Cerebral Vein and Sinus Thrombosis in Isfahan-Iran: A Changing Profile
Bibliographic record
Abstract
OBJECTIVES: This study was performed to investigate the clinical presentation and predisposing factors for cerebral vein and sinus thrombosis (CVST) in Isfahan, Iran. METHODS: Data from the records of all patients with CVST referred to the largest tertiary-care hospital of Isfahan during a five-year period (1997 to 2001) were extracted and reviewed. RESULTS: The number of cases with CVST diagnosed annually was 6, 9, 11, 14 and 15 patients, respectively. Thirteen men and 42 women were diagnosed to have CVST with the mean age of 35.1 +/- 3.8 and 28.7 +/- 1.3 years, respectively. Headache was the most frequent complaint (95%) and 63% of patients had focal neurological symptoms, including seizure (58%). Among possible predisposing factors, oral contraceptive pill was the most prevalent one, which was used by 38.1% of affected women for a period of as short as 1-3 months. Anticardiolipin antibodies were detected in 14% of patients. CONCLUSIONS: It seems that the annual incidence of CVST is increasing in Isfahan, perhaps due to more extensive intake of oral contraceptive pills and usage of more accurate modern diagnostic tools. The use of oral contraceptive pills was the most frequent predisposing factor; infections and postpartum factors were infrequently observed. Despite other reports from the Middle East, Behçet's disease is not a principal risk factor for CVST in Isfahani patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".