Caries Status in People with Dementia: A Systematic Review
Bibliographic record
Abstract
Background and Objective: People living with dementia typically have poor oral health. However, studies of caries status in this population have revealed different results. This systematic review aimed to assess caries status in old adults with dementia. Method: The PubMed, Web of Science, Embase, and Scopus databases were searched from inception to 13 February 2025. The Newcastle–Ottawa Scale (NOS) was used to assess the risk of bias in case–control studies, and the Joanna Briggs Institute (JBI) Critical Appraisal Checklist was used to assess the risk of bias in cross-sectional studies. Caries status was measured by the decayed, missing, filled teeth (DMFT) index, decayed, missing, filled surfaces (DMFS) index, or the component of DMFT/S. A random effects model was used to pool the included data. The weighted mean difference (WMD) and 95% confidence interval (CI) were calculated to analyze the effect of dementia on caries. Results: A total of 5363 studies were retrieved, and 20 studies were included in this study. Meta-analysis showed the DMFT index (WMD: 3.76, p < 0.0001; 13 studies), decayed teeth (DT) index (WMD: 0.40, p < 0.0001; 10 studies), and missing teeth (MT) index (WMD: 3.67, p = 0.04; 7 studies) values were higher in the dementia group than the control group. There were no differences in the filled teeth (FT) index (WMD: −0.66, p = 0.09; 9 studies) between the dementia group and the control group. Conclusions: Caries status was poorer in people with dementia than the controls. These findings suggest that medical staff and caregivers need to pay more attention to the oral health of dementia patients.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".