Biomimetic hydroxyapatite and caries prevention: a systematic review and meta-analysis.
Bibliographic record
Abstract
Dental caries is still one of the most prevalent diseases worldwide. Research has shown that fluoride has a role in caries prevention. For many reasons there are concerns about young children using fluoride-containing oral care products. Consequently, there is a need to identify effective fluoride-free products. A large body of literature now exists on the use of biomimetic hydroxyapatite (HAP) as an active ingredient in oral care products to combat caries. Aim: To conduct a systematic review of the clinical evidence of the effects of HAP-based fluoride-free oral care products in caries reduction and conduct a meta-analysis of available randomized clinical trials (RCTs). Methods: Using the PICO question "In individuals of all ages (P), do fluoride-free oral care products containing HAP as the anti-caries agent (I), compared to products with fluoride or without caries control products (C), reduce the risk of dental caries (O)?" Ovid MEDLINE (PubMed), Scopus, EMBASE, and Web of Science databases were searched using the following keywords: apatite, hydroxyapatite, caries, dental decay, dentin(e), enamel, toothpaste, dentifrice, mouthwash, gels, biofilm, (dental) plaque, ero(de, ded, sion), (de, re)mineral(ise, ized, ised, ization, isation). Reviews, tooth whitening, tooth sensitivity, and in vitro studies were excluded. PRISMA was used for the search and GRADE was used to assess quality. Clinical trials were subjected to the Cochrane Risk of Bias assessment followed by meta-analysis. Results: 291 studies were retrieved; 22 were suitable for systematic review, 5 were clinical caries trials and 4 were RCTs. A meta-analysis of 3 RCTs was possible showing HAP provided 17% protection against caries. The other 17 trials had simpler proxy outcomes for anticaries effects. Some trials showed non-inferior performance of HAP products compared to those with fluoride. Conclusion: There is good evidence that hydroxyapatite in oral care products in the absence of fluoride effectively reduces caries.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.026 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".