Oral and general health‐related quality of life with conventional and implant dentures
Bibliographic record
Abstract
UNLABELLED: Implant overdentures and conventional prostheses have been compared in several trials using a variety of functional and oral health-related quality of life (OHQOL) outcomes. In this paper, we describe the impact of implant overdentures on general and OHQOL in seniors. OBJECTIVES: To compare the oral health-related and general quality of life of seniors (aged 65-75 years) who received either mandibular implant overdentures or conventional dentures. METHODS: Sixty edentulous patients were recruited. Thirty received mandibular overdentures retained by two implants (IOD) and a conventional maxillary denture, the other 30 subjects received new maxillary and mandibular conventional complete dentures (CD). All completed the 20-item version of the Oral Health Impact Profile (OHIP-20) before treatment, then at two and 6 months after delivery of the dentures. The SF-36 general health questionnaire was completed at baseline and 6 months only. RESULTS: Pretreatment and 6-month data from 55 subjects were analyzed. Those who received the IODs had significantly better OHIP-20 total scores at 6 months. Results for IOD subjects were also superior in the functional limitation, physical pain, physical disability and psychological disability subscales. While no significant between group difference was found on the SF-36 health survey, significant pre-post-treatment differences within the IOD group were detected for the role emotional, vitality and the social function scales. CONCLUSIONS: Mandibular overdentures retained by two implants provide elderly patients with better OHQOL. General health-related quality of life improved in the implant group.
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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 | 0.002 |
| 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 | 0.000 | 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".