From aggregate data of COVID-19 patients across 657 US institutions, the average mortality for patients with lymphoma was 41.07% (95% CI 36.8 to 45.3) and for patients without lymphoma was 12.11% (95% CI 12.7 to 11.5). CONCLUSION: Our results show that, of those patients hospitalized for COVID-19 infection, the patients with active lymphoma have a nearly 8-fold increased risk of death compared to their non-lymphoma counterparts when adjusted for age, gender, race, month of presentation, and other comorbidities. External validation data demonstrated a greater than 3-fold increased risk of death in COVID-19 patients with active lymphoma compared to non-lymphoma patients. This research highlights the importance of mitigation strategies, such as social distancing and masking, to decrease the risk of COVID-19 infection in lymphoma patients and may have implications for prioritizing vaccines or therapies in the future. FIGURE:.

A patient developed symptomatic exercise-induced hypoxemia during pregnancy as a result of pulmonary arteriovenous microfistulas. Her symptoms resolved after pregnancy with spontaneous closure of the fistulas. Hormone-induced vasodilation is the probable mechanism.