Prevalence and Geographical Variation of Prothrombin G20210A Mutation in Patients with Cerebral Vein Thrombosis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVES: To compare the prevalence of prothrombin G20210A in patients with objectively confirmed cerebral vein or cortical vein thrombosis against healthy controls, and evaluate geographical variations. DESIGN: Systematic review and meta-analysis of case control studies. METHODS: We conducted a systematic review of electronic databases including MEDLINE and EMBASE. The main outcome was the prevalence of prothrombin G20210A in patients with objectively confirmed cerebral vein or cortical vein thrombosis; we also analyzed individual country variations in the prevalence. The random-effects model OR was used as the primary outcome measure. RESULTS: In total 19 studies evaluated 868 cases of cerebral venous thrombosis and 3981 controls. Prothrombin G20210A was found in 103/868 of the patients with cerebral venous thrombosis and 105/3999 of the healthy controls [random effects pooled OR 5.838, 95% CI 3.96 to 8.58; I217.9%]. The prevalence of prothrombin G20210A was significantly elevated in Italian studies (OR 9.69), in Brazilian studies (OR 7.02), and in German studies (OR 3.77), but not in Iranian studies (OR 0.98). CONCLUSION: Prothrombin G20210A is significantly associated with cerebral venous thrombosis when compared to healthy controls, although this association is highly dependent on the country of origin.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.020 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".