Measuring Direct Oral Anticoagulant ( <scp>DOAC</scp> ) Levels: Applications, Limitations, and Future Directions
Bibliographic record
Abstract
INTRODUCTION: There are important challenges with the measurement and interpretation of direct oral anticoagulant (DOAC) anticoagulant effect including a lack of therapeutic ranges, inaccuracy of routinely available coagulation assays, lack of established thresholds for clinically significant effect, and uncertainty about how to apply the results to patient care. OBJECTIVE: In this narrative review, we provide a practical approach to DOAC measurement in clinical practice. METHODS: By summarizing the literature and using illustrative cases, we highlight key principles of commonly available tests, outline potential indications for measuring DOAC drug levels, and provide guidance on interpreting results to inform management decisions. CONCLUSION: While DOACs do not require routine monitoring of anticoagulant effect, assessment of plasma DOAC concentration may be helpful in select emergency and non-emergency clinical scenarios.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".