A multicentre randomised assessment of the DAWN AC computer-assisted oral anticoagulant dosage program
Bibliographic record
Abstract
Computer-assisted oral anticoagulant dosage is being increasingly used to meet growing demands for oral anticoagulation. The DAWN AC is one of the most widely used computer-dosage programs. Evidence of its value and that of other computer programs has been based previously only on laboratory evidence of "time in target INR range" (TIR) not on clinical safety in practice. A five-year international randomised clinical study of computer assistance with the DAWN AC program compared with manual dosage in 2,631 patients has been performed at 13 centres with established expertise in oral anticoagulation mainly in the EU. Safety assessment have been based on the comparison of bleeding or thrombotic events with DAWN AC compared with manual dosage in a randomised study. Safety of the DAWN AC program has been demonstrated. Clinical events of bleeding and thrombosis were almost identical with the experienced manual dosage group. Therapeutic control improved with DAWN AC to 66.8% from 63.4% TIR. The program failed to provide a dosage recommendation on only 5.7% of occasions. At a group of experienced centres with a special interest in oral anticoagulation, the DAWN AC computer-dosage program proved as safe clinically as manual dosage by experienced medical staff. With DAWN AC, laboratory control was improved, the difference being highly significant. The results should reassure hospitals and community clinics that the DAWN AC program is safe and facilitate greater and longer provision of warfarin treatment where required.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".