Clinical Outcomes of COVID‐19 and Impact on Disease Course in Patients with Inflammatory Bowel Disease
Bibliographic record
Abstract
Background and Aims: The impact of COVID-19 has been of great concern in patients with inflammatory bowel disease (IBD) worldwide, including an increased risk of severe outcomes and/or possible flare of IBD. 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 activity. Methods: A consecutive cohort of IBD patients who were diagnosed with COVID-19 infection and followed up at the McGill University Health Care Centre was obtained between March 1, 2020, and April 30, 2021. Demographics, comorbidities, IBD (type, treatments, pre- and post-COVID-19 clinical activity, biomarkers, and endoscopic activity), and COVID-19-related outcomes (pneumonia, hospitalization, death, and flare of IBD disease) were analyzed. Results: < 0.001). Severe COVID-19 occurred in 6 patients (7.3%); 2 patients (2.4%) died. A flare of IBD post-COVID-19 infection was reported in 8 patients (9.8%) within 3 months. Biologic therapy was held during active COVID-19 infection in 37% of patients. Age ≥55 years (odds ratio (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 factors associated with severe COVID-19. After initial infection, 61% of IBD patients received COVID-19 vaccinations. Conclusion: The prevalence of COVID-19 infection among patients with IBD was lower than that in the general population in Canada. Severe COVID-19, mortality, and flare of IBD were relatively rare, while a large proportion of patients received COVID-19 vaccination. Older age, comorbidities, active IBD disease, and systemic corticosteroid, but not immunosuppressive or biological therapy, were associated with severe COVID-19 infection.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".