Do mandibular implant overdentures and conventional complete dentures meet the expectations of edentulous patients?
Bibliographic record
Abstract
OBJECTIVES: To measure expectations of satisfaction with implant and conventional denture treatment in 2 groups of edentulous people and compare them with their resultant ratings of satisfaction to determine if either treatment meets the pretreatment expectation. METHOD AND MATERIALS: One hundred sixty-two edentulous middle-aged (MA, n = 102) and senior (S, n = 60) patients were enrolled in 2 trials and, after randomization, received either a mandibular 2-implant overdenture (IOD) or a new conventional denture (CD). Before randomization, each subject rated their satisfaction with their current denture and expectations of satisfaction with both IOD and CD treatment on 100-mm visual analog scales (VAS). Six months posttreatment, all rated their satisfaction with their new prostheses on similar VAS. Expectations and satisfaction with treatment were compared. RESULTS: Posttreatment satisfaction with CD treatment was significantly lower than pretreatment expected satisfaction in both study populations (MA, P < .0001; S, P = .036). There was no (or only borderline) significant difference between pretreatment expectation and posttreatment satisfaction for patients receiving IODs in both study populations (MA, P = .078; S, P = .057). CONCLUSION: Posttreatment CD satisfaction failed to meet patients' pretreatment expectations of satisfaction; this was not the case for IODs, for which expectations were largely met.
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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 | 0.002 | 0.007 |
| 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 | 0.001 | 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".