Inflammatory Bowel Disease Clinical Activity is Associated with COVID-19 Severity Especially in Younger Patients
Bibliographic record
Abstract
BACKGROUND AND AIMS: Age is a major prognostic factor for COVID-19 outcomes. The effect of inflammatory bowel disease [IBD] activity on COVID-19 is unclear. We examined the relationship between IBD activity and COVID-19 severity according to age. METHODS: We included IBD patients diagnosed with COVID-19, reported to SECURE-IBD between March 13, 2020 and August 3, 2021. Clinical IBD activity was measured by physician global assessment [PGA]. COVID-19-related outcomes were [1] intensive care unit [ICU] admission, ventilation or death, and [2] hospitalization. Using generalized estimating equations, we determined adjusted odds ratios [aOR, 95% confidence interval] for moderate and severe PGA vs clinical remission/mild PGA, controlling for demographics, medications and COVID-19 diagnosis period. We performed stratified analyses by age [≤50 vs >50 years]. RESULTS: Among 6078 patients, adverse COVID-19 outcomes were more common with active IBD: ICU/ventilation/death in 3.6% [175/4898] of remission/mild, 4.9% [45/920] of moderate and 8.8% [23/260] of severe [p < 0.001]; and hospitalization in 13% [649/4898] of remission/mild, 19% [178/920] of moderate and 38% [100/260] of severe [p < 0.001]. Stratified by decade, effect sizes were larger for younger patients. In patients ≤50 years, severe PGA was independently associated with ICU/ventilation/death (aOR 3.27 [1.15-9.30]) and hospitalization (aOR 4.62 [2.83-7.55]). In contrast, severe PGA was not independently associated with COVID-19 outcomes in those older than 50 years. CONCLUSIONS: Clinically active IBD may be a risk factor for severe COVID-19, particularly in younger patients. IBD disease control, including through medication compliance, and strategies to mitigate the risk of COVID-19 infection amongst patients with active IBD [e.g. distancing, immunization] are key to limit adverse COVID-19 outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".