Antiviral Therapy in Steroid-refractory Ulcerative Colitis with Cytomegalovirus
Bibliographic record
Abstract
BACKGROUND: The role of antiviral therapy in patients with ulcerative colitis (UC) with cytomegalovirus (CMV) remains unclear. We therefore performed a systematic review and meta-analysis to assess the association between antiviral therapy and the risk of colectomy. METHODS: Multiple electronic databases were searched systematically through July 2014 for studies reporting the risk of colectomy in patients with UC with CMV stratified by treatment with antiviral agents. Colectomy rates were assessed for the overall cohort and stratified by corticosteroid (CS) refractoriness. We estimated summary odds ratios and 95% confidence intervals, using random-effects model, and used Grading of Recommendations Assessment, Development, and Evaluation criteria to appraise the quality of evidence. RESULTS: Fifteen observational studies (333 patients with UC with CMV, 43.2% treated with antiviral agents) were identified, of which 8 stratified patients according to CS-refractory disease (55.4% treated with antiviral agents). Antiviral therapy resulted in a significantly lower risk of colectomy in patients with CS-refractory disease (odds ratio, 0.20; 95% confidence interval, 0.08-0.49; I = 0%) but not in the overall population of patients with UC (odds ratio, 0.92; 95% confidence interval, 0.31-2.76; I = 65). The quality evidence was low. The results were stable when restricting the analysis to patients with a tissue diagnosis of CMV and studies that defined CS-refractory disease as a failure to respond to intravenous CS. CONCLUSIONS: Antiviral therapy may benefit a subgroup of patients with UC who are refractory to CS. Further prospective trials are required to confirm these findings.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.015 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".