Favoring Trauma as an Etiological Factor in Denture Stomatitis
Bibliographic record
Abstract
The etiology of denture stomatitis remains controversial. Trauma due to unstable dentures has been suggested as an etiological factor. Therefore, we tested the hypothesis that the prevalence of denture stomatitis is reduced when mandibular dentures are stabilized by implants. Data were collected at a one-year follow-up from 173 edentulous elders who had randomly received mandibular implant overdentures or conventional dentures. The diagnosis of denture stomatitis was determined according to the Newton classification. Elders wearing conventional dentures were almost 5 times more likely to have denture stomatitis than those wearing mandibular two-implant overdentures (P < 0.0001, Fisher's exact test). Adjusted odds ratios showed that only the type of the prosthesis (AOR = 4.54, 95% CI 2.20 to 9.40) and nocturnal wear (AOR = 3.03, 95% CI 1.24 to 7.40) predict the frequency of denture stomatitis. Thus, implant overdentures may reduce oral mucosal trauma and control denture stomatitis.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".