Periodontal Soft Tissue Non–Root Coverage Procedures: A Systematic Review From the AAP Regeneration Workshop
Bibliographic record
Abstract
BACKGROUND: Gingival augmentation procedures around natural teeth and dental implants are performed to facilitate plaque control, to improve patient comfort, to prevent future recession, and in conjunction with restorative, orthodontic, or prosthetic dentistry. The aim of this study is to answer the most common questions related to this treatment modality based on the most relevant and current knowledge in the field. METHODS: Two reviewers worked to answer the five most common and clinically relevant questions with supporting literature to understand the role of gingiva around teeth. 1) What circumstances require an increased zone of keratinized tissue (KT), or is KT important? 2) What is the ideal thickness of an autogenous gingival graft? Is a thick autogenous gingival graft more effective than a thin autogenous gingival graft? 3) What are the alternatives to autogenous gingival grafting to increase the zone of attached gingiva? 4) Does orthodontic intervention affect soft tissue health and dimensions? 5) What is the patient-reported patient outcome for minimal KT compared with that for an enhanced zone of KT? An extensive literature search was performed using PubMed, the Cochrane Oral Health Group Specialized Trials Registry (the Cochrane Library), and the most respected journals in the field. RESULTS: Although gingival augmentation procedures were first introduced in 1960s, there have not been in-depth comparative studies examining the five questions that have been proposed by the authors. Lack of relevant systematic reviews and randomized clinical trials (RCTs) on this topic do not allow authors to answer those questions with a strong level of evidence. However, the following can be recommended after reviewing case reports and case series on these topics. 1) There is enough clinical evidence to support maintaining an adequate band of gingiva for intracrevicular margin restoration. 2) Thick grafts do not appear to result in better clinical outcomes than thin grafts. Thick grafts are likely to result in more primary contraction, whereas thin grafts tend to be prone to secondary contraction. 3) Viable alternative treatment modalities are currently available that are capable of providing KT augmentation without the need for palatal donor tissue. 4) Appropriately applied orthodontic forces do not cause permanent damage to a healthy periodontium. The probability of recession during tooth movement in thin biotype is high to justify gingival augmentation when the dimension of gingiva is inadequate. In addition, cases in which there will be a facial tooth movement outside of the alveolar process need to be considered for a gingival augmentation procedure. 5) Although the articles that have been published on this topic did not consider patient-reported outcomes and esthetics as part of the overall treatment success assessment, patients who have received alternative treatment modalities that did not depend on palatal tissue harvesting appear to have reported more satisfaction and less discomfort after treatment. CONCLUSIONS: Autogenous gingival grafts are still considered to be the "gold standard" procedure with unmatched success rates and clinical success when gingival augmentation procedures are required. However, tissue-engineered materials may offer viable options to palatal tissue harvesting for gingival augmentation. KT augmentation may prevent the development and progression of gingival recession, especially when restorative margins may interact with the periodontium and/or orthodontic treatment is indicated. Patient-reported outcomes should be considered for future studies on this topic. Additional RCTs and systematic reviews are needed to support these conclusions.
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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 | 0.009 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".