Abstract WP359: Incidence and Outcome of Direct Oral Anticoagulant-related Intracranial Bleeding
Bibliographic record
Abstract
Background: In recent years, direct oral anticoagulants (DOAC) have been approved and included in guidelines as alternatives to warfarin for the prevention of stroke in patients with non-valvular atrial fibrillation, in part due to because of better safety profile. Prior to the introduction of DOACs, studies showed that anticoagulation with warfarin carries high risk of bleeding. The goal of this study is to examine the incidence of DOAC- related intracranial bleeding (ICB) in a single center retrospective registry of patients admitted with bleeding events. Methods: This is a single Centre observational/descriptive study. We identified consecutive patients presenting to a tertiary care stroke center in Ottawa, Canada between Oct 2010-Feb2015 with any bleeding event using ICD-10 criteria. We included patients taking DOACs at the time of admission, and abstracted demographic, clinical, laboratory and outcome data from the medical record. Results: From a total of 9291 patient presenting with hemorrhage, 100 patients were confirmed to be taking DOACs. Twenty two (22%) patients had ICB (mean age 83years), of whom 6 (27%) were taking Aspirin at time of bleeding. There were 4 intraparenchymal hemorrhages (IPH); (3 spontaneous and 1 traumatic) and the remaining 18 were traumatic SAH and SDH. All patients with ICB were on Dabigatran except one which was on Rivaroxaban. Five of them required reversal agents; 2 received PCC and 3 both PCC and activated PCC. Mean length of stay was 14 days and 12 were discharged to home, 3 to rehabilitation facility, 3 to long term care facility and 4 died. All 4 patients with IPH either died or discharged to long-term care Conclusion: In this descriptive retrospective study, spontaneous DOAC-related IPH was rare and outcomes following traumatic DOAC-related ICB appear better than spontaneous IPH
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".