Herbal as an Adjunct to Scaling and Root Planning (SRP) in Nonsurgical Periodontitis Treatment in Adult: A Systematic Review of Randomized Controlled Trials
Bibliographic record
Abstract
Background: Periodontitis is an inflammatory disease that affecting people worldwide.The herbal medications might act as adjuvant or to be an alternative therapy in nonsurgical periodontitis treatment in adult.Objective: To summarize the effects of herbal medications as an adjunct to scaling and root planning (SRP) or chlorhexidine compared to the standard of care (SRP alone) in adult periodontitis treatment.Methods: Searches of MEDLINE, EMBASE, CENTRAL, LILACS and ISI Web of Science up to March 2019 were performed to identify randomized controlled trials (RCTs).We used the GRADE approach to rate overall certainty of the evidence by outcome.Results: 30 randomized trials including 1,125 patients proved eligible.Pooled results from five RCTs showed a statistically significant difference in favor of herbal medicine as an adjunct to SRP when compared to SRP alone in reducing probing pocket depth (PPD) (Mean Difference (MD) -0.46, 95% Confidence Interval (CI) -0.67 to -0.26, p < 0.00001; I2 = 38%, p = 0.17, n = 166).Conclusions: Some possible clinically meaningful differences between herbal medicine as an adjunct to SRP and other comparisons exist, but no definitive conclusions can be drawn from these findings.Low-certainty evidence indicates that combination therapy with herbal medicine plus SRP is more effective than SRP alone to reduce PPD in adult with periodontitis.
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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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.006 | 0.006 |
| 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) | 0.005 | 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".