The Multiple Waves of COVID-19 in Patients With Inflammatory Bowel Disease: A Temporal Trend Analysis
Bibliographic record
Abstract
BACKGROUND: Cases of coronavirus disease 2019 (COVID-19) have emerged in discrete waves. We explored temporal trends in the reporting of COVID-19 in inflammatory bowel disease (IBD) patients. METHODS: The Surveillance Epidemiology of Coronavirus Under Research Exclusion for Inflammatory Bowel Disease (SECURE-IBD) is an international registry of IBD patients diagnosed with COVID-19. The average percent changes (APCs) were calculated in weekly reported cases of COVID-19 during the periods of March 22 to September 12, September 13 to December 12, 2020, and December 13 to July 31, 2021. RESULTS: Across 73 countries, 6404 cases of COVID-19 were reported in IBD patients. COVID-19 reporting decreased globally by 4.2% per week (95% CI, -5.3% to -3.0%) from March 22 to September 12, 2020, then climbed by 10.2% per week (95% CI, 8.1%-12.3%) from September 13 to December 12, 2020, and then declined by 6.3% per week (95% CI, -7.8% to -4.7%). In the fall of 2020, weekly reporting climbed in North America (APC, 11.3%; 95% CI, 8.8-13.8) and Europe (APC, 17.7%; 95% CI, 12.1%-23.5%), whereas reporting was stable in Asia (APC, -8.1%; 95% CI, -15.6-0.1). From December 13, 2020, to July 31, 2021, reporting of COVID-19 in those with IBD declined in North America (APC, -8.5%; 95% CI, -10.2 to -6.7) and Europe (APC, -5.4%; 95% CI, -7.2 to -3.6) and was stable in Latin America (APC, -1.5%; 95% CI, -3.5% to 0.6%). CONCLUSIONS: Temporal trends in reporting of COVID-19 in those with IBD are consistent with the epidemiological patterns COVID-19 globally.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".