Use of Tranexamic Acid in Aesthetic Surgery: A Retrospective Comparative Study of Outcomes and Complications
Why this work is in the frame
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Bibliographic record
Abstract
Background: Bleeding is a potential complication of aesthetic surgery. Surgeons have adhered to the principle of minimizing blood loss. Tranexamic acid (TXA) is an antifibrinolytic medication capable of reducing bleeding. This study aimed to investigate TXA and its effect on complications and overall outcomes in aesthetic surgery patients. Methods: This retrospective chart review of patients undergoing various aesthetic procedures between 2019 and 2022 was conducted in Riyadh, Saudi Arabia. Preoperative and postoperative hemoglobin levels, blood transfusions, and complications were the primary outcomes. Furthermore, the predictors of giving TXA were studied. Results: In total, 435 patients were included in the study. TXA was administered to 181 patients (41.6%). Significantly higher proportions of patients who received TXA underwent trunk aesthetic surgery ( P < 0.001), and those who received TXA underwent combined procedures more frequently than non-users ( P < 0.001). The mean operative time and length of hospital stay were significantly longer among patients who did not receive TXA ( P < 0.001, and P < 0.001, respectively). Most predictors for using TXA were significantly associated with performing liposuction (OR = 5.5), trunk aesthetic surgery (OR = 4.9), and undergoing combined procedures (OR = 2.7). No significant difference was noted in the rate of complications between the two cohorts. Conclusions: Although our data show improvement in patient outcomes in multiple aspects, the heterogeneity of our cohort makes us unable to draw definite conclusions to recommend the use of TXA in aesthetic surgery. Thus, a randomized controlled trial is necessary to support the findings of this study.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it