Prevalence of Epstein–Barr Virus in a population of patients with inflammatory bowel disease: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: The Epstein-Barr Virus (EBV) is truly prolific, with a prevalence of more than 90% in the adult human population. There are, however, little data available on the prevalence of EBV among patients with Inflammatory Bowel Disease (IBD), a population that is frequently immunosuppressed and thus at risk for severe, often fatal, primary infection. AIM: To identify the prevalence of EBV in a population of patients with IBD and to compare it with that of the general population. METHODS: A database of 2500 IBD patients previously followed at the University of Alberta IBD Centre was queried; 60 of these patients were randomly chosen to participate. A total of 220 patients attending the IBD Centre for clinical appointment were also prospectively asked to participate. Participants completed serological testing for VCA-IgM, VCA-IgG and EBNA-IgG, to determine prior EBV exposure. RESULTS: A total of 263 patients underwent testing. Results for EBV seroprevalence of specific age groups were as follows: 18-20 years (n = 17), 29% seronegative; 21-25 years (n = 31), 29% seronegative; 26-30 years (n = 35), 31-35 years (n = 18) and 36-40 years (n = 25), 100% seropositive. Finally, 3% of those older than 40 (n = 117) were seronegative. EBV seroprevalence was similar for Crohn's disease and ulcerative colitis. Azathioprine was associated with seropositivity (P = 0.048). CONCLUSION: The prevalence of EBV seronegativity in the IBD population aged 18-25 years was similar to that described in the general population, and above age 25 years, seropositivity approached 100%.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".