An inverted partially epithelialized connective tissue graft around dental implants: A report of three cases
Bibliographic record
Abstract
In clinical practice, it is common to encounter dental implants with insufficient keratinized mucosa width (KMW) and decreased peri-implant mucosa thickness (MT). Research indicates that such soft-tissue deficiencies can lead to unsatisfactory esthetic results and decreased bone stability over time. This case report presents a variation of standard free gingival graft and connective tissue graft (CTG) techniques, termed the inverted partially epithelialized CTG (IPE-CTG). Three patients (2 males and 1 female) experiencing insufficient attached gingiva and reduced peri-implant tissue volume were effectively treated with the IPE-CTG. This approach involves placing a partially epithelialized graft as an onlay graft on the recipient site, with the epithelialized surface oriented apically and the de-epithelialized surface directed coronally. This technique aims to address KMW and MT deficiencies in a single procedure. All cases treated with the IPE-CTG exhibited stable results over a 12-month period, with notable improvements in both KMW and MT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 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".