Relationship between non-ulcerative functional dyspepsia, occlusal pairs and masticatory performance in partially edentulous elderly persons
Bibliographic record
Abstract
OBJECTIVE: To relate occlusal state, masticatory performance and non-ulcerative functional dyspepsia. BACKGROUND: In spite of the relationship between gastric disturbances and number of present teeth being recognised, the influence of the number of occlusal pairs and masticatory performance, expressed as median particle size, has not been considered. MATERIALS AND METHODS: Thirty-eight subjects (mean age = 71.8 ± 7.7 years) diagnosed with non-ulcerative functional dyspepsia were selected. A further 38 healthy subjects (mean age = 71.9 ± 7.0 years) acted as controls. Subjects were subdivided according to their number of occlusal pairs: (1) 0-4, (2) 5-9 and (3) 10-14. Masticatory performance was evaluated by using the sieving method. Data were analysed using 2-way anova and Bonferroni post-hoc, Chi-square and Odd ratio tests. RESULTS: Subjects presenting with non-ulcerative functional dyspepsia and 0-4 occlusal pairs showed the lowest masticatory performance (p < 0.01). No association between the dyspepsia and the number of occlusal pairs (χ(2) = 0.48, p = 0.785) was observed, however results showed association between functional dyspepsia and masticatory performance (χ(2) = 4.07, p = 0.0437) presenting an odds ratio = 3.46 (Confidence Interval = 0.99-12.10). CONCLUSION: Changes in masticatory performance were associated with the presence of non-ulcerative functional dyspepsia.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".