Dental Caries Status in Postmenopausal Women: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background. Dental caries is one of the most common oral infections observed worldwide. It is defined as a multifactorial dynamic disease-causing mineral loss of dental hard tissue, which is identified by the caries lesion. Treatment of caries lesion involves filling the cavity or removing the damaged tooth. Then, decayed, missing, and filled teeth (DMFT) index is the simplest and most commonly used index to assess the dental caries status. Salivary glands are estrogen dependent and, after menopause, the changes in salivary flow and saliva consistency produce xerostomia, hyposiale or dryness, common findings among postmenopausal women. Since saliva plays a fundamental role in caries prevention, the postmenopausal decline in salivary secretion may contribute to increased caries incidence. The aim of this systematic review and meta-analysis was to answer the following PICO question: In adult women (P), does the presence of menopause (I), compared to its absence (C), influence dental caries status, assessed as DMFT index (O)? Methods. The study adhered to PRISMA guidelines. A systematic search was conducted in PubMed/MEDLINE, Web of Science, Scopus, and EMBASE databases. For each study, characteristics and mean difference (MD) with 95% CI were extracted. Meta-analyses were performed using the Revman software (version 5.4) to calculate pooled MD and 95% CI. Random-effects model meta-analysis was performed. Risk of bias was evaluated using the Newcastle-Ottawa Scale adapted for cross-sectional studies. To estimate variance and heterogeneity between trials, the Higgins I2 test was used. The certainty level of the evidence was determined through the GRADE approach. Results. Seven studies fulfilled the inclusion criteria, including 4,396 postmenopausal women and 5,131 control women. Meta-analysis showed an overall MD = 3.13 (95% CI = 2.12 – 4.15; p < 0.00001), which suggest that postmenopausal women had a DMFT index 3 units higher than the control group. Conclusions. Menopause significantly associated to worse dental caries status, probably due to declining estrogen levels affecting salivary function. Further research is needed to confirm mechanisms and evaluate preventive strategies like hormone replacement therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".