Effects of Minocycline Combined with Tinidazole for Treatment of Chronic Periodontitis
Bibliographic record
Abstract
Purpose: To investigate the therapeutic effects of minocycline combined with tinidazole in the treatment of chronic periodontitis (CP). Methods: Seventy-three CP patients treated May 2018–December 2019 at Yuyao People’s Hospital (Yuyao, China) were enrolled in this study: 34 were treated with minocycline alone (control group; CG) and 39 were treated with a combination of minocycline and tinidazole (observation group; OG). Both groups were treated continuously for four weeks and plaque index (PLI), bleeding index (BI), periodontal pocket depth (PD), periodontal attachment level (PAL) and alveolar bone height were compared before and after treatment. Pain was evaluated using the visual analogue scale (VAS). Levels of TNF-α and IL-6 before and after treatment were determined using an enzyme-linked immunosorbent assay. Adverse reactions were compared. Results: In each group, PLI, BI, PD, PAL and alveolar bone height were lower after treatment (P<0.05), and those in OG were lower than those in CG (P<0.05). TNF-α and IL-6 levels in both groups were lower after treatment (P<0.05), and the levels in serum of the OG were lower than those of the CG (P<0.05). After treatment, the VAS in OG was lower than that of CG (P<0.05). There was no significant difference in adverse reactions between groups (P>0.05). Conclusion: Minocycline combined with tinidazole was more effective in treating CP than minocycline alone. This drug combination improved the periodontal indexes and inflammatory reaction of CP and relieved their pain. No significant difference in adverse reactions was seen.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".