Preexisting Autoimmunity Is Associated With Increased Severity of Coronavirus Disease 2019: A Retrospective Cohort Study Using Data From the National COVID Cohort Collaborative (N3C).

BACKGROUND: Identifying individuals with a higher risk of developing severe coronavirus disease 2019 (COVID-19) outcomes will inform targeted and more intensive clinical monitoring and management. To date, there is mixed evidence regarding the impact of preexisting autoimmune disease (AID) diagnosis and/or immunosuppressant (IS) exposure on developing severe COVID-19 outcomes. METHODS: A retrospective cohort of adults diagnosed with COVID-19 was created in the National COVID Cohort Collaborative enclave. Two outcomes, life-threatening disease and hospitalization, were evaluated by using logistic regression models with and without adjustment for demographics and comorbidities. RESULTS: Of the 2 453 799 adults diagnosed with COVID-19, 191 520 (7.81%) had a preexisting AID diagnosis and 278 095 (11.33%) had a preexisting IS exposure. Logistic regression models adjusted for demographics and comorbidities demonstrated that individuals with a preexisting AID (odds ratio [OR], 1.13; 95% confidence interval [CI]: 1.09-1.17; P < .001), IS exposure (OR, 1.27; 95% CI: 1.24-1.30; P < .001), or both (OR, 1.35; 95% CI: 1.29-1.40; P < .001) were more likely to have a life-threatening disease. These results were consistent when hospitalization was evaluated. A sensitivity analysis evaluating specific IS revealed that tumor necrosis factor inhibitors were protective against life-threatening disease (OR, 0.80; 95% CI: .66-.96; P = .017) and hospitalization (OR, 0.80; 95% CI: .73-.89; P < .001). CONCLUSIONS: Patients with preexisting AID, IS exposure, or both are more likely to have a life-threatening disease or hospitalization. These patients may thus require tailored monitoring and preventative measures to minimize negative consequences of COVID-19.

Influence of Prior SARS-CoV-2 Infection on COVID-19 Severity: Evidence from the National COVID Cohort Collaborative.

Background: A large share of SARS-CoV-2 infections now occur among previously infected individuals. In this study, we sought to determine whether prior infection modifies disease severity relative to no prior infection. Methods: We used data from first and second COVID-19 episodes in the National COVID Cohort Collaborative, a nationwide collection of de-identified electronic health records. We used nested logistic regressions of monthly cohorts weighted on the inverse probability of prior infection to assess risk of hospitalization, death, and increased severity in the first versus second infection cohorts. Results: We included a total of 2,058,274 individuals in the analysis, 147,592 of whom had two recorded infections. The impact of prior infection differed meaningfully between months. Prior infection was largely protective prior to March 2022, with odds ratios (ORs) as low as 0.66 (95% confidence interval: 0.51 to 0.86) in November 2021 for hospitalization. and as low as 0.23 (0.06 to 0.86) in June 2021 for death. However, prior infection was associated with an increased risk of hospitalization and death, mostly after March 2022 when the ORs were as high as 1.87 (1.26 to 2.80) and 2.99 (1.65 to 5.41) in April 2022, respectively. The overall OR for more severe disease was 1.06 (1.03 to 1.10) among previously infected individuals. Conclusion: In the pandemic's first two years, previously infected patients generally had less severe disease than people without prior infection. During the Omicron era, however, previously infected patients had the same or worse severity of disease as patients without prior infection.

Assessing the effect of selective serotonin reuptake inhibitors in the prevention of post-acute sequelae of COVID-19.

Background: Post-acute sequelae of COVID-19 (PASC) produce significant morbidity, prompting evaluation of interventions that might lower risk. Selective serotonin reuptake inhibitors (SSRIs) potentially could modulate risk of PASC via their central, hypothesized immunomodulatory, and/or antiplatelet properties although clinical trial data are lacking. Materials and Methods: This retrospective study was conducted leveraging real-world clinical data within the National COVID Cohort Collaborative (N3C) to evaluate whether SSRIs with agonist activity at the sigma-1 receptor (S1R) lower the risk of PASC, since agonism at this receptor may serve as a mechanism by which SSRIs attenuate an inflammatory response. Additionally, determine whether the potential benefit could be traced to S1R agonism. Presumed PASC was defined based on a computable PASC phenotype trained on the U09.9 ICD-10 diagnosis code. Results: Of the 17,908 patients identified, 1521 were exposed at baseline to a S1R agonist SSRI, 1803 to a non-S1R agonist SSRI, and 14,584 to neither. Using inverse probability weighting and Poisson regression, relative risk (RR) of PASC was assessed.A 29% reduction in the RR of PASC (0.704 [95% CI, 0.58-0.85]; P = 4 ×10-4) was seen among patients who received an S1R agonist SSRI compared to SSRI unexposed patients and a 21% reduction in the RR of PASC was seen among those receiving an SSRI without S1R agonist activity (0.79 [95% CI, 0.67 - 0.93]; P = 0.005).Thus, SSRIs with and without reported agonist activity at the S1R were associated with a significant decrease in the risk of PASC.

Assessing the Effect of Selective Serotonin Reuptake Inhibitors in the Prevention of Post-Acute Sequelae of COVID-19.

Importance: Post-acute sequelae of COVID-19 (PASC) produce significant morbidity, prompting evaluation of interventions that might lower risk. Selective serotonin reuptake inhibitors (SSRIs) potentially could modulate risk of PASC via their central, hypothesized immunomodulatory, and/or antiplatelet properties and therefore may be postulated to be of benefit in patients with PASC, although clinical trial data are lacking. Objectives: The main objective was to evaluate whether SSRIs with agonist activity at the sigma-1 receptor lower the risk of PASC, since agonism at this receptor may serve as a mechanism by which SSRIs attenuate an inflammatory response. A secondary objective was to determine whether potential benefit could be traced to sigma-1 agonism by evaluating the risk of PASC among recipients of SSRIs that are not S1R agonists. Design: Retrospective study leveraging real-world clinical data within the National COVID Cohort Collaborative (N3C), a large centralized multi-institutional de-identified EHR database. Presumed PASC was defined based on a computable PASC phenotype trained on the U09.9 ICD-10 diagnosis code to more comprehensively identify patients likely to have the condition, since the ICD code has come into wide-spread use only recently. Setting: Population-based study at US medical centers. Participants: Adults (≥ 18 years of age) with a confirmed COVID-19 diagnosis date between October 1, 2021 and April 7, 2022 and at least one follow up visit 45 days post-diagnosis. Of the 17 933 patients identified, 2021 were exposed at baseline to a S1R agonist SSRI, 1328 to a non-S1R agonist SSRI, and 14 584 to neither. Exposures: Exposure at baseline (at or prior to COVID-19 diagnosis) to an SSRI with documented or presumed agonist activity at the S1R (fluvoxamine, fluoxetine, escitalopram, or citalopram), an SSRI without agonist activity at S1R (sertraline, an antagonist, or paroxetine, which does not appreciably bind to the S1R), or none of these agents. Main Outcome and Measurement: Development of PASC based on a previously validated XGBoost-trained algorithm. Using inverse probability weighting and Poisson regression, relative risk (RR) of PASC was assessed. Results: A 26% reduction in the RR of PASC (0.74 [95% CI, 0.63-0.88]; P = 5 × 10-4) was seen among patients who received an S1R agonist SSRI compared to SSRI unexposed patients and a 25% reduction in the RR of PASC was seen among those receiving an SSRI without S1R agonist activity (0.75 [95% CI, 0.62 - 0.90]; P = 0.003) compared to SSRI unexposed patients. Conclusions and Relevance: SSRIs with and without reported agonist activity at the S1R were associated with a significant decrease in the risk of PASC. Future prospective studies are warranted.

Pre-existing autoimmunity is associated with increased severity of COVID-19: A retrospective cohort study using data from the National COVID Cohort Collaborative (N3C).

Importance: Identifying individuals with a higher risk of developing severe COVID-19 outcomes will inform targeted or more intensive clinical monitoring and management. Objective: To examine, using data from the National COVID Cohort Collaborative (N3C), whether patients with pre-existing autoimmune disease (AID) diagnosis and/or immunosuppressant (IS) exposure are at a higher risk of developing severe COVID-19 outcomes. Design setting and participants: A retrospective cohort of 2,453,799 individuals diagnosed with COVID-19 between January 1 st , 2020, and June 30 th , 2022, was created from the N3C data enclave, which comprises data of 15,231,849 patients from 75 USA data partners. Patients were stratified as those with/without a pre-existing diagnosis of AID and/or those with/without exposure to IS prior to COVID-19. Main outcomes and measures: Two outcomes of COVID-19 severity, derived from the World Health Organization severity score, were defined, namely life-threatening disease and hospitalization. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using logistic regression models with and without adjustment for demographics (age, BMI, gender, race, ethnicity, smoking status), and comorbidities (cardiovascular disease, dementia, pulmonary disease, liver disease, type 2 diabetes mellitus, kidney disease, cancer, and HIV infection). Results: In total, 2,453,799 (16.11% of the N3C cohort) adults (age> 18 years) were diagnosed with COVID-19, of which 191,520 (7.81%) had a prior AID diagnosis, and 278,095 (11.33%) had a prior IS exposure. Logistic regression models adjusted for demographic factors and comorbidities demonstrated that individuals with a prior AID (OR = 1.13, 95% CI 1.09 - 1.17; p =2.43E-13), prior exposure to IS (OR= 1.27, 95% CI 1.24 - 1.30; p =3.66E-74), or both (OR= 1.35, 95% CI 1.29 - 1.40; p =7.50E-49) were more likely to have a life-threatening COVID-19 disease. These results were confirmed after adjusting for exposure to antivirals and vaccination in a cohort subset with COVID-19 diagnosis dates after December 2021 (AID OR = 1.18, 95% CI 1.02 - 1.36; p =2.46E-02; IS OR= 1.60, 95% CI 1.41 - 1.80; p =5.11E-14; AID+IS OR= 1.93, 95% CI 1.62 - 2.30; p =1.68E-13). These results were consistent when evaluating hospitalization as the outcome and also when stratifying by race and sex. Finally, a sensitivity analysis evaluating specific IS revealed that TNF inhibitors were protective against life-threatening disease (OR = 0.80, 95% CI 0.66-0.96; p =1.66E-2) and hospitalization (OR = 0.80, 95% CI 0.73 - 0.89; p =1.06E-05). Conclusions and Relevance: Patients with pre-existing AID, exposure to IS, or both are more likely to have a life-threatening disease or hospitalization. These patients may thus require tailored monitoring and preventative measures to minimize negative consequences of COVID-19.