Vaccination in Inflammatory Bowel Disease Patients: Attitudes, Knowledge, and Uptake
Bibliographic record
Abstract
BACKGROUND: Immunomodulators and biological agents, used to treat inflammatory bowel disease [IBD], are associated with an increased risk of infection, including vaccine-preventable infections. We assessed patient attitudes towards vaccination, knowledge of vaccine recommendations, and uptake of recommended vaccines. METHODS: Patients attending IBD clinics completed a self-administered, structured, paper-based questionnaire. We collected demographic data, medical and immunisation history, self-reported patient uptake, knowledge, and perceptions of childhood and adult vaccinations. RESULTS: The prevalence of treatment with biologicals, steroids, thiopurines, and methotrexate among the 300 respondents were 37.3%, 16.0%, 16.0%, and 5.7%, respectively. Self-reported vaccine completion was reported by 45.3% of patients. Vaccination uptake rates were 61.3% for influenza, 10.3% for pneumococcus, 61.0% for hepatitis B, 52.0% for hepatitis A, 26.0% for varicella, 20.7% for meningococcus, 5.3% for herpes zoster, and 11.0% for herpes papilloma virus [females only]. Significant predictors of vaccine completion were annual vaccination review by family physician (odds ratio [OR] = 1.82) or gastroenterologist [OR = 1.72], current steroid use [OR = 1.28], and current or prior treatment with biologicals [OR = 1.42]. The majority of patients reported that the primary responsibility to ensure vaccine completion lies with the patient [41.7%] and the family physician [32.3%]. Uncertainty about indications, fears of side effects, and concerns regarding vaccine safety were the most commonly reported reasons for non-uptake [22.0%, 20.7%, and 5.3%, respectively]. CONCLUSIONS: Uptake of recommended vaccines among IBD patients is suboptimal. Annual vaccination reviews by both family physician and gastroenterologist may improve vaccine uptake. Interventions targeted at improving vaccination uptake in IBD patients are needed.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".