Impact of Vaccination, Prior Infection and Therapy on Omicron Infection and Mortality.

BACKGROUND: Understanding the immunity against omicron infection and severe outcomes conferred by Covid-19 vaccination, prior SARS-CoV-2 infection, and monoclonal antibody therapy will inform intervention strategies. METHODS: We considered 295,691 patients who were tested for SARS-CoV-2 at Cleveland Clinic between October 1, 2021 and January 31, 2022. We used logistic regression to investigate the association of vaccination and prior infection with the risk of SARS-CoV-2 infection and used Cox regression to investigate the association of vaccination, prior infection and monoclonal antibody therapy with the risks of intensive care unit (ICU) stay and death. RESULTS: Vaccination and prior infection were less effective against omicron than delta infection but provided strong protection against ICU admission and death. Boosting greatly increased vaccine effectiveness against omicron infection and severe outcomes, though the effectiveness waned rapidly over time. Monoclonal antibody therapy considerably reduced the risks of ICU admission and death. Finally, the relatively low mortality of the omicron variant was due to both the reduced lethality of this variant and the increased population immunity acquired from booster vaccination and previous infection. CONCLUSIONS: Booster vaccination and prior SARS-CoV-2 infection provide strong protection against ICU admission and death from omicron infection. Monoclonal antibody therapy is also beneficial.

Acute skeletal muscle loss in SARS-CoV-2 infection contributes to poor clinical outcomes in COVID-19 patients.

BACKGROUND: Chronic disease causes skeletal muscle loss that contributes to morbidity and mortality. There are limited data on the impact of dynamic muscle loss on clinical outcomes in COVID-19. We hypothesized that acute COVID-19-related muscle loss (acute sarcopenia) is associated with adverse outcomes. METHODS: A retrospective analysis of a prospective clinical registry of COVID-19 patients was performed in consecutive hospitalized patients with acute COVID-19 (n = 95) and compared with non-COVID-19 controls (n = 19) with two temporally unique CT scans. Pectoralis muscle (PM), erector spinae muscle (ESM) and 30 day standardized per cent change in cross sectional muscle area were quantified. Primary outcomes included mortality and need for intensive care unit (ICU) admission. Multivariate linear and logistic regression were performed. Cox proportional hazard ratios were generated for ICU admission or mortality for the per cent muscle loss standardized to 30 days. RESULTS: The COVID-19 CT scan cohort (n = 95) had an average age of 63.3 ± 14.3 years, comorbidities including COPD (28.4%) and diabetes mellitus (42.1%), and was predominantly Caucasian (64.9%). The proportion of those admitted to the ICU was 54.7%, with 10.5% requiring tracheostomy and overall mortality 16.8%. Median duration between CT scans was 32 days (IQR: 16-63 days). Significant reductions in median per cent loss was noted for PM (-2.64% loss [IQR: -0.28, -5.47] in COVID-19 vs. -0.06 loss [IQR: -0.01, -0.28] in non-COVID-19 CT controls, P < 0.001) and ESM (-1.86% loss [IQR: -0.28, -5.47] in COVID-19 vs. -0.06 loss [IQR: -0.02, -0.11]) in non-COVID-19 CT controls, P < 0.001). Multivariate linear regression analysis of per cent loss in PM was significantly associated with mortality (-10.8% loss [95% CI: -21.5 to -0.19]) and ICU admission (-11.1% loss [95% CI: -19.4 to -2.67]), and not significant for ESM. Cox proportional hazard ratios demonstrated greater association with ICU admission (adj HR 2.01 [95% CI: 1.14-3.55]) and mortality (adj HR 5.30 [95% CI: 1.19-23.6]) for those with significant per cent loss in PM, and greater association with ICU admission (adj HR 8.22 [95% CI: 1.11-61.04]) but not mortality (adj HR 2.20 [95% CI: 0.70-6.97]) for those with significant per cent loss in ESM. CONCLUSIONS: In a well-characterized cohort of 95 hospitalized patients with acute COVID-19 and two temporally distinct CT scans, acute sarcopenia, determined by standardized reductions in PM and ESM, was associated with worse clinical outcomes. These data lay the foundation for evaluating dynamic muscle loss as a predictor of clinical outcomes and targeting acute sarcopenia to improve clinical outcomes for COVID-19.

Eosinophilia Is Associated with Improved COVID-19 Outcomes in Inhaled Corticosteroid-Treated Patients.

BACKGROUND: In addition to their proinflammatory effect, eosinophils have antiviral properties. Similarly, inhaled corticosteroids (ICS) were found to suppress coronavirus replication in vitro and were associated with improved outcomes in coronavirus disease 2019 (COVID-19). However, the interplay between the two and its effect on COVID-19 needs further evaluation. OBJECTIVE: To determine the associations among preexisting blood absolute eosinophil counts, ICS, and COVID-19-related outcomes. METHODS: We analyzed data from the Cleveland Clinic COVID-19 Research Registry (April 1, 2020 to March 31, 2021). Of the 82,096 individuals who tested positive, 46,397 had blood differential cell counts obtained before severe acute respiratory syndrome coronavirus 2 testing dates. Our end points included the need for hospitalization, admission to the intensive care unit (ICU), and in-hospital mortality. The effect of eosinophilia on outcomes was estimated after propensity weighting and adjustment. RESULTS: Of the 46,397 patients included in the final analyses, 19,506 had preexisting eosinophilia (>0.15 × 103 cells/µL), 5,011 received ICS, 9,096 (19.6%) were hospitalized, 2,129 required ICU admission (4.6%) and 1,402 died during index hospitalization (3.0%). Adjusted analysis associated eosinophilia with lower odds for hospitalization (odds ratio [OR] [95% confidence interval (CI)]: 0.86 [0.79-0.93]), ICU admission (OR [95% CI]: 0.79 [0.69-0.90]), and mortality (OR [95% CI]: 0.80 [0.68-0.95]) among ICS-treated patients but not untreated ones. The correlation between absolute eosinophil count and the estimated probability of hospitalization, ICU admission, and death was nonlinear (U-shaped) among patients not treated with ICS, and negative in treated patients. CONCLUSIONS: The association between eosinophilia and improved COVID-19 outcomes depends on ICS. Future randomized controlled trials are needed to determine the role of ICS and its interaction with eosinophilia in COVID-19 therapy.

Intranasal Corticosteroids Are Associated with Better Outcomes in Coronavirus Disease 2019.

BACKGROUND: Sites of entry for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are highly expressed in nasal epithelial cells; however, little is known about the impact of intranasal corticosteroids (INCS) on coronavirus disease 2019 (COVID-19)-related outcomes. OBJECTIVE: To determine the association between baseline INCS use and COVID-19-related outcomes. METHODS: Using the Cleveland Clinic COVID-19 Research Registry, we performed a propensity score matching for treatment with INCS before SARS-CoV-2 infection (April 1, 2020, to March 31, 2021). Of the 82,096 individuals who tested positive, 72,147 met inclusion criteria. Our endpoints included the need for hospitalization, admission to the intensive care unit (ICU), or in-hospital mortality. RESULTS: Of the 12,608 (17.5%) who were hospitalized, 2935 (4.1%) required ICU admission and 1880 (2.6%) died during hospitalization. A significant proportion (n = 10,187; 14.1%) were using INCS before SARS-CoV-2 infection. Compared with nonusers, INCS users demonstrated lower risk for hospitalization (adjusted odds ratio [OR] [95% confidence interval (CI)]: 0.78 [0.72; 0.85]), ICU admission (adjusted OR [95% CI]: 0.77 [0.65; 0.92]), and in-hospital mortality (adjusted OR [95% CI]: 0.76 [0.61; 0.94]). These findings were replicated in sensitivity analyses where patients on inhaled corticosteroids and those with allergic rhinitis were excluded. The beneficial effect of INCS was significant after adjustment for baseline blood eosinophil count (measured before SARS-CoV-2 testing) in a subset of 30,289 individuals. CONCLUSION: INCS therapy is associated with a lower risk for COVID-19-related hospitalization, ICU admission, or death. Future randomized control trials are needed to determine if INCS reduces the risk for severe outcomes related to COVID-19.

Right Ventricle Dilation Detected on Point-of-Care Ultrasound Is a Predictor of Poor Outcomes in Critically Ill Patients With COVID-19.

BACKGROUND: During the COVID-19 pandemic, the need for judicious use of diagnostic tests and to limit personnel exposure has led to increased use and dependence on point-of-care ultrasound (POCUS) examinations. We reviewed POCUS findings in patients admitted to the intensive care unit (ICU) for acute respiratory failure with COVID-19 and correlated the findings to severity of illness and 30-day outcomes. METHODS: Patients admitted to the ICU in March and April 2020 were reviewed for inclusion (acute hypoxemic respiratory failure secondary to COVID-19 pneumonia; documentation of POCUS findings). RESULTS: Forty-three patients met inclusion criteria. B lines and pleural thickening were associated with a lower PaO2/FiO2 by 71 (P = .005; adjusted R 2 = 0.24). Right ventricle (RV) dilation was more common in patients with 30-day mortality (P = .02) and was a predictor of mortality when adjusted for hypertension, diabetes mellitus, and age (odds ratio, 12.0; P = .048). All patients with RV dilation had bilateral B lines with pleural irregularities. CONCLUSIONS: Although lung ultrasound abnormalities are prevalent in patients with severe disease, RV involvement seems to be predictive of outcomes. Further studies are needed to discern the etiology and pathophysiology of RV dilation in COVID-19.

Inhaled corticosteroids do not adversely impact outcomes in COVID-19 positive patients with COPD: An analysis of Cleveland Clinic's COVID-19 registry.

Inhaled Corticosteroids (ICS) are commonly prescribed to patients with severe COPD and recurrent exacerbations. It is not known what impact ICS cause in terms of COVID-19 positivity or disease severity in COPD. This study examined 27,810 patients with COPD from the Cleveland Clinic COVID-19 registry between March 8th and September 16th, 2020. Electronic health records were used to determine diagnosis of COPD, ICS use, and clinical outcomes. Multivariate logistic regression was used to adjust for demographics, month of COVID-19 testing, and comorbidities known to be associated with increased risk for severe COVID-19 disease. Amongst the COPD patients who were tested for COVID-19, 44.1% of those taking an ICS-containing inhaler tested positive for COVID-19 versus 47.2% who tested negative for COVID-19 (p = 0.033). Of those who tested positive for COVID-19 (n = 1288), 371 (28.8%) required hospitalization. In-hospital outcomes were not significantly different when comparing ICS versus no ICS in terms of ICU admission (36.8% [74/201] vs 31.2% [53/170], p = 0.30), endotracheal intubation (21.9% [44/201] vs 16.5% [28/170], p = 0.24), or mortality (18.4% [37/201] vs 20.0% [34/170], p = 0.80). Multivariate logistic regression demonstrated no significant differences in hospitalization (adj OR 1.12, CI: 0.90-1.38), ICU admission (adj OR: 1.31, CI: 0.82-2.10), need for mechanical ventilation (adj OR 1.65, CI: 0.69-4.02), or mortality (OR: 0.80, CI: 0.43-1.49). In conclusion, ICS therapy did not increase COVID-19 related healthcare utilization or mortality outcome in patients with COPD followed at the Cleveland Clinic health system. These findings should encourage clinicians to continue ICS therapy for COPD patients during the COVID-19 pandemic.

Genetic and non-genetic factors affecting the expression of COVID-19-relevant genes in the large airway epithelium.

BACKGROUND: The large airway epithelial barrier provides one of the first lines of defense against respiratory viruses, including SARS-CoV-2 that causes COVID-19. Substantial inter-individual variability in individual disease courses is hypothesized to be partially mediated by the differential regulation of the genes that interact with the SARS-CoV-2 virus or are involved in the subsequent host response. Here, we comprehensively investigated non-genetic and genetic factors influencing COVID-19-relevant bronchial epithelial gene expression. METHODS: We analyzed RNA-sequencing data from bronchial epithelial brushings obtained from uninfected individuals. We related ACE2 gene expression to host and environmental factors in the SPIROMICS cohort of smokers with and without chronic obstructive pulmonary disease (COPD) and replicated these associations in two asthma cohorts, SARP and MAST. To identify airway biology beyond ACE2 binding that may contribute to increased susceptibility, we used gene set enrichment analyses to determine if gene expression changes indicative of a suppressed airway immune response observed early in SARS-CoV-2 infection are also observed in association with host factors. To identify host genetic variants affecting COVID-19 susceptibility in SPIROMICS, we performed expression quantitative trait (eQTL) mapping and investigated the phenotypic associations of the eQTL variants. RESULTS: We found that ACE2 expression was higher in relation to active smoking, obesity, and hypertension that are known risk factors of COVID-19 severity, while an association with interferon-related inflammation was driven by the truncated, non-binding ACE2 isoform. We discovered that expression patterns of a suppressed airway immune response to early SARS-CoV-2 infection, compared to other viruses, are similar to patterns associated with obesity, hypertension, and cardiovascular disease, which may thus contribute to a COVID-19-susceptible airway environment. eQTL mapping identified regulatory variants for genes implicated in COVID-19, some of which had pheWAS evidence for their potential role in respiratory infections. CONCLUSIONS: These data provide evidence that clinically relevant variation in the expression of COVID-19-related genes is associated with host factors, environmental exposures, and likely host genetic variation.

Safety of influenza vaccine during COVID-19

The propensity score for each individual is the predicted probability of receiving influenza vaccination from a nonparsimonious logistic regression model using the covariates listed as clinical characteristics in Table 1. Clinical characteristics and outcome of all individuals in the cohort and in the subgroup of patients tested positive for SARS-CoV-2 All tested individuals SARS-CoV-2-positive Never vaccinated Vaccinated in 2019 p Never vaccinated Vaccinated in 2019 p Clinical characteristics (n = 9082) (n = 4138) (n = 1125) (n = 309) Age – year 49.3 [34.6, 62.9] 61.5 [46.9, 72.0] <0.001 52.7 [38.6, 64.1] 63.3 [49.2, 73.4] <0.001 Race – no (%) <0.001 <0.001 White 5985 (65.9) 3050 (73.7) 686 (61.0) 203 (65.7) Black 1695 (18.7) 833 (20.1) 246 (21.9) 91 (29.4) Other 1402 (15.4) 255 (6.2) 193 (17.2) 15 (4.9) Male sex – no (%) 4050 (44.6) 1651 (39.9) <0.001 593 (52.7) 152 (49.2) 0.30 Non-Hispanic ethnicity – no (%) 7986 (87.9) 3974 (96.0) <0.001 893 (79.4) 298 (96.4) <0.001 BMI – kg/m2 28.6 [24.4, 33.6] 29.0 [24.8, 34.9] 0.002 29.7 [26.1, 34.0] 30.0 [25.0, 35.5] 0.66 Smoking – no (%) <0.001 <0.001 Current smoker 1481 (16.3) 504 (12.2) 64 (5.7) 15 (4.9) Former smoker 1625 (17.9) 1684 (40.7) 178 (15.8) 123 (39.8) Nonsmoker 5976 (65.8) 1950 (47.1) 883 (78.5) 171 (55.3) Median annual income – USD 57,250.0 [42,500.9–74,812.2] 59,390.0 [41,635.0–79,201.0] 0.005 58,429.0 [45,161.0–76,719.0] 60,000.0 [43,097.0–81,953.0] 0.91 Exposure to COVID-19 – no (%) 4805 (52.9) 1923 (46.5) <0.001 825 (73.3) 203 (65.7) 0.01 Family history of COVID-19 – no (%) 4452 (49.0) 1849 (44.7) <0.001 795 (70.7) 205 (66.3) 0.16 Coexisting conditions – no (%) COPD 517 (5.7) 689 (16.7) <0.001 39 (3.5) 40 (12.9) <0.001 Asthma 1433 (15.8) 1195 (28.9) <0.001 121 (10.8) 66 (21.4) <0.001 Diabetes 1288 (14.2) 1493 (36.1) <0.001 177 (15.7) 111 (35.9) <0.001 Hypertension 2885 (31.8) 2677 (64.7) <0.001 387 (34.4) 205 (66.3) <0.001 Coronary artery disease 673 (7.4) 998 (24.1) <0.001 71 (6.3) 57 (18.4) <0.001 Congestive heart failure 551 (6.1) 880 (21.3) <0.001 49 (4.4) 61 (19.7) <0.001 Cancer 848 (9.3) 1149 (27.8) <0.001 72 (6.4) 71 (23.0) <0.001 Connective tissue disease 795 (8.8) 1003 (24.2) <0.001 69 (6.1) 46 (14.9) <0.001 Long-term medications – no (%) NSAIDs 1659 (18.3) 1459 (35.3) <0.001 189 (16.8) 108 (35.0) <0.001 Glucocorticoids 1066 (11.7) 1350 (32.6) <0.001 67 (6.0) 66 (21.4) <0.001 ACE inhibitors 512 (5.6) 565 (13.7) <0.001 74 (6.6) 52 (16.8) <0.001 ARB 374 (4.1) 439 (10.6) <0.001 70 (6.2) 41 (13.3) <0.001 Laboratory measurements Platelet count – (x 109/L) 239.0 [188.0, 298.0] 233.0 [176.0, 301.0] 0.005 198.0 [160.0, 250.0] 196.0 [157.0, 251.5] 0.66 Eosinophil count – (cells/μL) 70.0 [30.0, 170.0] 80.0 [30.0, 190.0] 0.001 30.0 [30.0, 30.0] 30.0 [30.0, 30.0] 0.55 Lymphocyte count – (109/μL) 1.4 [0.9, 2.1] 1.2 [0.8, 1.9] <0.001 1.1 [0.7, 1.5] 0.9 [0.6, 1.3] 0.011 Neutrophil count – (109/μL) 5.6 [3.7, 8.7] 5.9 [3.9, 8.9] 0.086 3.9 [2.9, 5.5] 4.1 [2.8, 6.5] 0.33 Hemoglobin – (g/dL) 13.2 [11.5, 14.6] 12.2 [10.0, 13.9] <0.001 13.6 [12.1, 14.9] 13.30 [11.7, 14.6] 0.07 Albumin – (g/dL) 4.00 [3.50, 4.35] 3.80 [3.40, 4.20] <0.001 3.80 [3.52, 4.10] 3.70 [3.40, 4.00] 0.10 Total bilirubin – (mg/dL) 0.4 [0.3, 0.7] 0.5 [0.3, 0.7] 0.277 0.4 [0.3, 0.6] 0.4 [0.3, 0.7] 0.07 ALT – (IU/L) 21.0 [14.0, 34.0] 19.0 [13.0, 30.00] <0.001 26.0 [17.0, 40.0] 22.0 [15.0, 37.8] 0.23 Creatinine – (mg/dL) 0.90 [0.73, 1.15] 0.99 [0.76, 1.41] <0.001 0.97 [0.80, 1.22] 1.09 [0.82, 1.42] 0.04 Outcome – no (%) Positive SARS-CoV-2 test 1125 (12.4) 309 (7.5) <0.001 Hospitalization 192 (17.1) 127 (41.1) <0.001 ICU admission 77 (6.8) 43 (13.9) <0.001 Hospital mortality 32 (2.8) 20 (6.5) 0.01 Continuous data are presented as median [IQR]. BMI stands for body mass index;USD for US dollar;COPD for chronic obstructive pulmonary disease;NSAIDS for nonsteroidal anti-inflammatory drugs;ACE for angiotensin-converting enzyme;ARB for angiotensin receptor blocker;and ICU for Intensive Care Unit. The effect of influenza vaccines, and adjuvanted vaccin s in particular, on Th17 immune responses in coronavirus immunopathology and on vaccine-induced immune enhancement [5] is unknown and needs to be closely monitored.

A Network Medicine Approach to Investigation and Population-based Validation of Disease Manifestations and Drug Repurposing for COVID-19.

The global Coronavirus Disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to unprecedented social and economic consequences. The risk of morbidity and mortality due to COVID-19 increases dramatically in the presence of co-existing medical conditions while the underlying mechanisms remain unclear. Furthermore, there are no proven effective therapies for COVID-19. This study aims to identify SARS-CoV-2 pathogenesis, diseases manifestations, and COVID-19 therapies using network medicine methodologies along with clinical and multi-omics observations. We incorporate SARS-CoV-2 virus-host protein-protein interactions, transcriptomics, and proteomics into the human interactome. Network proximity measure revealed underlying pathogenesis for broad COVID-19-associated manifestations. Multi-modal analyses of single-cell RNA-sequencing data showed that co-expression of ACE2 and TMPRSS2 was elevated in absorptive enterocytes from the inflamed ileal tissues of Crohn's disease patients compared to uninflamed tissues, revealing shared pathobiology by COVID-19 and inflammatory bowel disease. Integrative analyses of metabolomics and transcriptomics (bulk and single-cell) data from asthma patients indicated that COVID-19 shared intermediate inflammatory endophenotypes with asthma (including IRAK3 and ADRB2). To prioritize potential treatment, we combined network-based prediction and propensity score (PS) matching observational study of 18,118 patients from a COVID-19 registry. We identified that melatonin (odds ratio (OR) = 0.36, 95% confidence interval (CI) 0.22-0.59) was associated with 64% reduced likelihood of a positive laboratory test result for SARS-CoV-2. Using PS-matching user active comparator design, melatonin was associated with 54% reduced likelihood of SARS-CoV-2 positive test result compared to angiotensin II receptor blockers or angiotensin-converting enzyme inhibitors (OR = 0.46, 95% CI 0.24-0.86).

A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19.

The global coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to unprecedented social and economic consequences. The risk of morbidity and mortality due to COVID-19 increases dramatically in the presence of coexisting medical conditions, while the underlying mechanisms remain unclear. Furthermore, there are no approved therapies for COVID-19. This study aims to identify SARS-CoV-2 pathogenesis, disease manifestations, and COVID-19 therapies using network medicine methodologies along with clinical and multi-omics observations. We incorporate SARS-CoV-2 virus-host protein-protein interactions, transcriptomics, and proteomics into the human interactome. Network proximity measurement revealed underlying pathogenesis for broad COVID-19-associated disease manifestations. Analyses of single-cell RNA sequencing data show that co-expression of ACE2 and TMPRSS2 is elevated in absorptive enterocytes from the inflamed ileal tissues of Crohn disease patients compared to uninflamed tissues, revealing shared pathobiology between COVID-19 and inflammatory bowel disease. Integrative analyses of metabolomics and transcriptomics (bulk and single-cell) data from asthma patients indicate that COVID-19 shares an intermediate inflammatory molecular profile with asthma (including IRAK3 and ADRB2). To prioritize potential treatments, we combined network-based prediction and a propensity score (PS) matching observational study of 26,779 individuals from a COVID-19 registry. We identified that melatonin usage (odds ratio [OR] = 0.72, 95% CI 0.56-0.91) is significantly associated with a 28% reduced likelihood of a positive laboratory test result for SARS-CoV-2 confirmed by reverse transcription-polymerase chain reaction assay. Using a PS matching user active comparator design, we determined that melatonin usage was associated with a reduced likelihood of SARS-CoV-2 positive test result compared to use of angiotensin II receptor blockers (OR = 0.70, 95% CI 0.54-0.92) or angiotensin-converting enzyme inhibitors (OR = 0.69, 95% CI 0.52-0.90). Importantly, melatonin usage (OR = 0.48, 95% CI 0.31-0.75) is associated with a 52% reduced likelihood of a positive laboratory test result for SARS-CoV-2 in African Americans after adjusting for age, sex, race, smoking history, and various disease comorbidities using PS matching. In summary, this study presents an integrative network medicine platform for predicting disease manifestations associated with COVID-19 and identifying melatonin for potential prevention and treatment of COVID-19.

SARS-CoV-2 infection in the COPD population is associated with increased healthcare utilization: An analysis of Cleveland clinic's COVID-19 registry.

BACKGROUND: We sought to determine whether COPD conferred a higher risk for healthcare utilization in terms of hospitalization and clinical outcomes due to COVID-19. METHODS: A cohort study with covariate adjustment using multivariate logistic regression was conducted at the Cleveland Clinic Health System in Ohio and Florida. Symptomatic patients aged 35 years and older who were tested for SARS-CoV-2 between March 8 and May 13, 2020 were included. FINDINGS: 15,586 individuals tested for COVID-19 at the Cleveland Clinic between March 8, 2020 and May 13, 2020 met our inclusion criteria. 12.4% of COPD patients (164/1319) tested positive for COVID-19 compared to 16.6% (2363/14,267) of the non-COPD population. 48.2% (79/164) of COVID-19 positive COPD patients required hospitalization and 45.6% (36/79) required ICU admission. After adjustment for covariates, rates of COVID-19 infection were not significantly different than the non-COPD population (adj OR 0.97; CI: 0.89-1.05), but COPD patients had increased healthcare utilization as demonstrated by risk for hospitalization (adj OR 1.36; CI: 1.15-1.60), ICU admission (OR 1.20; CI: 1.02-1.40), and need for invasive mechanical ventilation (adj OR 1.49; CI: 1.28-1.73). Unadjusted risk for in-hospital mortality was higher in the COPD population (OR 1.51; CI: 1.14-1.96). After adjusting for covariates however, the risk for in-hospital mortality was not significantly different than the non-COPD population (adj OR 1.08: CI: 0.81-1.42). INTERPRETATION: Our analysis demonstrated that COPD patients with COVID-19 had a higher risk for healthcare utilization, although adjusted in-hospital mortality risk was not different than the non-COPD patients with COVID-19.