Detection of Cytomegalovirus Infection in Infants with Biliary Atresia: A Meta-analysis
Bibliographic record
Abstract
Abstract Objectives Biliary atresia (BA) is the most common indication of liver transplantation in children. Several reports attributed BA to both prenatal and perinatal etiologies, including a viral infection-induced autoimmune response that targets the bile ducts. Cytomegalovirus (CMV) remains the most common virus being linked to BA. This meta-analysis aimed to estimate to what extent CMV infection is detected in patients with BA. Methods This study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The databases of MEDLINE, Embase, Scopus, WHO-Virtual Health Library (VHL), ScienceDirect, and Google Scholar were used for the systematic search. The risk of bias was assessed using the Newcastle–Ottawa scale. Random effects model was used to estimate the pooled prevalence estimate with the corresponding 95% confidence interval (CI) using Comprehensive Meta-Analysis Software version 3.3. Results A total of 19 studies that fulfilled the eligibility criteria were included in the meta-analysis. The total number of infants with BA was 630 patients, and the pooled overall prevalence of CMV infection among them was 25.4% (95% CI: 15.9%–38.0%). There was high heterogeneity among studies (I2 = 85.1%, p < .001), and subgroup analyses showed significant regional differences (X2 = 48.9, p <.001). Data on the prognosis of CMV-associated BA were scarce and obtainable from few studies that suggested an association between detection of CMV infection and poor prognosis of BA. Conclusions The limited available data demonstrates that the rate of detection of CMV infection is high in infants with BA. There is still a need for large studies with appropriate controls for obtaining more reliable results about the various aspects of the association between CMV infection and BA.
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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.071 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".