Surgical approach combining implantoplasty and reconstructive therapy with locally delivered antibiotic in the treatment of peri‐implantitis: A prospective clinical case series
Bibliographic record
Abstract
BACKGROUND: Nonsurgical treatment, resective surgery, reconstructive surgery, or combined approaches have been proposed for the treatment of peri-implantitis, with variable results. PURPOSE: To evaluate the 1-year clinical and radiographic outcomes following combined resective and reconstructive surgical treatment with topical piperacillin/tazobactam antibiotic in the management of peri-implantitis. MATERIAL AND METHODS: Forty-three patients diagnosed with peri-implantitis were included. Surgical treatment consisted of implantoplasty of the supra-crestal component of the defect, the application of a topical antibiotic solution over the implant surface, and subsequent reconstruction of the intra-osseous component of the peri-implant defect. The primary outcome was disease resolution, defined as the absence of bleeding on probing (BoP) and/or suppuration on probing (SoP), a peri-implant pocket probing depth (PPD) ≤5 mm, and no bone loss >0.5 mm 1 year after surgery. Secondary outcomes included changes in BoP, PPD, SoP, and peri-implant marginal bone levels. One implant per patient was included in the analysis. RESULTS: The treatment success rate of the 43 dental implants included in the study was 86% at 1 year after surgery. Mean PPD and BoP decreased from 6.41 ± 2.11 mm and 100% at baseline to 3.19 ± 0.99 mm (p < 0.001) and 14% (p < 0.001) at 1 year, respectively. SoP was significantly reduced from 48.8% at baseline to 0% 1 year after surgery (p < 0.001). Radiographically, a mean defect fill of 2.64 ± 1.59 mm was recorded (p < 0.001). CONCLUSIONS: The combination of a resective and reconstructive surgical approach together with locally delivered antibiotic achieved a high disease resolution rate after 1 year of follow-up and constitutes a viable option for the management of peri-implantitis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".