The effect of epsilon aminocaproic acid on blood loss in patients who undergo primary total hip replacement: a pilot study.
Bibliographic record
Abstract
OBJECTIVE: To determine if the use of an antifibrinolytic agent (epsilon aminocaproic acid [EACA]) decreased perioperative and postoperative blood loss in patients who underwent total hip arthroplasty (THA). DESIGN: A prospective, double-blind, randomized, controlled clinical trial. SETTING: A university-affiliated tertiary care hospital with a large joint arthroplasty population. PARTICIPANTS: Fifty-five patients who were scheduled for a primary THA. METHOD: Patients were randomly assigned to 2 groups to receive either EACA or saline placebo perioperatively. Preoperatively, the groups were similar with respect to gender, mean age, mean hemoglobin level, operative time and prosthesis type. OUTCOME MEASURES: Blood loss from the start of surgery until the Hemovac drain was removed, and the transfusion rate and hemoglobin levels. RESULTS: Mean (and standard error) total blood loss for patients receiving EACA was 867 (207) mL and for patients receiving placebo was 1198 (544) mL (p < 0.025). Four patients in the EACA group received 7 units of packed red blood cells and 7 patients in the saline group required 12 units. CONCLUSIONS: Patients receiving the placebo sustained greater total blood loss than EACA patients and were more likely to require blood transfusion. In the current climate of concern over blood transfusions during surgery, EACA administration can reduce blood loss and consequently transfusion and transfusion-related risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".