The safety of oral anticoagulants registry (SOAR): A national, ED-based study of the evaluation and management of bleeding and bleeding concerns due to the use of oral anticoagulants
Bibliographic record
Abstract
OBJECTIVE: The Safety of Oral Anticoagulants Registry (SOAR) was designed to describe the evaluation and management of patients with oral anticoagulant (OAC)-related major bleeding or bleeding concerns who present to the emergency department (ED) with acute illness or injury. Patients in the ED are increasingly taking anticoagulants, which can cause bleeding-related complications as well as impact the acute management of related or unrelated clinical issues that prompt presentation. Modifications of emergency evaluation and management due to anticoagulation have not previously been studied. METHODS: This was a multicenter observational in-hospital study of patients who were judged to be experiencing an active OAC effect and had (a) an obvious bleeding event or (b) were deemed at risk for serious bleeding spontaneously, after injury, or during an indicated invasive procedure. Diagnostic testing, therapies employed, and clinical outcomes were collected. RESULTS: in 49.4%. The most common sites of AH were gastrointestinal (51.0%) and intracranial (26.8%). In warfarin-treated patients, the mean (IQR) presenting INR was 3.1 (2.2, 4.8) in AH patients and 3.9 (2.4, 7.2) in BC patients. Three-fifths of SOAR patients were treated with factor repletion or specific reversal agents, and those patients had a longer length of stay. In addition, seven (0.76%) of the treated patients experienced an in-hospital thrombotic complication; two of these seven died on the index admission, both of fatal pulmonary embolism. Vitamin K was used and dosed inconsistently in both warfarin and NOAC cohorts. CONCLUSION: Care of anticoagulated patients in the acute care setting is inconsistent, reflecting the diversity of presentation. As the prevalence of OAC use increases with the aging of the US population, further study and targeted educational efforts are needed to drive more evidence-based care of these patients.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".