Pre-treatment oral microbiome analysis and salivary Stephan curve kinetics in white spot lesion development in orthodontic patients wearing fixed appliances. A pilot study
Bibliographic record
Abstract
BACKGROUND: White spot lesions (WSLs) are a formidable challenge during orthodontic treatment, affecting patients regardless of oral hygiene. Multifactorial in nature, amongst potential contributors to their development are the microbiome and salivary pH. The aim of our pilot study is to determine if pre-treatment differences in salivary Stephan curve kinetics and salivary microbiome features correlate with WSL development in orthodontic patients with fixed appliances. We hypothesize that non-oral hygiene determined differences in saliva could be predictive of WSL formation in this patient population through analysis of salivary Stephan curve kinetics, and that these differences would further manifest as changes in the oral microbiome. METHODS: In this prospective cohort study, twenty patients with initial simplified oral hygiene index scores of "good" that were planning to undergo orthodontic treatment with self-ligating fixed appliances for at least 12 months were enrolled. At pre-treatment stage, saliva was collected for microbiome analysis, and at 15-minute intervals after a sucrose rinse over 45 min for Stephan curve kinetics. RESULTS: 50% of patients developed a mean 5.7 (SEM: 1.2) WSLs. There were no differences in saliva microbiome species richness, Shannon alpha diversity or beta diversity between the groups. Capnocytophaga sputigena exclusively and Prevotella melaninogenica predominantly were found in WSL patients, while Streptococcus australis was negatively correlated with WSL development. Streptococcus mitis and Streptococcus anginosus were primarily present in healthy patients. There was no evidence to support the primary hypothesis. CONCLUSIONS: While there were no differences in salivary pH or restitution kinetics following a sucrose challenge and no global microbial differences in WSL developers, our data showed change in salivary pH at 5 min associated with an abundance of acid-producing bacteria in saliva. The results suggest salivary pH modulation as a management strategy to inhibit the abundance of caries initiators. Our study may have uncovered the earliest predecessors to WSL/caries development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".