Anterior single implants with different neck designs: 5 Year results of a randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: The design of the implant neck might be significant for preservation of marginal bone. PURPOSE: To compare the 5-year radiographic and clinical outcome of single anterior implants provided with a smooth neck, a rough neck or a scalloped rough neck. MATERIALS AND METHODS: 93 Patients with a missing anterior tooth in the maxilla were included. At random, patients received an implant with a 1.5 mm smooth neck ("smooth group"), a rough neck with grooves ("rough group") or a scalloped rough neck with grooves ("scalloped group"). Implants were installed in healed sites. Follow-up visits were conducted after final crown delivery and 1 year and 5 years later. RESULTS: Scalloped implants showed significantly more initial marginal bone resorption. The total amount of bone loss was 1.26 ± 0.90 mm in the smooth group, 1.20 ± 1.1 mm in the rough group and 2.28 ± 0.97 mm in the scalloped group (P < .05). Survival rates were 96.2% for the smooth and scalloped group and 100% for the rough group. Scalloped implants showed deeper pocket depths, more bleeding and more technical complications. There were no differences in esthetic outcome nor in patient satisfaction. CONCLUSIONS: For anterior single tooth replacements, scalloped implants show less favorable radiographic and clinical outcome compared to regular implants with a smooth neck or rough neck.
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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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".