Treatment of Gingival Fenestration With a Double Pedicle Flap Approach and Dehydrated Amnion–Chorion Membrane: A Case Report
Bibliographic record
Abstract
INTRODUCTION: Although gingival fenestrations (GFs) occur with relative infrequency, their actual incidence is thought to be much higher. Furthermore, if left untreated, these mucogingival defects can lead to unfavorable sequelae which can compromise the esthetics and stability of the teeth affected. Most GFs require surgical treatment for closure. Previously reported modalities of treatment include connective tissue grafting, acellular dermal matrix allograft, and pedicle flap approaches. This case demonstrates the first documented use of a dehydrated amnion-chorion membrane (dHACM) to treat GF. CASE PRESENTATION: A surgical approach involving a double pedicle flap and dHACM with 15 months follow-up is described. Following gentle cleansing of the defect and careful split-thickness elevation of a double pedicle flap, the area of exposure fenestration was covered with dHACM. The overlying flap was then closed carefully to completely cover the dHACM. The case presented shows a successful clinical outcome as characterized by successful closure of the fenestration defect with nice tissue maturation. CONCLUSION: The technique described in this case report demonstrates that GFs can be successfully treated with a periodontal plastic surgical approach using dHACM with minimal patient discomfort.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".