Effectiveness of Silver Diamine Fluoride for Preventing Occlusal Caries in the Primary Teeth of Preschool Children: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Tooth decay is a significant public health problem globally. The caries-arrest effectiveness of 38% silver diamine fluoride (SDF) has been well documented. However, information on the caries-preventive effect of SDF on primary teeth is insufficient. OBJECTIVE: The aim of this trial is to investigate the effectiveness of semiannual application of 38% SDF and that of 5% sodium fluoride (NaF) varnish when compared with placebo control for preventing occlusal caries in the primary molars of preschool children over 30 months. METHODS: This 3-arm, parallel design, double-blind, randomized controlled trial involves 791 preschool children. Children are randomly allocated to receive 1 of 3 interventions as follows: Group 1, 38% SDF; Group 2, 5% NaF varnish; and Group 3, placebo control (tonic water). The intervention and dental examination will be carried out every 6 months. A parent-administered questionnaire, including the children's demographic background and oral health-related behaviors, has been collected at baseline. Follow-up examinations to detect new caries development will be conducted every 6 months by a masked examiner. Caries development will be diagnosed at the cavitation level. Chi-square tests and logistic regression analyses will be adopted. A 2-level logistic regression analysis will be performed to investigate the effects of the study interventions and other potential confounding factors on the development of occlusal caries. RESULTS: This study was started on September 1, 2020, and the recruitment process ended on September 30, 2021. At present, a total of 791 children are participating in the study. This 30-month clinical trial is expected to be completed in March 2024. CONCLUSIONS: If SDF application is more effective than NaF varnish for preventing caries on occlusal surfaces of primary teeth, it can be a preferred choice for caries prevention in a kindergarten-based program. Results of this trial will provide valuable clinical evidence for the development of oral health strategies and policies on the promotion of child oral health. TRIAL REGISTRATION: HKU Clinical Registry HKUCTR-2844, https://tinyurl.com/bdhz9yuk; ClinicalTrials.gov NCT05084001, https://clinicaltrials.gov/ct2/show/NCT05084001. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35145.
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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 | 0.040 | 0.036 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.073 | 0.011 |
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".