Association between denture restoration for tooth loss and cognitive impairment: A systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: This study aimed to investigate the association between denture restoration and cognitive impairment through a meta-analysis and to assess the correlation between different degrees of tooth loss. STUDY SELECTION: Observational studies exploring the association between denture restoration and cognitive function were systematically searched across six databases from January 2000 to January 2024. Two researchers independently searched electronic databases and extracted relevant studies from all articles. RESULTS: This study included 24,252 participants from six observational studies. The risk ratio and 95% confidence interval (CI) were used to compare the risk of cognitive impairment. Participants who experienced tooth loss without dentures had a 1.27-fold (95% CI: 1.20-1.38) higher risk of cognitive impairment, whereas those with dentures had only a 1.01-fold (95% CI: 0.92-1.12) higher risk. In the dose-response analysis, the risk of cognitive impairment in the non-denture group increased by 1.009 times (95% CI: 1.006-1.012) for each tooth lost, whereas the denture restoration group showed a 1.003 times (95% CI: 1.000-1.006) increased risk. The years of follow-up and clinical measurement tools simultaneously explained this heterogeneity. CONCLUSIONS: This study provides detailed evidence of a potential association between denture restoration and a reduced risk of cognitive impairment. Furthermore, there was a correlation between denture restoration and a reduced impact of the number of teeth lost on the risk of cognitive impairment. Therefore, timely and reasonable denture restoration may contribute to prevent cognitive impairment.
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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 | 0.017 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| 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 | 0.001 |
| 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 it