Blood transfusion and ischaemic outcomes according to anemia and bleeding in patients with non-ST-segment elevation acute coronary syndromes: Insights from the TAO randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: The benefits and risks of blood transfusion in patients with acute myocardial infarction who are anemic or who experience bleeding are debated. We sought to study the association between blood transfusion and ischemic outcomes according to haemoglobin nadir and bleeding status in patients with NST-elevation myocardial infarction (NSTEMI). METHODS: The TAO trial randomized patients with NSTEMI and coronary angiogram scheduled within 72h to heparin plus eptifibatide versus otamixaban. After exclusion of patients who underwent coronary artery bypass surgery, patients were categorized according to transfusion status considering transfusion as a time-varying covariate. The primary ischemic outcome was the composite of all-cause death or MI within 180 days of randomization. Subgroup analyses were performed according to pre-transfusion hemoglobin nadir and bleeding status. RESULTS: 12,547 patients were enrolled. Among these, blood transfusion was used in 489 (3.9%) patients. Patients who received transfusion had a higher rate of death or MI (29.9% vs. 8.1%, p<0.01). This excess risk persisted after adjustment on GRACE score and nadir of hemoglobin (HR 3.36 95%CI 2.63-4.29 p<0.01). Subgroup analyses showed that blood transfusion was associated with a higher risk in patients without overt bleeding (adjusted HR 6.25 vs. 2.85; p-interaction 0.001) as well as in those with hemoglobin nadir > 9.0 g/dl (HR 4.01; p-interaction<0.0001). CONCLUSION: In patients with NSTEMI, blood transfusion was associated with an overall increased risk of ischaemic events. However, this was mainly driven by patients without overt bleeding and those hemoglobin nadir > 9.0g/dl. This suggests possible harm of transfusion in those groups.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".