Avoiding Transfusions in Children Undergoing Cardiac Surgery: A Meta-Analysis of Randomized Trials of Aprotinin
Bibliographic record
Abstract
In Brief Aprotinin, a potent antifibrinolytic drug, reduces the proportion of adults who receive blood transfusions during cardiac surgery, although the effect in children remains unclear. We performed a systematic review of the literature to identify all English language, randomized controlled trials of aprotinin involving children undergoing corrective or palliative cardiac surgery with cardiopulmonary bypass. All studies were assessed for methodological quality, and sources of heterogeneity were examined. We measured the effect of aprotinin on the proportion of children transfused, the volume of blood transfused, and the volume of chest tube drainage. Twelve trials enrolling 626 eligible children met the inclusion criteria. Aprotinin reduced the proportion of children who received red blood cell or whole blood transfusions during cardiac surgery by 33% (relative risk = 0.67; 95% confidence interval, 0.51 to 0.89). Aprotinin did not have a significant effect on the volume of blood transfused or on the amount of postoperative chest tube drainage. Most of the studies were of poor methodological quality and predefined transfusion triggers were infrequently used. Overall, aprotinin reduced the proportion of children who received blood transfusion during cardiac surgery with cardiopulmonary bypass. Further high-quality trials with clinically important outcomes may be warranted before aprotinin can be routinely recommended in this population. IMPLICATIONS: In this meta-analysis of randomized controlled trials, aprotinin reduced the proportion of children who received blood transfusions during cardiac surgery. However, the sustained effect of aprotinin on reducing blood loss remains uncertain. Further rigorous clinical trials with clinically important outcomes are needed before aprotinin can be routinely recommended.
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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 | 0.021 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.054 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".