Efficacy of implantoplasty in management of peri-implantitis: A systematic review
Bibliographic record
Abstract
Aim: Peri-implantitis causes progressive loss of the supporting bony structure around the dental implant. Implantoplasty mechanically removes contaminated threads to achieve smoother implant surface thus reducing the bacterial load enabling fibroblastic growth to stimulate the healing effect. This Systematic review is done to appraise the outcome of implantoplasty on surface quality of Implant (roughness), biocompatibility of implants in peri-implantitis cases. Settings and Design: The Settings of the studies are major online databases like PubMed, Scopus, and Cochrane online library. The design of the current study is systematic review of published qualitative studies. Materials and Method: 37 articles were identified for the present review and systematic electronic literature search was done from August 2022 to January 2023, via PubMed, Scopus, Medline, and The Cochrane Library (Wiley) databases [PRISMA guidelines]. In vitro studies on implantoplasty for peri-implantitis were included for the review. 2 examiners independently selected based on the inclusion criteria and recorded the necessary data. Statistical Analysis Used: Risk of bias assessment tool was evaluated with Newcastle Ottawa scale (NOS) and screened based on Selection, Comparability, and Outcome with the following categories: - maximum of 4, 2 and 4 points respectively. The observations were tabulated and analysed. Results: Among the 8 selected studies, two studies reported no statistical difference between implantoplasty and control, one study proposed carbide burs were better than diamond burs, another study also suggested multilaminar burs were better than diamond and carbide. The Newcastle Ottawa scale (NOS) score for the quality of the included studies ranged from 6 to 8. Two of the studies had score of 6 points, eight had 7 points and one had 8 points. Conclusion: Implantoplasty has been recommended as an efficacious treatment protocol for peri-implantitis that helps to diminish the inflammation and accompanied by a high success rate.
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".