Effects of a Noncompressive Hematoma on Free Flap Viability
Bibliographic record
Abstract
Microvascular free tissue transfer has become an integral component of head and neck reconstructive surgery and historically has a greater than 95% success rate. Hematomas have long been known to cause skin flap necrosis by a variety of mechanisms including direct pressure necrosis, cellular damage secondary to the effects of free radicals, and inflammation. Compression from a hematoma is known to cause free flap compromise. To our knowledge, however, there have been no studies documenting the effect of a noncompressive hematoma surrounding the vascular pedicle on free flap viabiliry. This animal study was designed to assess the effects of a noncompressive hematoma on free flap survival. A right groin cutaneous free flap was created in 32 male Spraque Dawley rats. The rats were then divided into three groups: (1) 10 rats had no fluid added to the anastomotic compartment; (2) 11 rats had 0.5 cc of blood, taken from the femoral artery at the time it was cut, instilled in the anastomotic compartment via the 18-gauge angiocath; and (3) 11 rats had 0.5 cc of pentastarch instilled in the anastomotic compartment via the 18-gauge angiocath. There was 100% free flap survival in all three groups. All vessels examined at the time of sacrifice revealed intact anastomoses and no evidence of luminal clots. This study strongly suggests that in the cutaneous groin free flap model, a perianastomotic noncompressive hematoma has no effect on free flap survival.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".