Association of oral anticoagulants with risk of brain haemorrhage expansion compared to no-anticoagulation
Bibliographic record
Abstract
BACKGROUND: The impact of direct oral anticoagulants (DOAC) on haematoma size after intracerebral haemorrhage (ICH) compared to no-anticoagulation is controversial and prospective data are lacking. METHODS: The investigator-initiated, multicentre, prospective RASUNOA-prime study enrolled patients with non-traumatic ICH and atrial fibrillation while on a DOAC, vitamin K antagonist (VKA) or no anticoagulation (non-OAC). Neuroimaging was reviewed centrally blinded to group allocation. Primary endpoint was haematoma expansion (≥ 6.5 ml or ≥ 33%, any new intraventricular blood or an increase in modified Graeb score by ≥ 2 points) between baseline and follow-up scan within 72 h after symptom onset. RESULTS: Of 1,440 patients screened, 951 patients with ICH symptom onset less than 24 h before admission were enrolled. Baseline scans were performed at a median of 2 h (IQR 1-6) after symptom onset. Neurological deficit and median baseline haematoma volumes (11 ml; IQR 4-39) did not differ among 577 DOAC, 251 VKA and 123 non-OAC patients. Haematoma expansion was observed in DOAC patients in 142/356 (39.9, 95%-CI 34.8-45.0%), VKA in 47/155 (30.3, 95-CI 23.1%-37.6%), versus non-OAC in 22/74 (29.7, 19.3-40.1%). Unspecific reversal agents in DOAC-ICH (212/356, 59.6%) did not affect the haematoma expansion rate compared to no-antagonization. CONCLUSION: Baseline haematoma volume and risk of haematoma expansion did not differ statistically significantly in patients with and without DOAC.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".