Usual On-therapy Ranges of Drug Concentrations in Patients with Atrial Fibrillation Treated with Direct Oral Anticoagulants: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Abstract Although most patients with atrial fibrillation (AF) receiving a direct oral anticoagulant (DOAC) do not require drug concentration measurements, there are situations where such information could be useful. Existing guidance documents provide usual on-therapy ranges for drug concentrations, but these have important limitations. This is a systematic review and meta-analysis of studies reporting trough and peak levels of DOAC regimens approved for stroke prevention in AF. We used random effects models and the quantile estimation method to estimate the median and a usual on-therapy range (10th and 90th percentiles). Of 4,822 unique publications, 53 studies met eligibility (29,266 trough and 12,103 peak levels). Usual on-therapy ranges for trough levels were 38 to 155 and 58 to 206 ng/mL for apixaban 2.5 and 5 mg twice daily; 35 to 138 and 33 to 151 ng/mL for dabigatran 110 and 150 mg twice daily; 8 to 54 and 13 to 66 ng/mL for edoxaban 30 and 60 mg daily; and 16 to 74 and 19 to 72 ng/mL for rivaroxaban 15 and 20 mg daily. The corresponding range for peak levels were 96 to 251 and 132 to 343; 65 to 223 and 76 to 285; 57 to 219 and 127 to 407; 131 to 384, and 169 to 313 ng/mL, respectively. This systematic review and meta-analysis provides updated and more representative usual on-therapy ranges of DOAC levels in patients with AF.
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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 | 0.013 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.007 | 0.009 |
| 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) | 0.003 | 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".