The effects of two baking-soda toothpastes in enhancing mechanical plaque removal and improving gingival health: A 6-month randomized clinical study.
Bibliographic record
Abstract
PURPOSE: To compare the effectiveness in reducing plaque and gingivitis of two fluoride toothpastes containing baking soda (35% and 20%) with a fluoride toothpaste control. METHODS: 319 subjects, who met entry criteria, participated in this single-center, three-cell, double-blind, randomized, parallel-group clinical study. Gingival Index (MGI), Gingival Bleeding Index (GBI), and Plaque Index (PI) were assessed at baseline, and after 6 weeks, 3 and 6 months. RESULTS: All three toothpastes significantly (P< 0.0001) reduced MGI, GBI, and PI versus baseline, and the two baking soda toothpastes significantly (P< 0.0001) reduced MGI, GBI, and PI compared to the fluoride control, at all three time points. After 6 months use, the 35% and 20% baking soda toothpastes had reduced MGI, GBI and PI by 15.0%, 46.9%, and 18.3%, and 9.4%, 25.9%, and 12.4%, respectively, compared to the control. In addition, the 35% baking soda toothpaste had reduced (P≤ 0.0005) MGI, GBI, and PI by 6.2%, 28.4%, and 6.8%, respectively, compared to the 20% baking soda toothpaste. This clinical study showed that brushing with fluoride toothpastes containing baking soda at 35% and 20% reduces plaque, gingival inflammation and bleeding more effectively than regular fluoride toothpaste. Further, it showed that 35% baking soda toothpaste was more effective in reducing these parameters than 20% baking soda toothpaste. CLINICAL SIGNIFICANCE: Fluoride toothpastes containing 20% or more baking soda can provide significant and meaningful gingival health benefits when used regularly as an adjunct to tooth brushing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".