Periodontal Soft Tissue Non–Root Coverage Procedures: A Consensus Report From the AAP Regeneration Workshop
Bibliographic record
Abstract
BACKGROUND: Soft tissue grafting for the purposes of increasing the width of keratinized tissue (KT) is an important aspect of periodontal treatment. A systematic review was analyzed, focusing on non-root coverage tissue grafts. The references were updated to reflect the current literature. METHODS: To formulate the consensus report, group members submitted any new literature related to the topic that met criteria fitting the systematic review, and this information was reviewed for inclusion in this report. A consensus report was developed to summarize the findings from the systematic review and to guide clinicians in their treatment decision-making process. RESULTS: Forty-six articles met the criteria for inclusion in the final analysis, and two articles were added that were used to formulate this consensus report. A list of eight clinically relevant questions was posed, and consensus statements were developed. CONCLUSIONS: The evidence suggests that a minimum amount of KT is not needed to prevent attachment loss (AL) when optimal plaque control is present. However, if plaque control is suboptimal, a minimum of 2 mm of KT is needed. The standard procedure to predictably gain KT is the autogenous gingival graft. There is limited evidence for alternative treatment options. However, additional research may offer promising results in certain clinical scenarios. CLINICAL RECOMMENDATIONS: Before patient treatment, the clinician should evaluate etiology, including the role of inflammation and various types of trauma that contribute to AL. The best outcome procedure (autograft) and alternative options should be reviewed with the patient during appropriate informed consent. Proper assessment of the outcome should be included during supportive periodontal care.
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 | 0.114 | 0.153 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.014 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".