Implications of isolated white matter abnormalities on neonatal MRI in congenital CMV infection: a prospective single-centre study
Bibliographic record
Abstract
OBJECTIVE: Investigating the clinical implications of isolated white matter abnormalities on neonatal brain MRI in congenital cytomegalovirus (CMV). DESIGN: Prospective, observational. PATIENTS/INTERVENTIONS: Two paediatric radiologists, blinded to clinical data, independently scored the white matter in 286 newborns with congenital CMV. After assessing interobserver variability, mean score was used to categorise white matter (normal, doubtful or abnormal). Patients with other brain abnormalities were excluded. MAIN OUTCOME MEASURES: Hearing and neuromotor evaluation. RESULTS: Cohen's weighted kappa was 0.79 (95% CI 0.73 to 0.84). White matter was normal in 121 patients, doubtful in 62, abnormal in 28. Median clinical follow-up was 12.0 months (IQR 12.0-27.7 months). Neonatal hearing loss occurred in 4/27 patients (14.8%) with abnormal, 1/118 patients (0.8%) with normal and 1/62 patients (1.6%) with doubtful white matter (p<0.01). Impaired cognitive development was seen in 3/27 patients (11.1%) with abnormal, 3/114 patients (2.6%) with normal and 1/59 patients (1.7%) with doubtful white matter (p=0.104). Alberta Infant Motor Scale (AIMS) was below P75 in 21/26 patients (80.8%) with abnormal, 73/114 patients (64.0%) with normal and 36/57 patients (63.2%) with doubtful white matter (p=0.231). In a subgroup of patients with minimal clinical follow-up of 18 months, AIMS score was below P75 in 10/13 patients (76.9%) with abnormal, 13/34 patients (38.2%) with normal and 7/20 patients (35.0%) with doubtful white matter (p<0.05). CONCLUSIONS: Abnormal white matter was associated with neonatal hearing loss and mild, lower motor scores. A tendency towards impaired cognitive development was seen. Patients with doubtful white matter did not show worse clinical 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".