Crohn’s and Colitis Canada’s 2021 Impact of COVID-19 and Inflammatory Bowel Disease in Canada: Children and Expectant Mothers With Inflammatory Bowel Disease
Bibliographic record
Abstract
Coronavirus disease 2019 (COVID-19) in children with inflammatory bowel disease (IBD) typically results in a mild infection, similar to those without IBD. Children and adolescents have less severe manifestations of COVID-19 compared to older people, whether or not they have IBD. However, some IBD medications (in particular, corticosteroids) are associated with more severe COVID-19. During the first year of the global pandemic, more IBD care was provided with online technology, necessitated by efforts to reduce hospital and clinic visits. Additionally, non-endoscopic monitoring of inflammation has been required due to the cancellation of non-urgent procedures, resulting in longer endoscopy wait-times. In contrast, pregnant people (with and without IBD) who contract COVID-19 are at increased risk of severe manifestations, death and preterm delivery, making them a priority for severe acute respiratory syndrome coronavirus 2 protective measures and vaccination. Few studies have examined effect of COVID-19 on IBD-related disease activity in pregnant people with IBD. The pandemic has significantly affected the mental health and sense of well-being of children and their families, as well as pregnant people with IBD. These groups were much more likely to experience anxiety and depression compared with prior to the pandemic, even while concern has mostly abated regarding the effect of IBD medications and COVID-19 severity. Unfortunately, the availability of mental health care providers who specialize in people with IBD has not kept pace with the increasing demand.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".