Minimizing Blood Loss in Burn Surgery
Bibliographic record
Abstract
BACKGROUND: Significant blood loss continues to plague early tangential excision of the burn wound. Although various techniques to reduce intraoperative blood loss have been described, there is an absence of uniformity and consistency in their application. Furthermore, it is unclear whether these techniques compromise intraoperative tissue assessment and wound outcome. The purpose of this study was to evaluate the effects of a comprehensive intraoperative blood conservation strategy on blood loss, transfusion requirements, and wound outcome in burn surgery. METHODS: An intraoperative blood conservation strategy (CONSV) that included donor site and burn wound adrenaline tumescence, donor site and excised wound topical adrenaline, and limb tourniquets was prospectively evaluated and compared with a historical control group (HIST) where only topical adrenaline and thrombin were applied to donor sites and excised wounds. RESULTS: Estimated blood loss was reduced from 211 +/- 166 mL per percentage body surface area excised and grafted in the HIST group to 123 +/- 106 mL in the CONSV group (p = 0.02). Similarly, the intraoperative transfusion requirement in the HIST group was reduced from 3.3 +/- 3.1 units per case to 0.1 +/- 0.3 units per case in the CONSV group (p < 0.001). There was no compromise in wound outcome in the CONSV group, which had a mean skin graft take rate of 96 +/- 4.2%. CONCLUSION: The application of a strict and comprehensive intraoperative blood conservation strategy during burn excision and grafting resulted in a profound reduction in blood loss and transfusion requirements, without compromising wound outcome.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".