Apixaban Pharmacokinetics at Steady State in Hemodialysis Patients
Bibliographic record
Abstract
It is unclear whether warfarin is protective or harmful in patients with ESRD and atrial fibrillation. This state of equipoise raises the question of whether alternative anticoagulants may have a therapeutic role. We aimed to determine apixaban pharmacokinetics at steady state in patients on hemodialysis. Seven patients received apixaban 2.5 mg twice daily for 8 days. Blood samples were collected before and after apixaban administration on days 1 and 8 (nondialysis days). Significant accumulation of the drug was observed between days 1 and 8 with the 2.5-mg dose. The area under the concentration-time curve from 0 to 24 hours increased from 628 to 2054 ng h/ml ( P <0.001). Trough levels increased from 45 to 132 ng/ml ( P <0.001). On day 9, after a 2.5-mg dose, apixaban levels were monitored hourly during dialysis. Only 4% of the drug was removed. After a 5-day washout period, five patients received 5 mg apixaban twice daily for 8 days. The area under the concentration-time curve further increased to 6045 ng h/ml ( P =0.03), and trough levels increased to 218 ng/ml ( P =0.03), above the 90th percentile for the 5-mg dose in patients with preserved renal function. Apixaban 2.5 mg twice daily in patients on hemodialysis resulted in drug exposure comparable with that of the standard dose (5 mg twice daily) in patients with preserved renal function and might be a reasonable alternative to warfarin for stroke prevention in patients on dialysis. Apixaban 5 mg twice daily led to supratherapeutic levels in patients on hemodialysis and should be avoided.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".