A Comparison of Aprotinin and Lysine Analogues in High-Risk Cardiac Surgery
Bibliographic record
Abstract
BACKGROUND: Antifibrinolytic agents are commonly used during cardiac surgery to minimize bleeding and to reduce exposure to blood products. We sought to determine whether aprotinin was superior to either tranexamic acid or aminocaproic acid in decreasing massive postoperative bleeding and other clinically important consequences. METHODS: In this multicenter, blinded trial, we randomly assigned 2331 high-risk cardiac surgical patients to one of three groups: 781 received aprotinin, 770 received tranexamic acid, and 780 received aminocaproic acid. The primary outcome was massive postoperative bleeding. Secondary outcomes included death from any cause at 30 days. RESULTS: The trial was terminated early because of a higher rate of death in patients receiving aprotinin. A total of 74 patients (9.5%) in the aprotinin group had massive bleeding, as compared with 93 (12.1%) in the tranexamic acid group and 94 (12.1%) in the aminocaproic acid group (relative risk in the aprotinin group for both comparisons, 0.79; 95% confidence interval [CI], 0.59 to 1.05). At 30 days, the rate of death from any cause was 6.0% in the aprotinin group, as compared with 3.9% in the tranexamic acid group (relative risk, 1.55; 95% CI, 0.99 to 2.42) and 4.0% in the aminocaproic acid group (relative risk, 1.52; 95% CI, 0.98 to 2.36). The relative risk of death in the aprotinin group, as compared with that in both groups receiving lysine analogues, was 1.53 (95% CI, 1.06 to 2.22). CONCLUSIONS: Despite the possibility of a modest reduction in the risk of massive bleeding, the strong and consistent negative mortality trend associated with aprotinin, as compared with the lysine analogues, precludes its use in high-risk cardiac surgery. (Current Controlled Trials number, ISRCTN15166455 [controlled-trials.com].).
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".