Risk Factors of Cytomegalovirus Reactivation in Ulcerative Colitis Patients: A Meta-Analysis
Bibliographic record
Abstract
Cytomegalovirus (CMV) infection is associated with exacerbation of disease activity in patients with ulcerative colitis (UC). However, the risk factors for CMV reactivation in this population remain debatable. This meta-analysis was performed to identify the risk factors for CMV reactivation in UC patients. PubMed, Cochrane Library, EMBASE, Web of Science, and China National Knowledge Infrastructure were searched from the inception of these databases to 31 August 2021, with the aim of identifying studies that investigated the risk factors of CMV reactivation in UC patients. A quality assessment of the included studies was performed with the Newcastle-Ottawa Scale. The publication bias was assessed respectively via a funnel plot and Egger’s regression asymmetry test. The robustness and reliability of each outcome were evaluated by sensitivity analysis. Twenty studies were included in the final meta-analysis, comprising a total of 2099 patients with UC. A significantly higher risk of CMV reactivation was observed in patients with severe UC (OR = 1.465, 95% CI: 1.107 to 1.939, p = 0.008), pancolitis (OR = 2.108, 95% CI: 1.586 to 2.800, p = 0.0001), older age of UC onset (MD = 6.212, 95% CI: 2.552 to 9.971, p = 0.001), as well as use of glucocorticoids (OR = 4.175, 95% CI: 3.076 to 5.666, p = 0.001), immunosuppressants (OR = 1.795, 95% CI: 1.289 to 2.501, p = 0.001), and azathioprine (OR = 1.444, 95% CI: 1.012 to 2.061, p = 0.043). However, infliximab treatment was observed not to increase the occurrence of CMV reactivation in patients who suffered from UC. In contrast, 5-aminosalicylic acid (OR = 0.674, 95% CI: 0.492 to 0.924, p = 0.014) was associated with a lower risk of CMV reactivation. Patients with UC should be closely monitored for risk factors of CMV reactivation in order to provide timely diagnosis and antiviral treatment.
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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.064 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".