Should vitamin K antagonist therapy be started simultaneously with parenteral anticoagulation
Bibliographic record
Abstract
For patients with an acute episode of venous thromboembolism (VTE), the optimal starting time of long-term therapy with vitamin K antagonists (VKA) and how much overlap should occur with heparin are unclear and the current guidelines and practice are not based on high-quality data. The objective of this study was to perform a meta-analysis on the evidence comparing early versus late initiation of VKA on the effectiveness and safety of anticoagulation. We searched for randomized controlled trials in Medline, EMBASE, Cochrane CENTRAL, IPA and ClinicalTrials.gov. Studies were included if they compared early initiation of VKA (within approximately 24 h) and late initiation (>4 days) of the onset of heparin therapy. Data were pooled using the Review Manager 5 software and the quality of evidence was appraised with Grading of Recommendations, Assessment, Development and Evaluation profiler. Five studies were included in the review, with a total of 840 patients. Meta-analysis of recurrence of VTE, death and major bleeding revealed no significant differences between the two treatment regimens. Minor bleeding [RR 0.65, 95% confidence interval (CI) 0.43-0.98] and hospital stay (mean difference 3.92 days, 95% CI -4.57 to -3.28) were reduced in the early VKA group (P < 0.05). The quality of evidence for each outcome except hospital stay was low. Results from this meta-analysis favour the early start of VKA (within 24 h of the initiation of heparin) based on minor bleeding and resource utilization. However, these results should be interpreted with caution, as the quality and quantity of evidence is limited.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| 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".