Dabigatran-Induced Acute Hepatitis
Bibliographic record
Abstract
In the March of 2010, a 71-year-old man with a history of chronic atrial fibrillation presented to our institution with a 2-week history of progressive painless icterus, fatigue, and anorexia. He had been initiated on off-label dabigatran for stroke prevention 1 month prior to his hospital admission. Dabigatran was discontinued at the time of admission to hospital. There had been no other recent change to medications or exposure to hepatoxins. He had no premorbid history of hepatic disease. On examination, he had prominent scleral and dermal icterus in the absence of general stigmata of chronic hepatic disease. There was no asterixis. The abdomen was nontender with no palpable masses or visceromegaly. Biochemical investigations during admission demonstrated an aspartate aminotransferase of 667 IU/L (normal 5 times the upper limit of normal). There were no cases of significant hepatic dysfunction or associated morbidity or mortality. Reviewing the Health Canada database on dabigatran, there have been 5 cases of elevated liver enzymes that may have been associated with dabigatran use. Given this information, our case is important in that it identifies a patient who presented with clinically severe hepatic dysfunction that onsets with dabigatran use, in the absence of another identifiable cause and that resolved with only withdrawal of dabigatran. Although not meeting all criteria for Hy’s Law of drug-induced liver injury, the relationship between drug and side effect seems quite distinct. As such, it points to the need for ongoing monitoring of patients receiving this drug for rare cases of drug-induced hepatic dysfunction, especially in patients on other potentially hepatotoxic medications.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".