Poor outcomes after dabigatran-associated intracranial hemorrhage despite idarucizumab reversal
Bibliographic record
Abstract
Intracranial hemorrhage (ICH) is the most deadly bleeding complication associated with anticoagulation. The efficacy of idarucizumab in treating dabigatran-associated ICH in the real world is uncertain. We sought to assess patient outcomes in this sick population. This was a 2-year prospective observational study of functional neurologic status in patients who received idarucizumab following dabigatran-associated ICH across three tertiary Canadian hospitals. The primary outcome was disability on the modified Rankin scale thirty days after antidote administration. Five patients received idarucizumab for dabigatran-associated ICH. The median time to idarucizumab administration was 43 minutes (range: 2–163 minutes). Four patients were dead at 30 days. The fifth patient was in a minimally conscious state with hemiparesis requiring full nursing care. Three patients were transitioned to palliative care based on their advanced directives and dismal prognosis as determined by the treating team. High quality care should not include idarucizumab when it is unlikely to achieve patients’ previously stated goals of care. However, rapid administration of this expensive antidote is often necessary when information is incomplete.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".