Impact of Allergic Rhinitis and Asthma on COVID-19 Infection, Hospitalization, and Mortality
Why this work is in the frame
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Bibliographic record
Abstract
BackgroundIt remains unclear if patients with allergic rhinitis (AR) and/or asthma are susceptible to corona virus disease 2019 (COVID-19) infection, severity, and mortality.ObjectiveTo investigate the role of AR and/or asthma in COVID-19 infection, severity, and mortality, and assess whether long-term AR and/or asthma medications affected the outcomes of COVID-19.MethodsDemographic and clinical data of 70,557 adult participants completed SARS-CoV-2 testing between March 16 and December 31, 2020, in the UK Biobank were analyzed. The rates of COVID-19 infection, hospitalization, and mortality in relation to pre-existing AR and/or asthma were assessed based on adjusted generalized linear models. We further analyzed the impact of long-term AR and/or asthma medications on the risk of COVID-19 hospitalization and mortality.ResultsPatients with AR of all ages had lower positive rates of SARS-CoV-2 tests (relative risk [RR]: 0.75, 95% confidence interval [CI]: 0.69-0.81, P < .001), with lower susceptibility in males (RR: 0.74, 95% CI: 0.65-0.85, P < .001) than females (RR: 0.8, 95% CI: 0.72-0.9, P < .001). However, similar effects of asthma against COVID-19 hospitalization were only major in participants aged <65 (RR: 0.93, 95% CI: 0.86-1, P = .044) instead of elderlies. In contrast, patients with asthma tested positively had higher risk of hospitalization (RR: 1.42, 95% CI: 1.32-1.54, P < .001). Neither AR nor asthma had an impact on COVID-19 mortality. None of conventional medications for AR or asthma, for example, antihistamines, corticosteroids, or β2 adrenoceptor agonists, showed association with COVID-19 infection or severity.ConclusionAR (all ages) and asthma (aged <65) act as protective factors against COVID-19 infection, whereas asthma increases risk for COVID-19 hospitalization. None of the long-term medications had a significant association with infection, severity, and mortality of COVID-19 among patients with AR and/or asthma. It remains unclear if patients with allergic rhinitis (AR) and/or asthma are susceptible to corona virus disease 2019 (COVID-19) infection, severity, and mortality. To investigate the role of AR and/or asthma in COVID-19 infection, severity, and mortality, and assess whether long-term AR and/or asthma medications affected the outcomes of COVID-19. Demographic and clinical data of 70,557 adult participants completed SARS-CoV-2 testing between March 16 and December 31, 2020, in the UK Biobank were analyzed. The rates of COVID-19 infection, hospitalization, and mortality in relation to pre-existing AR and/or asthma were assessed based on adjusted generalized linear models. We further analyzed the impact of long-term AR and/or asthma medications on the risk of COVID-19 hospitalization and mortality. Patients with AR of all ages had lower positive rates of SARS-CoV-2 tests (relative risk [RR]: 0.75, 95% confidence interval [CI]: 0.69-0.81, P < .001), with lower susceptibility in males (RR: 0.74, 95% CI: 0.65-0.85, P < .001) than females (RR: 0.8, 95% CI: 0.72-0.9, P < .001). However, similar effects of asthma against COVID-19 hospitalization were only major in participants aged <65 (RR: 0.93, 95% CI: 0.86-1, P = .044) instead of elderlies. In contrast, patients with asthma tested positively had higher risk of hospitalization (RR: 1.42, 95% CI: 1.32-1.54, P < .001). Neither AR nor asthma had an impact on COVID-19 mortality. None of conventional medications for AR or asthma, for example, antihistamines, corticosteroids, or β2 adrenoceptor agonists, showed association with COVID-19 infection or severity. AR (all ages) and asthma (aged <65) act as protective factors against COVID-19 infection, whereas asthma increases risk for COVID-19 hospitalization. None of the long-term medications had a significant association with infection, severity, and mortality of COVID-19 among patients with AR and/or asthma.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it