Abstract TMP95: Cerebral Sinovenous Thrombosis In Preterm Infants
Bibliographic record
Abstract
Introduction: Neonatal cerebral sinovenous thrombosis (CSVT) can lead to brain injury and long-term neurodevelopmental impairments. Previous studies of neonatal CSVT have primarily focused on term infants, and studies of preterm infants are lacking. In this study, we examined the clinical and radiological features, treatment and outcome of CSVT in preterm infants. Methods: This was a retrospective, consecutive cohort study of preterm infants (gestational age <37 weeks) with radiologically confirmed CSVT. All MRI/MRV and CT/CTV scans were re-reviewed to study thrombus characteristics and the pattern of brain injury. Clinical and radiological data were analysed using descriptive statistics, ANOVA and chi-square tests. Outcome was assessed by the validated Pediatric Stroke Outcome Measure (PSOM). Results: A total of 26 preterm infants with CSVT were included. Of these, 65% were late preterm, 27% very preterm and 8% extreme preterm. Most (73%) were symptomatic at presentation with seizures or abnormal exam. Transverse (85%) and superior sagittal (42%) sinus were most common sites of thrombosis. Parenchymal brain injury was predominantly periventricular (35%) and deep white matter (31%) in location. Intraventricular hemorrhage occurred in 46%. Most infants (69%) were treated with anticoagulation. None of the treated infants had hemorrhagic complications. Outcome at follow-up ranged from no impairment (39%), mild impairment (19%) and severe impairment (19%). Conclusions: Preterm infants with CSVT are often symptomatic and have white matter brain lesions at presentation. Anticoagulation treatment of preterm CSVT in this small cohort appeared to be safe. Further larger studies and treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".