What are the neurodevelopmental outcomes of children with asymptomatic congenital cytomegalovirus infection at birth? A systematic literature review
Bibliographic record
Abstract
Abstract Congenital cytomegalovirus (cCMV) is among the most common congenital infections globally. Of 85%–90% cCMV‐infected infants without symptoms at birth, 10%–15% develop sequelae, most commonly sensorineural hearing loss (SNHL); their childhood neurodevelopmental outcomes are less well understood. Embase and MEDLINE were searched for publications from 16th September 2016 to 9th February 2024 to identify studies reporting primary data on neurodevelopmental outcomes in children with asymptomatic cCMV (AcCMV), measured using assessment tools or as evaluated by the study investigators, clinicians, educators, or parents. The Newcastle‐Ottawa scale was applied to studies to assess risk of bias. Of 28 studies from 18 mostly high‐income countries, there were 5‐109 children with AcCMV per study and 6/28 had a mean or median age at last follow‐up of ≥5 years. Children with AcCMV had better neurodevelopmental outcomes than children with symptomatic cCMV in 16/19 studies. Of 9/28 studies comparing AcCMV with CMV‐uninfected children, six reported similar outcomes whilst three reported differences limited to measures of full‐scale intelligence and receptive vocabulary among children with AcCMV and SNHL, or more generally in motor impairment. Common limitations of studies for our question were a lack of cCMV‐uninfected controls, heterogeneous definitions of AcCMV, lack of focus on neurodevelopment, selection bias and inadequate follow‐up. There was little evidence of children with AcCMV having worse neurodevelopmental outcomes than CMV‐uninfected children, but this conclusion is limited by study characteristics and quality; findings highlight the need for well‐designed and standardised approaches to investigate long‐term sequelae.
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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 | 0.005 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".