Treatment for dental erosion: a systematic review of <i>in vitro</i> studies
Bibliographic record
Abstract
Background Dental erosion is a chemical loss of the mineralized dental tissue caused by exposure to nonbacterial acids. Different treatment protocols have been adopted with the use of fluoride compounds to promote the formation of a layer of mineral precipitation in eroded lesions. Aim This systematic review aimed to evaluate the main treatments for dental erosion. Methodology This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and recorded in the Open Science Framework database (OSF) under DOI 10.17605/OSF.IO/XMFNZ . The searches were conducted in six electronic databases (Pubmed, Embase, Web of Science, Cochrane, Scopus, Lilacs) and two grey literature sources (Google Scholar and OpenGrey). The eligibility criteria included in vitro studies that evaluated eroded teeth under treatment with some topical agent. Risk of bias assessment and qualitative synthesis were performed using the Cochrane collaboration’s tool for assessing risk of bias modified for in vitro studies. Results A total of 522 studies were identified, and only four studies that fulfilled our eligibility criteria were included in this review. Among these studies, three were considered to have a low risk of bias, and one to have a high risk of bias. Two studies evaluated the anti-erosion effect of fluoride toothpaste, and the other two assessed the action of casein phosphopeptide–amorphous calcium phosphate (CPP-ACP) on the surface of human teeth. Among the products analyzed, CPP-ACP was the only one that promoted a significant increase in enamel microhardness and reduced tooth wear. Conclusion Based on the in vitro studies included in this review, there was no anti-erosion effect after using different fluoride toothpaste. However, it should be considered that one of these studies presented a high risk of bias. On the other hand, studies with CPP-ACP showed anti-erosion efficacy when applied before or after erosive wear.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| 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".