Aragonite toothpaste for management of dental calculus: A double‐blinded randomized controlled clinical trial
Bibliographic record
Abstract
Abstract Objectives Aragonite from animal origin such as cuttlefish bone powder is an abrasive with hardness properties ideal for calculus removal. The purpose of this randomized controlled trial was to test the efficacy of a cuttlebone‐derived aragonite toothpaste in removing dental calculus. Materials and Methods Eighty‐one patients who fulfilled the inclusion criteria were blindly and randomly assigned into two study groups. The intervention treatment group (n = 40) received cuttlebone toothpaste (Dr. D‐Tart) and the control group (n = 41) received an off‐the‐shelf commercial toothpaste (Crest). Evaluations were performed before and after scaling and polishing procedures done at 3 months in order to evaluate the toothpaste's ability to remove calculus and to prevent calculus formation. Calculus, stains, plaque, and gingival indices scores, and patient satisfaction surveys were compared at baseline (first visit), 3, and 9 months, using generalized linear models and Wald's χ2 test. Results At the end of the 3‐month period, the intervention group showed a 30% reduction in total calculus compared to the baseline score (p = .0006) and 45% less total calculus compared to the control group (p = .0001). Six months after scaling, the mean calculus score for Crest users was 42% higher than that for Dr. D‐Tart users (p = .0692). There was a significant improvement in the gingival health of cuttlebone toothpaste users at the observed intervals, and both kinds of toothpaste achieved comparable results in terms of plaque and stains removal. Conclusions Aragonite toothpaste can remove calculus, prevent calculus formation, and improve gingival health. Patients are generally satisfied with the performance of the aragonite toothpaste. Clinical significance: Animal‐derived aragonite toothpaste (Dr. D‐Tart) shows promising efficacy in removing calculus, preventing calculus formation, and for the improvement of gingival health. Clinical trial ID: A08‐M35‐16B.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".