Tranexamic Acid Dosing for Cardiac Surgical Patients With Chronic Renal Dysfunction: A New Dosing Regimen
Bibliographic record
Abstract
BACKGROUND: Tranexamic acid (TXA) is a common antifibrinolytic agent used to minimize bleeding in cardiac surgery. Up to 50% cardiac surgical patients have chronic renal dysfunction (CRD). Optimal dosing of TXA in CRD remains poorly investigated. This is important as TXA is renally eliminated with accumulation in CRD. High TXA doses are associated with postoperative seizures. This study measures plasma TXA concentrations in CRD cardiac surgical patients for pharmacokinetic modeling and dose adjustment recommendations. METHODS: This prospective cohort study enrolled 48 patients with stages 1-5 CRD, classified by Kidney Disease Outcome Quality Initiative. Patients were separated into 2 treatment groups. A "low-risk" group underwent simple aortocoronary bypass or single-valve repair/replacement and received a 50 mg/kg TXA bolus. A "high-risk" group underwent redo, aortic, multiple valve or combination surgery and received the Blood Conservation Using Anti-fibrinolytics Trial dosing regimen (loading dose 30 mg/kg, infusion 16 mg/kg/h with 2 mg/kg in pump prime). Primary outcome identified changes in TXA clearance and distribution volume, which provided the rationale for dose adjustment. Descriptive clinical outcomes assessed postoperative seizures, blood loss, ischemic-thrombotic complications, in-hospital mortality, and length of hospital stay. RESULTS: TXA concentrations were elevated and sustained above the therapeutic threshold for approximately 12 hours in high-risk stages 3-5 groups, in accordance to CRD severity. CONCLUSIONS: Using a pharmacokinetic model, we propose a simple new TXA dosing regimen that optimizes maximal antifibrinolysis and avoids excessive drug dosing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".