Islandized mucoperiosteal flaps: A versatile technique for closure of a wide palatal cleft
Bibliographic record
Abstract
BACKGROUND: A variety of surgical methods have been described to repair wide cleft palate; they are all challenging to perform and yield consistently good results. The islandized mucoperiosteal flap, the technique described in the present article, is very versatile because it can close palatal defects of any size without undue tension. Moreover, it provides adequate length and mobility of the soft palate with improved speech and feeding functions without fistula formation. METHODS: Between 2005 and 2011, 36 patients with wide cleft palate were operated on using islandized mucoperiosteal flaps. This technique involves dissection of the neurovascular bundle from the mucoperiosteal flaps for approximately 1 cm and dissecting the muscle from the posterior edge of the hard palate with intravelar veloplasty. The flaps subsequently become freely mobile in all directions. It can move medially to close palatal defects of any size without tension. In addition, posterior or backward mobilization lengthens the soft palate and renders it freely mobile. RESULTS: All repairs were successful, with no complications and no patients requiring secondary procedures. All patients regained normal feeding function three weeks postoperatively. All patients showed normal nasal resonance of speech except for two (three and five years of age) who experienced abnormal resonance in the form of open nasality that required regular speech therapy for six months. There was significant improvement and no secondary procedures were required for either. CONCLUSIONS: A technical modification for closure of wide palatal clefts is introduced. The islandized mucoperiosteal flap, which is a very versatile technique, can close cleft palates of any width without tension, lengthens the soft palate and renders it freely mobile for proper speech functions. Using this technique, good speech and feeding function with no complications were achieved.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".