Restrictive versus Liberal Transfusion in Myocardial Infarction — A Patient-Level Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Clinical guidelines have concluded that there are insufficient data to provide recommendations for the hemoglobin threshold for the use of red cell transfusion in patients with acute myocardial infarction (MI) and anemia. After the recent publication of the Myocardial Infarction and Transfusion (MINT) trial, we performed an individual patient-level data meta-analysis to evaluate the effect of restrictive versus liberal blood transfusion strategies. METHODS: We conducted searches in major databases. Eligible trials randomly assigned patients with MI and anemia to either a restrictive (i.e., transfusion threshold of 7-8 g/dl) or liberal (i.e., transfusion threshold of 10 g/dl) red cell transfusion strategy. We used individual patient data from each trial. The primary outcome was a composite of 30-day mortality or MI. RESULTS: We included 4311 patients from four trials. The primary outcome occurred in 334 patients (15.4%) in the restrictive strategy and 296 patients (13.8%) in the liberal strategy (relative risk [RR] 1.13, 95% confidence interval [CI], 0.97 to 1.30). Death at 30 days occurred in 9.3% of patients in the restrictive strategy and in 8.1% of patients in the liberal strategy (RR 1.15, 95% CI, 0.95 to 1.39). Cardiac death at 30 days occurred in 5.5% of patients in the restrictive strategy and in 3.7% of patients in the liberal strategy (RR 1.47, 95% CI, 1.11 to 1.94). Heart failure (RR 0.89, 95% CI, 0.70 to 1.13) was similar in the transfusion strategies. All-cause mortality at 6 months occurred in 20.5% of patients in the restrictive strategy compared with 19.1% of patients in the liberal strategy (hazard ratio 1.08, 95% CI, 1.05 to 1.11). CONCLUSIONS: Pooling individual patient data from four trials did not find a definitive difference in our primary composite outcome of MI or death at 30 days. At 6 months, a restrictive transfusion strategy was associated with increased all-cause mortality. (Partially funded by a grant from the U.S. National Heart, Lung, and Blood Institute [R01HL171977].).
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 | 0.020 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.036 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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".