A systematic review and meta-analysis of supplemental education in patients treated with oral anticoagulation
Bibliographic record
Abstract
Oral anticoagulants (OACs) are indicated for treatment and prevention of thromboembolic diseases. Supplemental patient education (education) has been proposed to improve outcomes, and this systematic review assesses the effect of education on mortality, thromboembolic events (TEEs) including venous thromboembolism (VTE), and bleeding in patients taking OACs. Randomized controlled trials were included, and 2 authors independently screened articles and assessed risk of bias. In 9 trials (controls, n = 720; intervention group patients, n = 646), 4 assessed critical outcomes of mortality, TEEs (VTE, stroke, and systemic embolism), and bleeding to estimate absolute risk ratios. When comparing education with usual care, in 1000 patients, there may be 12 fewer deaths (95% confidence interval [CI], 19 fewer to 154 more) and 16 fewer bleeding events (95% CI, 34 fewer to 135 more), but this evidence is uncertain; the evidence also suggests 6 fewer VTEs (95% CI, 10 fewer to 16 more) and 8 fewer TEEs (95% CI, 16 fewer to 18 more). The mean difference in time in therapeutic range may be 2.4% higher in the education group compared with usual care (95% CI, 2.79% lower to 7.58% higher). We also found very low certainty of evidence for a large increase in knowledge scores (standardized mean difference, 0.84 standard deviation units higher; 95% CI, 0.51-1.16). Overall, the certainty of evidence was low to very low because of serious risk of bias and serious imprecision. Additional sufficiently powered trials or different approaches to education are required to better assess supplemental education effects on outcomes in patients taking OACs.
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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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".