Improving long-term outcomes in pediatric torcular dural sinus malformations with embolization and anticoagulation: a retrospective review of The Hospital for Sick Children experience
Bibliographic record
Abstract
OBJECTIVE: Torcular dural sinus malformations (tDSMs) are rare pediatric cerebrovascular malformations characterized by giant venous lakes localized to the midline confluence of sinuses. Historical clinical outcomes of patients with these lesions were poor, though better prognoses have been reported in the more recent literature. Long-term outcomes in children with tDSMs are uncertain and require further characterization. The goal of this study was to review a cohort of tDSM patients with an emphasis on long-term outcomes and to describe the treatment strategy. METHODS: This study is a single-center retrospective review of a prospectively maintained data bank including patients referred to and cared for at The Hospital for Sick Children for tDSM from January 1996 to March 2019. Each patient's clinical, radiological, and demographic information, as well as their mother's demographic information, was collected for review. RESULTS: Ten patients with tDSM, with a mean follow-up of 58 months, were included in the study. Diagnoses were made antenatally in 8 patients, and among those cases, 4 families opted for either elective termination (n = 1) or no further care following delivery (n = 3). Of the 6 patients treated, 5 had a favorable long-term neurological outcome, and follow-up imaging demonstrated a decrease or stability in the size of the tDSM over time. Staged embolization was performed in 3 patients, and anticoagulation was utilized in 5 treated patients. CONCLUSIONS: The authors add to a growing body of literature indicating that clinical outcomes in tDSM may not be as poor as initially perceived. Greater awareness of the lesion's natural history and pathophysiology, advancing endovascular techniques, and individualized anticoagulation regimens may lead to continued improvement in outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".