Comparison of immediate‐load mini dental implants and conventional‐size dental implants to retain mandibular Kennedy class I removable partial dentures: A randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Complications of distal extension mandibular removable partial dentures are: loss of retention, irritation, and so forth. Dental implants have been used to support distal extension removable partial dentures. However, many patients have limited bone support in which to place conventional-size dental implants. PURPOSE: To compare the clinical outcomes of using immediate-loaded mini dental implants and immediate-loaded conventional-size dental implants, when used to retain mandibular Kennedy class I removable partial dentures. MATERIALS AND METHODS: Thirty patients were randomly divided into two groups. Mini dental implants and conventional-size dental implants were placed in participants in the first molar region on both sides. The dentures were connected immediately. Patients were recalled on 1, 3, 6, and 12 months after surgery. Digital periapical radiographs were made, and patient satisfaction was recorded. Data were analyzed by independent samples t-test and paired samples t-test (P = .05). RESULTS: Twenty eight of the implants survived (survival rate = 93.3%) in each group. Mean radiographic bone loss was 0.47 ± 0.42 and 1.03 ± 1.07 mm in groups 1 and 2, respectively. Conventional-size implants revealed significantly greater marginal bone loss than mini implants (P = .01). Patient satisfaction showed significant improvement after treatment in both groups. CONCLUSIONS: Immediate-loaded mini dental implants can be applied for retaining mandibular Kennedy class I removable partial dentures with very favorable results.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".