P814 Latent cytomegalovirus infection does not influence disease course in inflammatory bowel disease
Bibliographic record
Abstract
Cytomegalovirus (CMV) infection is common in the general population. Patients with inflammatory bowel disease (IBD) are at risk for CMV reactivation, most likely mediated by both the inflammatory state of the mucosa and use of immunosuppressive drugs. A CMV infection affects the disease course in transplant recipients and HIV patients. However, it is unclear if latent CMV infection has influence on the long-term disease course in IBD. In this study, we investigated if latent CMV infection has an impact on IBD disease outcome. A nested case-only cross-sectional study was performed in the IBD cohort of the University Medical Center Groningen, a large tertiary referral center in the Netherlands. Data were prospectively collected relating patients’ clinical characteristics, disease course and medication use. Patients were screened for the availability of CMV serology tests performed as part of standard clinical care. When multiple tests were available, most recent test results were used for further analysis. Patients were considered seropositive when anti-CMV IgG antibodies were detected (>4 AU/ml). Logistic regression models were used to estimate multivariable-adjusted odds ratios for disease outcomes, adjusting for confounding factors. CMV serology was available for 412 of 1215 (33.9%) patients, of whom 186 (45.1%) patients were seropositive, which is comparable to seroprevalence in the general Dutch population. Seropositive patients were significantly older and had a longer disease duration (both p-values ≤ 0.01). No difference was found for CMV IgG seroprevalence between types of IBD (p-value = 0.86). CMV IgG seroprevalence was associated with patients of non-Western origin, birth outside the Netherlands, and a lower educational level (all p-values ≤ 0.02). CMV IgG seroprevalence was not associated with a more complicated disease course evaluated by the Montreal classification, need for surgical resection or the use of steroids, immunosuppressive drugs and biologicals (all p-values > 0.05). In this study, we show that latent CMV infection is not associated with a more complicated disease course, the need for surgery or treatment regimens in IBD. While testing for CMV IgG/IgM antibodies and viremia as part of the diagnostic work-up for acute enteritis remains important, standard CMV IgG testing is unnecessary for clinical decision-making in IBD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".