Relationship between prosthodontic evaluation and patient ratings of mandibular conventional and implant prostheses.
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to compare clinicians' ratings of the state of oral tissues and their satisfaction with treatment to edentulous patients' ratings of treatment success after provision of mandibular implant overdentures or conventional dentures. MATERIALS AND METHODS: Sixty subjects randomly received either mandibular overdentures retained by two implants (n = 30) or new conventional mandibular complete dentures (n = 30). All were given new conventional maxillary dentures. Baseline measures included clinical evaluation of the oral soft and hard tissues. Patients rated their general satisfaction before and after treatment, as well as their satisfaction with stability, speech, and esthetics on visual analogue scales. The treating prosthodontist rated the dentures for the same categories. Patient and clinician ratings were compared using correlations, t tests, and linear regression. RESULTS: None of the clinical variables were significantly correlated with patient satisfaction before or after treatment. The prosthodontist rated mandibular implant overdentures significantly better than conventional dentures regarding general satisfaction, stability, speech, and esthetics. Implant overdentures were also easier to fabricate (P < .0001). The prosthodontists' scores were not significantly correlated with patient scores for any question. CONCLUSION: Clinicians' assessments of the quality of denture-supporting tissues are poor predictors of patient satisfaction with mandibular implant or conventional prostheses. Prosthodontists and patients both rate mandibular implant overdentures as significantly superior to conventional dentures, but patients and clinicians do not usually agree when evaluating individual prostheses.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".