Immediately loaded mini‐implants supporting mandibular overdentures: A one‐year comparative prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Little is known about differences between mini-implants and conventional immediately loaded implants for overdentures. OBJECTIVES: To compare clinical outcomes using two immediately loaded conventional or mini-implants for mandibular overdentures. MATERIALS AND METHODS: Edentulous patients receiving either conventional (4.1 mm) or mini-implants (2.9 mm or less), based on available bone width were analyzed. All implants were immediately loaded with mandibular overdentures installed using locator attachments. Digital periapical radiographs for measuring marginal bone loss and clinical outcomes (ie, periodontal probing, plaque, and bleeding indices) were assessed at 1, 3, 6, and 12-month follow-up periods. RESULTS: Fifty patients (25 receiving conventional implants-12 females, mean age of 65.3 ± 7.3 years; and 25 receiving mini-implants-11 females, mean age of 66.8 ± 8.1 years) was analyzed. Peak insertion torque (P = .001) and bone loss (P = .02), as well as change in plaque (P = .02) and bleeding (P = .04) indices at 12 months differed significantly between groups. Furthermore, linear regression revealed the height of the locator as a risk factor for bone loss (P = .038). CONCLUSIONS: The present findings suggest that two mini-implants are significantly more susceptible to bone loss after immediate loading, for which the height of locator might be considered a risk factor.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".