Apixaban Anti-Xa Level Monitoring in Treatment of Provoked Acute Upper Extremity Deep Vein Thrombosis for Patient on Dialysis: A Case Report
Bibliographic record
Abstract
Background. Patients with end stage renal disease on dialysis are at higher risk of major bleeding and recurrent thrombosis and as such, treatment of acute venous thromboembolism (VTE) is challenging. Ideally, treatment would avoid inpatient admission as for most other patients with acute VTE. DOACs represent the easiest option but there are concerns over bioaccumulation increasing bleeding risk. Despite the absence of a standardized therapeutic range, anti-Xa trough level is measured to monitor potential DOACs bioaccumulation and thus, used for safety surveillance. Methods. We describe a case of a 51 yo female, 36 kg, on chronic hemodialysis with a provoked acute upper extremity deep vein thrombosis. Due to a lack of subcutaneous fat and calciphylaxis we were reluctant to use low molecular weight heparin and warfarin. She was treated with apixaban 2,5 mg twice daily for 6 weeks. Over 4 weeks, the apixaban anti-Xa trough levels were measured on dialysis days 12 hours after the morning dose. Results. The anti-Xa trough levels ranged from 58 to 84 ng/mL, similar to what is expected in patients with normal kidney function. There were no adverse events in the 3 months after anticoagulation initiation. Conclusion. We saw no evidence of bioaccumulation. This indicates a potential role for apixaban low doses in acute venous thromboembolism for patients on dialysis. Disclosures No relevant conflicts of interest to declare. OffLabel Disclosure: The use of Apixaban for treatment of acute venous thromboembolism in patient on dialysis has not been approved.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".