Covid-19 severity and mortality in Veterans with chronic lung disease

Abstract: INTRODUCTION: Chronic lung disease (CLD) has been associated with risk for more severe manifestations and death with COVID-19. However, few studies have evaluated the risk overall and by type of CLD for severity of COVID-19 outcomes in a US national cohort. METHODS: Using data from the Veterans Health Administration, we determined the risk associated with CLDs including COPD (mild/severe), asthma (mild/active/severe), idiopathic pulmonary fibrosis (IPF), sarcoidosis and other interstitial lung diseases (ILDs) for outcomes among veterans with SARS-CoV-2 positive tests between 3/1/2020-4/30/2021. We used multinomial regression to estimate risk of four mutually exclusive COVID-19 outcomes within 30-days: outpatient management, hospitalization, hospitalization with indicators of critical illness, or death. We calculated the overall proportion with each outcome, the absolute risk difference and risk ratios for each outcome between those with and without CLD. We also describe clinical and laboratory abnormalities by CLD in those hospitalized. RESULTS: We included 208,283 veterans with COVID-19; 35,587 (17%) had CLD. Compared to no CLD, veterans with CLD were older and had more comorbidities. Hospitalized veterans with CLD were more likely to have low temperature, mean arterial pressure, oxygen saturation, leukopenia and thrombocytopenia, and more likely to receive oxygen, mechanical ventilation and vasopressors. Veterans with CLD were significantly less likely to have mild COVID-19 (-4.5%, adjusted risk ratio [aRR] 0.94, 95% confidence interval [CI] 0.94-0.95), and more likely to have a moderate (+2.5%, aRR 1.21, 95% CI 1.18-1.24), critical (+1.4%, aRR 1.38, 95% CI 1.32-1.45) or fatal (+0.7%, aRR 1.15, 95% CI 1.10-1.20) outcome. IPF was most strongly associated with COVID-19 severity, especially mortality (+3.2%, aRR 1.69, 95% CI 1.46-1.96), followed by other ILDs and COPD, whereas asthma was less likely to be associated with severity of COVID-19. In veterans under age 65, worse COVID-19 outcomes were generally more likely with IPF, sarcoidosis, and other ILDs. CONCLUSIONS: Veterans who had CLD, particularly IPF, other ILDs and COPD, had an increased probability of more severe 30-day outcomes with COVID-19. These results provide insight into the absolute and relative risk of different CLDs with severity of COVID-19 outcomes and can help inform considerations of healthcare utilization and prognosis.

Read the full article
Report a problem with this article

Related articles

  • More for Researchers

    Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data

    Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate the extraction of opioid relapses, and the timing of these occurrences, from veteran patients' electronic medical record. We then demonstrated the utility of our NLP tool via analysis of pre-/post-COVID-19 opioid relapse trends among veterans with OUD. For this demonstration, we analyzed data from 107,606 veterans OUD enrolled in Veterans Health Administration, comparing a pandemic-exposed cohort (n = 53,803; January 2019-March 2021) to a matched prepandemic cohort (n = 53,803; October 2017-December 2019). The recall of our NLP tool was 75% and our precision was 94%, demonstrating moderate sensitivity and excellent specificity. Using the NLP tool, we found that the odds of opioid relapse postpandemic onset were proportionally higher compared to prepandemic trends, despite patients having fewer mental health encounters from which to derive instances of relapse postpandemic onset. In this research application of the tool, and as hypothesized, we found that opioid relapse risk was elevated postpandemic. The application of NLP Methods: to identify and monitor relapse risk holds promise for future surveillance, risk prevention, and clinical outcome research.

    Mental Health Peer reviewed