Relationship of Activated Partial Thromboplastin Time to Coronary Events and Bleeding in Patients With Acute Coronary Syndromes Who Receive Heparin
Bibliographic record
Abstract
BACKGROUND: Antithrombotic therapy with intravenous heparin in conjunction with aspirin reduces negative cardiovascular (CV) outcomes in patients with acute coronary syndromes. The need for a therapeutic range with the activated partial thromboplastin time (APTT) has not been validated in patients with arterial thrombosis who receive heparin. Therefore, it is unclear whether there is an association between recurrent CV events and low APTT values and between bleeding and high APTT values. METHODS AND RESULTS: We examined the relationship between the APTT and recurrent cardiovascular events and bleeding among 5058 patients with an acute coronary syndrome without ST elevation who received intravenous heparin in the OASIS-2 trial. The increase in relative risk of recurrent CV events was 1.54 (95% CI 1.10 to 2.15; P=0.01) among patients with APTT values <60 seconds compared with patients with APTT values > or =60 seconds. When patients had persistently subtherapeutic APTT values for more than 48 hours, the increase in relative risk of a recurrent CV event was 1.84 (95% CI 1.25 to 2.70). Higher APTT values were associated with bleeding; for every 10-second increase in the APTT, the probability of major bleeding was increased by 7% (95% CI 3% to 11%; P=0.0004). CONCLUSIONS: In patients with acute coronary syndromes without ST elevation who are treated with intravenous heparin, our findings justify regular APTT monitoring to minimize recurrent ischemic events and bleeding.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".