Adjunctive use of metronidazole‐minocycline ointment in the nonsurgical treatment of peri‐implantitis: A multicenter randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Clinical benefits of local antibiotics as an adjunct to nonsurgical treatment of peri-implantitis have been widely reported, but most studies evaluated incipient peri-implantitis lesions, and showed incomplete treatment success rates. PURPOSE: To assess the clinical and microbiological outcomes of administering metronidazole in combination with minocycline as a local adjunct to the nonsurgical treatment of peri-implantitis. MATERIALS AND METHODS: One hundred and eighteen subjects with peri-implantitis were recruited in a four-center, three-arm, and 12-week randomized controlled trial. Subjects were randomly assigned to receive one of the following treatments: (a) MM-mechanical debridement + metronidazole-minocycline ointment, (b) MC-mechanical debridement + minocycline ointment, (c) NST-mechanical debridement only. RESULTS: Except for four subjects who was excluded during the trial, a total of 114 patients with 114 implants (one implant per each patient) finally completed the trial and were included in the analyses. Multivariate logistic regression analysis revealed that the treatment success rates (absence of bleeding or suppuration on probing, and sites showing pocket probing depth [PPD] ≥5 mm) on at 12 weeks were higher in MM-group patients (31.6%) and MC-group patients (20.5%) compared to NST-group patients (2.7%; p = 0.011 and 0.040, respectively). Subjects with deepest PPD ≥8 mm showed a significant difference in the PPD reduction between MM and MC groups at week 4 (p = 0.025) and week 12 (p = 0.047). Detection ratio of Tannerella forsythia was significantly lower for MM group than MC group (p = 0.038). CONCLUSIONS: Additive use of either MM or MC results in significantly higher treatment success rates compared to sole mechanical debridement in nonsurgical treatment of peri-implantitis. Moreover, MM contributes to a significantly greater reduction in the PPD compared to MC in deep pockets (cris.nih.go.kr KCT0004557).
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".