Anticoagulant Related Nephropathy Induced by Dabigatran
Bibliographic record
Abstract
We describe a case of biopsy-proven dabigatran related nephropathy in a patient without underlying IgA nephropathy. To date, dabigatran related nephropathy was only reported in patients with concurrent or undiagnosed IgA nephropathy, suggesting that it may predispose patients to dabigatran associated injury. The patient is an 81-year-old woman with multiple medical comorbidities, including nonvalvular atrial fibrillation, who was anticoagulated with dabigatran. She presented to hospital with acute kidney injury in the setting of volume overload. Her estimated glomerular filtration rate decreased from a baseline of 57 mL/min/1.73 m2 to 4 mL/min/1.73 m2, necessitating hemodialysis. Renal ultrasound findings, fractional excretion of sodium, and urinalysis suggested acute kidney injury. Renal biopsy showed acute tubular injury, tubular red blood cell casts, and an absence of active glomerulonephritis, similar to the pathological findings of warfarin related nephropathy. A diagnosis of anticoagulant related nephropathy secondary to dabigatran was therefore established. This case demonstrates that dabigatran, like warfarin, may increase tubular bleeding risk in patients, irrespective of underlying kidney or glomerular disease.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".