Do Implant Overdentures Improve Dietary Intake? A Randomized Clinical Trial
Bibliographic record
Abstract
People wearing mandibular two-implant overdentures (IOD) chew food with less difficulty than those wearing conventional complete dentures (CD). However, there is still controversy over whether or not this results in better dietary intake. In this randomized clinical trials (RCT), the amounts of total dietary fiber (TDF), macronutrients, 9 micronutrients, and energy in diets consumed by persons with IOD and CD were compared. Male and female edentate patients ≥ 65 yrs (n = 255) were randomly divided into 2 groups and assigned to receive a maxillary CD and either a mandibular IOD or a CD. One year following prosthesis delivery, 217 participants (CD = 114, IOD = 103) reported the food and quantities they consumed to a registered dietician through a standard 24-hour dietary recall method. The mean and median values of TDF, macro- and micronutrients, and energy consumed by both groups were calculated and compared analytically. No significant between-group differences were found (ps > .05). Despite quality-of-life benefits from IODs, this adequately powered study reveals no evidence of nutritional advantages for independently living medically healthy edentate elders wearing two-implant mandibular overdentures over those wearing conventional complete dentures in their dietary intake at one year following prosthesis delivery.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".