Prophylactic anticoagulant therapy decreases the incidence of deep vein thrombosis in patients with solid tumors: A systematic review and meta-analysis
Bibliographic record
Abstract
It is not well understood the efficacy and safety of primary deep vein thrombosis (DVT) prophylaxis of anticoagulants in patients with solid tumors. This systematic review and meta-analysis of randomized controlled trials (RCT) determines the relative ratio of primary DVT, survival rate and bleeding events among patients with solid tumors treated with anticoagulants or placebo. Comprehensive literature searches were conducted through the Pubmed, Ovid MEDLINE and EMBASE databases published from January 1st, 1993 to December 31st, 2015. Statistical analysis was performed by RevMan 5.0 software. For DVT events, therisk ratio in 16 trials between the prophylactic and control patients was statistically significant at 0.45 [0.36-0.58]; for major bleeding events, the risk ratio in 18 trials between the prophylactic and control patients was not statistically significant at 1.33 [0.99-1.79], while that in 15 trials with clinically relevant non-major bleeding was statistically significant at 1.83 [1.46-2.30]; the risk ratio for the mortality rate of patients with solid tumors in 16 trials was not statistically significant at 0.97 [0.93-1.02]. Inconclusion, the risk ratio in this meta-analysis showed a significantly reduced incidence of DVT with anticoagulant use. Treatment to patients who had solid tumors with prophylactic anticoagulants enhanced the incidence rate of non-major bleeding but has no significant impact on the incidence rate of major bleeding. No significant differences were found in the mortality outcomes between anticoagulant and non-anticoagulant groups.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.018 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".