Regenerative surgical treatment of peri‐implantitis using either a collagen membrane or concentrated growth factor: A 12‐month randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Platelet concentration based membranes, as well as collagen membranes in combination with bone substitutes, have demonstrated successful outcomes in regeneration of peri-implant bone defects (PBD). PURPOSE: The aim of this study was to evaluate the clinical and radiographic outcomes of regenerative surgical treatment (RST) of peri-implantitis using a bone substitute combined with two different bioresorbable barrier membranes, either collagen membrane (CM) or concentrated growth factor (CGF), during 12-month follow-up. MATERIALS AND METHODS: Fifty two patients, who had at least one peri-implantitis lesion was treated by using a bone substitute in combination with CGF or CM. After surgical procedures, implants were allowed for submerged healing. Clinical assessments were conducted at baseline, 6 and 12 months postoperatively, while radiographic evaluation was performed at baseline and 12 months. RESULTS: Significant reductions were obtained in the mean gingival index (GI), bleeding on probing (BOP), probing depth (PD), clinical attachment level (CAL) and mucosal recession (MR) values at both 6 and 12 months postoperatively compared to baseline for both treatment procedures (P < 0.05). At 6 months, no statistically significant difference was observed for all clinical parameters between the groups, whereas the mean PD, CAL and vertical defect depth (VDD) values were statistically significant in favor of the CM group at 12 months (P < 0.05). The mean defect fill (DF) in the CM group (1.99 ±0.76) was not statistically significantly different from that observed in the CCF group (1.63 ±1.00) (P = 0.154). CONCLUSIONS: The outcomes of the present study suggest that both regenerative approaches yielded significant improvements in both clinical and radiographic assessments. The procedure using a collagen membrane in combination with a bone substitute showed better results at 12 months in RST 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".