Minimally Invasive Treatment for Papillae Deficiencies in the Esthetic Zone: A Pilot Study
Bibliographic record
Abstract
BACKGROUND: The presence of papillary deficiencies adjacent to dental implants or teeth presents an esthetic concern for the dental team and patients. PURPOSE: The aim of this pilot project is to evaluate a new method for reducing or eliminating small papillary deficiencies. The use of a commercially available gel was evaluated as a possible method for enhancing deficient papillae. MATERIALS AND METHODS: Eleven patients, seven females and four males, with an average age of 55.8 years (ranging from 25 to 75 years) with 14 treated sites are included in this pilot study. Patients had a minimum of one papillary deficiency in the esthetic zone. Prior to treatment photographs were either taken at a 1:1 ratio or converted to a 1:1 ratio using a commercially available program. A standardization photographic device was not used. After administration of a local anesthetic, a 23-gauge needle was used to inject less than 0.2 mL of a commercially available and Food and Drug Administration-approved gel of hyaluronic acid 2-3 mm apical to the coronal tip of the involved papillae. Patients were seen every three weeks and treatment was repeated up to three times. Patients were followed from 6 to 25 months after initial gel application. A computer program measured changes in pixels between initial and final treatments. A formula was derived to determine percentage change in the negative space between initial and final examinations. RESULTS: Each site was individually evaluated. Three implant sites and one site adjacent to a tooth had 100% improvement between treatment examinations. Seven sites improved from 94 to 97%, three sites improved from 76 to 88%, and one site adjacent to an implant had 57% improvement. CONCLUSION: Results from this pilot study are encouraging and present evidence that small papillary deficiencies between implants and teeth can be enhanced by injection of a hyaluronic gel. Improvements were maintained for a range of 6 to 25 months.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".