Is D-dimer measurement useful in pediatric cerebral sinovenous thrombosis?
Bibliographic record
Abstract
Introduction: Pediatric CSVT diagnosis is dependent on neuroimaging (MRV/CTV). Biomarkers to suspect, quantify and prognosticate CSVT are lacking. D-dimer (DD) assay is useful in adults for diagnosis/prognosis. Objectives: To determine frequency of elevated DD and its correlation with clot burden and outcome in pediatric CSVT. Methodology : Children (29-days-18-years) with CSVT and DD assay from Sept’99-Dec’09 were identified. Patients with DD performed institutional age-specific normative value, ng/mL) and neuroimaging data [high clot burden (>1 sinus with thrombus), hemorrhage, CSVT-propagation, recanalization] were analyzed. Goups were compared by Fisher’s exact/Chi-Square test. Logistic regression was used for outcome prediction. Results: Ninety-three CSVT patients were identified. Sixty had DD. Forty-six (21 males) were included [mean age: 8-yrs, median time (in relation to CSVT-diagnosis) of DD-assay: 4 + 6.2-days]. DD was elevated in 32/46(70%). No significant differences (with respect to age, gender, clinical/radiological features, risk factors, treatment) were found between those with and without elevated DD, except strong trends with respect to high clot burden [97% with, 79% without elevated DD, (p=0.069)] and CSVT-propagation [25% with, 0% without elevated DD, (p=0.0845)]. Logistic regression analysis revealed 55% and 61% increased likelihood of clot propagation and poor neurological outcome respectively per 1000 unit DD increase. Interpretation: D-dimer level is elevated in most children with CSVT and seems to correlate with CSVT burden, propagation and poor clinical outcome. Larger prospective study is warranted.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".