Is oral health‐related quality of life stable following rehabilitation with mandibular two‐implant overdentures?
Bibliographic record
Abstract
OBJECTIVES: The superiority of mandibular two-implant overdentures (IODs) over conventional complete dentures (CDs) in terms of quality of life is still questioned. Furthermore, the stability and magnitude of the treatment effect over time remain uncertain. This follow-up study aimed to determine the stability and magnitude of the effect of IODs on oral health-related quality of life (OHRQoL). MATERIAL AND METHODS: 172 participants (mean age 71 ± 4.5 years) randomly received CDs or IODs, both opposed by conventional maxillary dentures. OHRQoL was measured using the Oral Health Impact Profile (OHIP-20) at baseline, 1 and 2 years post-treatment. Repeated measures ANOVAs were conducted to assess the effects of time and treatment on the total OHIP and its individual domain scores. RESULTS: A statistically significant improvement in OHRQoL was seen for both treatment groups (P < 0.001). This improvement was maintained over the 2 year assessment. At both follow-ups, participants wearing IODs reported significantly better total OHIP scores than those wearing CDs (P < 0.001), with a 1.5 times larger magnitude of effect. In the CD group, baseline OHIP scores influenced the post-treatment scores (P < 0.001). This effect was not found in the IOD group. CONCLUSIONS: The effect of mandibular two-IODs on OHRQoL is stable over a 2-year period. The large magnitude of effect of this treatment supports its clinical significance.
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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 | 0.003 |
| 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 | 0.001 | 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".