Thrombosed Fetal Dural Sinus Malformation: A Case Report
Bibliographic record
Abstract
Background: Fetal dural venous sinus thrombosis is an uncommon disorder in which a blood clot forms in the developing fetus's dural venous sinuses. A detailed ultrasound examination, including neurosonography, and color Doppler are usually used to identify it, and fetal brain magnetic resonance imaging (MRI) is used to confirm the diagnosis. Although few case reports exist, the incidence of fetal occurrence remains unknown. Case Description: A 25-year-old woman, primigravida, with no comorbidities at 20 weeks and 1 day, underwent a detailed ultrasound followed by MRI. The imaging revealed a triangular extra-axial expansile lesion measuring 1.6cm AP × 3 craniocauded × 2.6cm transverse diameter. - The lesion was located at the torcula, at the confluence of the transverse sinuses, extending towards the posterior aspect of the left transverse sinus. This extension caused flattening of the posterior portion of the cisterna magna and the left posterior aspect of the cerebellum. The size of the intracranial mass increased. Fetal and parental investigations failed to find any underlying cause. The patient had a spontaneous vaginal birth at 38 weeks. A postnatal diagnosis of thrombosis in the sinus was confirmed by MRI and venography. No brain damage or hydrocephalus was noted, and the neurological outcome was normal at 9 months of age. Conclusion: Fetal intracranial thrombosis can result from dural sinus abnormalities. When dural sinus malformation (DSM) is detected in prenatal imaging, timely fetal MRI is recommended to help diagnose dural sinus abnormalities, identify intracranial complications, and determine perinatal plan and management options.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".