B.2 Time from symptom onset and number of health care encounters prior to diagnosis of cerebral venous thrombosis
Bibliographic record
Abstract
Background: Cerebral venous thrombosis (CVT)most commonly affects younger women. Diagnosis may be delayed due to its distinct presentation and demographic profile compared to other stroke types. Methods: We examined delays to diagnosis of CVT in the SECRET randomized trial and TOP-SECRET parallel registry. Adults diagnosed with symptomatic CVT within <14 days were included. We examined time to diagnosis and number of health care encounters prior to diagnosis and associations with demographics, clinical and radiologic features and functional and patient-reported outcomes (PROMS) at days 180&365. Results: Of 103 participants, 68.9% were female; median age was 45 (IQR 31.0-61.0). Median time from symptom onset to diagnosis was 4 (1-8) days. Diagnosis on first presentation to medical attention was made in 60.2%. The difference in time to diagnosis for single versus multiple presentations was on the order of days (3[1-7] vs. 5[2-11.75], p=0.16). Women were likelier to have multiple presentations (OR 2.53; 95% CI1.00-6.39; p=0.05) and longer median times to diagnosis (5[2-8]days vs. 2[1-4.5] days; p=0.005). However, this was not associated with absolute or change in functional, or any patient reported, outcome measures (PROMs) at days 180&365. Conclusions: Diagnosis of CVT was commonly delayed; women were likelier to have multiple presentations. We found no association between delayed diagnosis and 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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".