OP01.03: Brain <scp>MRI</scp> abnormalities in fetuses with congenital cytomegalovirus infection: systematic review and meta‐analysis
Bibliographic record
Abstract
It is widely accepted that fetal MRI is complementary to ultrasound brain evaluation, however, the incidence of fetal brain MRI abnormalities secondary to congenital CMV infection is yet to be established. The aim of this study was to quantify the incidence of fetal brain MRI abnormalities secondary to congenital CMV infection. Medline, Embase and the Cochrane library were searched electronically utilising combinations of the relevant medical subject heading for “Cytomegalovirus infection” and “MRI”. The outcomes assessed included all the brain abnormalities associated with congenital CMV infection. Quality assessment of the included studies was performed using the Newcastle-Ottawa Scale (NOS) for cohort studies. Meta-analyses of proportions were used to combine data. Between-study heterogeneity was explored using the I statistic. A total of 119 articles were identified, 14 were assessed with respect to their eligibility for inclusion and total of 7 studies were included in the systematic review. Among the 252 fetuses of congenital CMV infection, there were only 2 cases with brain calcifications, giving an overall prevalence of 1.2% (95% CI, 0.2-3.0). The prevalence of ventriculomegaly was 13.0% (95% CI, 5.8 – 22.6). Fifteen out of 252 fetuses were diagnosed with microcephaly (4.9%, 95% CI, 0.9-11.8). The overall incidence of brain cysts was 8.5%. Abnormal cerebellar findings were described in only 5 out of 252 cases of congenital CMV, (2.2%, 95% CI, 0.8-4.4). White matter abnormalities and cortical migration abnormalities had an incidence of 32.8% and 6.5%, respectively. The most frequent brain lesions reported in fetuses with congenital CMV undergoing prenatal MRI evaluation are white matter abnormalities (33%), especially in the temporal lobes. Large prospective studies are needed in order to ascertain the correlation between each of these abnormalities and the long-term neurodevelopmental outcome.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.037 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".