Refractory Dabigatran-Induced Hemorrhage Despite Multiple Idarucizumab Administration and Renal Replacement Therapy
Bibliographic record
Abstract
Purpose: This case report describes a patient with dabigatran accumulation due to acute kidney injury on chronic kidney disease, requiring multiple administration of idarucizumab along with renal replacement therapy because of rebound effect causing numerous episodes of bleeding. Summary: An 86-year-old man on dabigatran etexilate 110 mg twice daily for stroke prevention with atrial fibrillation was admitted to the hospital for bowel obstruction and severe acute kidney injury on chronic kidney disease. The patient had an abnormal coagulation profile and no history of bleeding. Initial laboratory values revealed a hemoglobin concentration of 10.7 g/dL, a platelet count of 115 × 10 3 platelets/μL, an activated partial thromboplastin time of 150.4 seconds, an international normalized ratio of 10.28, a thrombin time greater than 100 seconds and a serum creatinine of 5.54 mg/dL (490 μmol/L). An initial dose of idarucizumab was administered 1 hour prior to surgery to prevent bleeding. Significant bleeding and hemodynamic instability occurred following surgery. Three additional doses of idarucizumab, 2 sessions of intermittent hemodialysis, continuous venovenous hemofiltration and blood products were required to achieve normalization of coagulation parameters and hemodynamic stability due to rebound coagulopathy after each dose of idarucizumab. Conclusion: Acute kidney injury on chronic kidney disease and third-space redistribution could have led to important dabigatran accumulation and favored rebound coagulopathy. Multiple therapeutic approaches may be required in the management of complex dabigatran intoxication.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.003 |
| 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".