Bibliographic record
Abstract
The increasing prevalence of vaccine-preventable diseases (VPDs) in patients with inflammatory bowel disease (IBD) has given rise to increased awareness of the need to educate clinicians and patients about the critical role of immunization in this patient population. In 2023, it was estimated that in the Canadian population, 320,000 individuals (0.83%) were affected by IBD. Patients with IBD are at risk of vaccine-preventable diseases as the result of several factors, including potentially reduced efficacy and safety of vaccinations in the context of systemic immunosuppressive therapies administered for the management of IBD2 and a state of malnutrition caused by the disease. Barriers to the administration of vaccinations include: Clinicians’ reluctance to immunize patients with IBD; patient lack of awareness regarding the critical importance of a structured vaccination protocol; gastroenterologists’ assumption that immunization falls under the auspices of the primary care provider (PCP); and limited time and resources. The objective of this paper is to highlight the need for broader implementation of the 2021 Canadian Association of Gastroenterology (CAG) Guidelines concerning both live and inactivated vaccines in patients with IBD. This overview focuses on commonly encountered VPDs for which administration of live and non-live vaccines may be required and for which an IBD-specific deviation from the NACI recommendations have been made. The vaccines selected for this brief overview are also commonly administered in clinical practice. Clinicians may experience uncertainty in relation to management of these vaccinations in practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".