Agenesis of the corpus callosum: What to tell expecting parents?
Bibliographic record
Abstract
Agenesis of the corpus callosum (ACC) is one of the most common brain malformations, with an incidence estimated to range from 0.5 to 70 in 10,000 among the general population. Prenatal diagnosis is made via ultrasound; however, fetal MRI is useful to confirm or exclude the presence of associated cerebral abnormalities-mostly cortical malformations-that may affect postnatal prognosis. When no additional central nervous system (CNS) or extra CNS anomalies are identified and no genetic cause is found, an isolated ACC is diagnosed. Overall, in cases of ACC, an underlying genetic cause can be identified in up to 12.5% with chromosomal microarray (CMA) and up to 47% with whole exome sequencing (WES). In cases where ACC is the only anomaly detected, the yield of WES is 30%. Postnatal outcomes are variable and depend on whether the condition is isolated or not. In truly isolated ACC, outcomes range from normal in 65% of cases through mild to severe neurodevelopmental impairments in 35% of cases. An interdisciplinary team of medical experts is key in guiding parents toward informed decision-making in pregnancies complicated by ACC. Considering current and expected advancements in genetic testing and imaging technologies in upcoming years, we herein summarize current recommendations for the management and prenatal counseling of expecting parents of fetuses with ACC. Our review pertains primarily to expecting parents of fetuses with complete ACC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".