Cytomegalovirus and its role in congenital infection: A narrative-review study
Bibliographic record
Abstract
Introduction: Human cytomegalovirus (HCMV) is a major cause of congenital infection worldwide. HCMV seroprevalence is higher in Asian regions than in European societies. Pregnant women can transmit the virus to their fetuses depending on the type of infection (primary or non-primary). Congenital HCMV infection is the leading cause of sensorineural hearing loss in children. Given the importance of HCMV, this narrative-review study was performed with aim to determine the role of HCMV in congenital infection. Methods: In this narrative-review study, to find the related articles, the English and Persian databases including Google Scholar, PubMed and Magiran were searched from 2002 to 2019. The keywords of cytomegalovirus, congenital cytomegalovirus infection, diagnosis and prevalence both in Persian and English and also their combination used. Results: Developing countries estimated that the incidence of HCMV congenital infection is 6%-14%. While in developed countries such as Western Europe, United States, Canada and Australia, the incidence rate is 0.5-0.7%. Although HCMV infection is a significant cause of hearing loss and disability in children, there is still little awareness among general population and some physicians in this field. Several European countries routinely screen the pregnant women for HCMV but this screening is not currently performed in Iran. Conclusion: The studies in different societies highlighted the importance of congenital HCMV infection and its long-term complications in infants.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".