A180 CLINICAL OUTCOMES OF COVID-19 AND IMPACT ON DISEASE COURSE IN PATIENTS WITH INFLAMMATORY BOWEL DISEASE
Bibliographic record
Abstract
Abstract Background The impact of COVID-19 has been of great concern in patients with IBD worldwide, including an increased risk of severe outcomes and/or flare of IBD. Aims This study aims to evaluate prevalence, outcomes, the impact of COVID-19 in patients with IBD, and risk factors associated with severe COVID-19 or flare of IBD. Methods A consecutive cohort of IBD patients diagnosed with COVID was obtained between March 2020 - April 2021. Results A total of 3,516 IBD cohort patients were included. 82 patients (2.3%) were diagnosed with COVID infection (median age 39.0, 77% with Crohn’s disease). The prevalence of COVID-19 in IBD was significantly lower compared to the general population in Canada and Quebec (3.5% vs. 4.3%, p<0.001). Severe COVID occurred in 6 patients (7.3%); 2 patients (2.4%) died. A flare of IBD post-COVID infection was reported in 8 patients (9.8%) within 3 months. Age ≥55 years (OR 11.1, 95%CI:1.8–68.0), systemic corticosteroid use (OR:4.6, 95%CI:0.7–30.1), active IBD (OR:3.8, 95%CI:0.7–20.8) and comorbidity (OR:4.9, 95%CI:0.8–28.6) were associated with severe COVID. After initial infection, 61% received vaccinations. Conclusions The prevalence of COVID-19 among patients with IBD was lower than the general population. Severe COVID and flare of IBD were relatively rare. Older age, comorbidities, active IBD, and corticosteroid, but not biological therapy were associated with severe COVID. Outcome of COVID-19 in IBD patients, disease course of IBD, and vaccination after COVID infection Funding Agencies None
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".