Correlation between ventriculomegaly on prenatal magnetic resonance imaging and the need for postnatal ventricular shunt placement
Bibliographic record
Abstract
OBJECT: Pediatric neurosurgeons are increasingly called on to provide prognostic data regarding the antenatal diagnosis of ventriculomegaly. This study was designed to determine if there is a correlation between prenatal MR imaging results and the need for ventricular shunt placement during the neonatal period. METHODS: The authors retrospectively reviewed the prenatal MR imaging data of 38 consecutive patients who had been referred for neurosurgical consultation following the diagnosis of ventriculomegaly. The outcome measure was placement of a ventricular shunt. Assessed parameters included prenatal atrial diameter (AD), gestational age at MR imaging, time between imaging studies, presence of concomitant CNS anomalies, laterality of ventriculomegaly, fetal sex, and temporal evolution of ventriculomegaly. Logistic regression analysis was completed with the calculation of appropriate ORs and 95% CIs. RESULTS: Six patients (16%) required shunt placement, all with an AD > or = 20 mm (mean 23.8 mm) at the time of imaging. Eight patients had presented with an AD > or = 20 mm. Atrial diameter was the only presenting feature that correlated with shunt placement (OR 1.58, 95% CI 1.10-2.25, p = 0.01). Logistic regression analysis revealed no statistical correlation between the need for ventricular shunting and gestational age at MR imaging, time between imaging studies, fetal sex, presence of additional CNS anomalies, and laterality of the ventriculomegaly. CONCLUSIONS: When assessed using MR imaging, an AD > or = 20 mm at any gestational age is highly associated with the need for postnatal shunting. Patients with concomitant CNS anomalies did not require shunts at a greater rate than those with isolated ventriculomegaly. Further studies are required to assess the long-term outcome of this patient population.
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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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".