A Cadaveric Study of the Buccal Fat Pad: Implications for Closure of Palatal Fistulae and Donor-Site Morbidity
Bibliographic record
Abstract
BACKGROUND: For the cleft surgeon, palatal fistulae after cleft palate repair remain a difficult problem, with a paucity of local tissue options to aid closure. Small clinical series have described the use of the buccal fat pad flap to repair palatal fistulae; however, there is no literature detailing the anatomical coverage of the flap. This study delineates the anatomy of the buccal fat pad flap to guide surgeons in patient selection and examines the residual buccal fat after flap harvest to provide new information with regard to possible effects on the donor site. METHODS: Buccal fat pad flaps were raised in 30 hemicadavers. The reach of the flap across the midline, anteriorly and posteriorly, was recorded. In 18 hemicadavers, the entire buccal fat pad was then exposed to determine the effects of flap harvest on movement and volume of the residual fat. RESULTS: All buccal fat pad flaps provided coverage from the soft palate to the posterior third of the hard palate and all across the midline. Approximately three-fourths of flaps would cover the mid hard palate. The flap constitutes 36 percent of the total buccal fat pad on average, and a series of retaining ligaments were identified that may prevent overresection. CONCLUSIONS: The buccal fat pad flap is a useful tool for coverage of fistulae in the soft palate to the posterior third of the hard palate. In most cases, it will also reach the middle third; however, it is not suitable for more anterior defects. On average, two-thirds of the buccal fat pad remains within the cheek after flap harvest, which may protect against unwanted alteration in aesthetics.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".