A Systematic Review on a Variety of Alternate Fluoride Options Effective in Preventing Dental Caries
Bibliographic record
Abstract
Conventional fluoride therapies are effective in preventing dental caries but present limitations, such as esthetic concerns and fluoride sensitivity This has led to the development of alternate agents with comparable or improved preventive potential. To systematically review and evaluate the effectiveness of alternate fluoride-based and fluoride-free interventions in the guidelines. A prevention of dental caries. This review adhered to PRISMA 2020 comprehensive literature search was conducted across five databases and grey literature sources. Studies included randomized controlled trials, in vitro experiments, and systematic reviews without meta-analysis that examined the efficacy of agents, such as "silver diamine fluoride (SDF)," "nano-silver fluoride (NSF)," grape seed extract, hydroxyapatite, casein phosphopeptide-amorphous calcium phosphate (CPP-ACP), probiotics, and bioactive glasses Data were extracted regarding intervention type, mechanism, outcomes, and patient acceptability. Twenty studies met inclusion criteria. SDF was found to be noninferior to conventional sealants, while NSF offered superior esthetic outcomes with better caries arrest. Hydroxyapatite, CPP-ACP, and bioactive glasses demonstrated significant remineralization potential. Natural agents, such as theobromine and grape seed extract, showed antimicrobial and surface hardening benefits. Probiotics effectively reduced cariogenic bacterial load. Alternative caries-preventive strategies, especially NSF, CPP-ACP, and natural agents, demonstrate strong potential. Further long-term clinical trials are needed.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".