Bibliographic record
Abstract
Bleeding is the main complication of oral anticoagulant (OAC) therapy, with major bleeds occurring in about 2% to 4% of OAC-treated patients per year. Although direct oral anticoagulants (DOACs) reduce the risk of major, fatal, and intracranial hemorrhage, major DOAC-related bleeding is associated with substantial morbidity and mortality, with case-fatality rates of 8% to 15% reported. Specific reversal agents for dabigatran (idarucizumab) and factor Xa inhibitors (andexanet) correct laboratory indices of anticoagulant effect. Clinical studies suggest that the majority of patients receiving these agents for DOAC-associated major bleeds experience clinical hemostasis. However, uncertainty remains regarding the incremental benefit of these agents and prothrombin complex concentrates over supportive measures alone, based on cohort studies that lacked control groups. Similar methodologic limitations preclude firm conclusions regarding the harms associated with use of these agents. Importantly, patients with DOAC-related major bleeding have substantial short-term risks of thrombosis and mortality, emphasizing the need for individualized patient assessment and protocolized bleed management strategies that include assessment of candidacy for safe resumption of OACs. With expanding indications and increasing prevalence of DOAC-eligible patients, bleeding complications and their management represent an ever-greater major health problem.
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 | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".