About Dosage Schemes and Safety of Tranexamic Acid in Cardiac Surgery
Bibliographic record
Abstract
In Reply:—We appreciate your interest in our work and would like to take this opportunity to reply to your comments. First, we would like to apologize for misquoting your tranexamic acid (TA) administration regimen. However, we think that the principal behind the administration of a loading dose remains the same (1 g of TA over 20 min).Regarding the criticism with respect to validity of increased TA dosage for patients undergoing complex cardiac surgery, we would like to emphasize that our previous studies (J Thorac Cardiovasc Surg 1995; 110:835–42) showed that higher TA dose regimens were more effective in reducing postoperative bleeding compared to a lower single-dose regimen.With respect to safety aspects of TA, we must admit that we have never claimed that the use of any antifibrinolytics during cardiac surgery is a safe practice in the face of circulatory arrest. All information in the literature about vascular thrombosis after the use of antifibrinolytics in cardiac surgery is anecdotal. We have recently reviewed stroke rates (as an indicator of vascular thrombosis) in our prospectively collected database of 18,000 primary coronary artery bypass graft patients with respect to utilization of TA. Stroke rates of 1.2–1.4% were similar between the two groups of patients, regardless of TA assignment. Furthermore, we have conducted a prospective randomized placebo controlled trial that demonstrated that there was no difference in early coronary graft patency between high-dose TA and placebo 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 | 0.010 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.025 | 0.025 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".