Serological Responses to the First Three Doses of SARS-CoV-2 Vaccination in Inflammatory Bowel Disease: A Prospective Cohort Study
Bibliographic record
Abstract
Background Individuals with inflammatory bowel disease (IBD) who are immunocompromised may have a reduced serological response to the SARS-CoV-2 vaccine. We investigated serological responses following 1 st , 2 nd , and 3 rd doses of SARS-CoV-2 vaccination in those with IBD. Methods A prospective cohort study of persons with IBD ( n = 496) assessed serological response 1–8 weeks after 1 st dose vaccination, 1–8 weeks after 2 nd dose, 8 or more weeks after 2 nd dose, and at least 1 week after 3 rd dose. Seroconversion and geometric mean titer (GMT) with 95% confidence intervals (CI) were assessed for antibodies to the SARS-CoV-2 spike protein. Multivariable linear regression models assessed the adjusted fold change (FC) in antibody levels. Results Seroconversion and GMT increased from post-1 st dose to 1–8 weeks post-2 nd dose (81.6%, 1814 AU/mL vs. 98.7%, 9229 AU/mL, p <0.001), decreased after 8 weeks post-2 nd dose (94.9%, 3002 AU/mL, p <0.001), and rebounded post-3 rd dose (99.6%, 14639 AU/mL, p <0.001). Prednisone was the only IBD-related medication associated with diminished antibody response after 3 rd -dose vaccination (FC: 0.07 [95% CI: 0.02, 0.20]). Antibody levels steadily decline following the 2 nd (FC: 0.92 [95% CI: 0.90, 0.94] per week) and 3 rd dose (FC: 0.88 [95% CI: 0.84, 0.92] per week) of the SARS-CoV-2 vaccine. Conclusion A three-dose regimen of vaccination to SARS-CoV-2 yields a robust antibody response for those with IBD across all classes of IBD therapies except for prednisone. The decaying antibody levels following the 3 rd dose of the vaccine should be monitored in future studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".