Within‐Subject Comparison of Maxillary Implant‐Supported Overdentures with and without Palatal Coverage
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to compare patient-reported outcomes for maxillary implant-supported overdentures with and without palatal coverage. MATERIALS AND METHODS: Twenty-one maxillary edentulous patients (six women, 15 men) were included. In total, 42 implants were inserted in the anterior maxilla. All patients received implant-supported overdentures on two retentive anchors with palatal coverage for 2 months. Thereafter, patient satisfaction was assessed by means of questionnaires capturing the oral health impact profile (OHIP) on functional limitation, physical pain, psychological discomfort, physical, psychological and social disability, and handicap. Additionally, cleaning ability, general satisfaction, speech, comfort, esthetics, stability, and chewing ability were rated. Subsequently, palatal coverage was reduced, and the patients wore the overdentures for another 2 months. Patient satisfaction was obtained in the same way as above, and the evaluated parameters were compared for the two overdenture designs. RESULTS: There were no significant differences between implant-supported overdentures with and without palatal coverage for any of the OHIP domains. The evaluation of additional parameters revealed significantly higher patient satisfaction for esthetics (mean difference 8.8 mm ± 24.6) and taste (mean difference 28.4 mm ± 29.9) without palatal coverage, p < .01. CONCLUSIONS: Within the limits of this study, maxillary overdentures supported by two implants were equally satisfactory with and without palatal coverage.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".