Viral infections and complications in inflammatory bowel disease
Bibliographic record
Abstract
This thesis aimed to clarify the impact of several viral infections, their complications and vaccination responses in patients with inflammatory bowel disease (IBD). The first part focuses on two herpes viruses, Epstein-Barr virus (EBV) and cytomegalovirus (CMV), that can cause severe opportunistic infections, mostly as a rare complication of the use of immunosuppressants. In the second part we studied the risk of the premalignant condition cervical intraepithelial neoplasia (CIN) and cervical cancer caused by human papillomavirus (HPV) in women with IBD and we aimed to identify risk factors, in particular by studying the exposure to immunosuppressants in detail. The third part describes an uncommon case of a hepatitis E virus (HEV) infection in a patient using the gut-selective biologic agent vedolizumab. In the last part of this thesis, we focused on vaccination responses to influenza vaccination and severe acute respiratory coronavirus 2 (SARS-Cov-2) vaccination in immunocompromised patients with IBD and other immune-mediated inflammatory diseases (IMID).
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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".