Prospective randomized clinical trial evaluating the effects of two different implant collar designs on peri‐implant healing and functional osseointegration after 25 years
Bibliographic record
Abstract
OBJECTIVES: Evaluate the effects of two different machined-collar lengths and designs on peri-implant healing. MATERIAL AND METHODS: An implant with a microtextured surface and 3.6mm-long internal-connection machined collar was compared to two implants that had an identical 1.2mm-long external-connection machined collar, but one had the microtextured surface while the other's was machined. Participants received the three implants, with microgap at the crest, alternately at five sites between mental foramen, and a full-arch prosthesis. Peri-implant bone levels were measured after 23 to 26 years of function. Keratinized tissue height, plaque, probing depth, bleeding, and purulence were also evaluated. Descriptive and mixed models for repeated\measures analyses were used, with Bonferroni correction for pairwise comparisons. RESULTS: Twenty-two participants (110 implants) were evaluated at the 25-year examination. Microtextured implants with the longer machined collar had significantly greater mean marginal bone loss (-1.77mm ± 0.18, mean ± SE) than machined (-0.85mm ± 0.18, p < .001) and microtextured (-1.00 ± 0.18mm, p < .001) implants with the shorter machined collar. Keratinized tissue height was greater for internal-connection (0.74mm ± 0.10) versus external-connection (0.51 ± 0.08, p = 0.01) microtextured implants. No differences were observed for plaque (p = 0.78), probing depth (p = 0.42), bleeding (p = 0.07), and purulence (p = 1.00). Implant survival rate was 99%. CONCLUSIONS: Implants with the 1.2mm machined collar limited bone loss to 1mm, while those with the longer machined collar showed > 1.5mm loss after 25 years of function with microgap at the crest. Internal-connection design and fixture surface microtexturing did not result in greater bone preservation. ClinicalTrials.gov Identifier: NCT03862482.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".