Current Knowledge on Factor V Leiden Mutation as a Risk Factor for Recurrent Venous Thromboembolism: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Thrombophilia screening is widely done in clinical practice, and it is claimed that the extent of venous thromboembolism (VTE) recurrence risk in patients with common defects is still not fully understood. Aim: We aimed to summarize data of all observational studies prospectively assessing the association of heterozygous factor V Leiden (FVL) mutation and recurrent VTE in patients with VTE, and to calculate pooled relative risks (RR), overall and in various subgroups. Methods: We searched MEDLINE and EMBASE databases for cohort studies prospectively assessing VTE recurrence in patients with and without FVL mutation (PROSPERO: CRD42021182800). Data were extracted on cohort and study-level. The methodological quality was assessed using the Newcastle-Ottawa Scale (NOS). RR were calculated overall and in subgroups using a random-effects model. Results: From 31 cohorts, 24 studies were finally included summarizing 13,571 patients. Heterozygous FVL mutation was identified in 2,840 individuals (21%). The methodological quality was estimated to be high in 20 studies (83%). The overall RR was 1.46 (95% CI: 1.31, 1.64), consistent across subgroups. Conclusions: Pooling all high-quality epidemiological data, the risk of recurrent VTE was increased by 46% in patients with heterozygous FVL mutation. Against the background of established risk factors, the FVL mutation plays only a marginal role in the risk assessment for recurrent VTE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.027 | 0.010 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".