Resonance frequency analysis of dental implants placed at the posterior maxilla varying the surface treatment only: A randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Chemical modifications of the dental implant surface that improve the wettability result in a faster and better osseointegration. PURPOSE: The aim of this randomized clinical trial was to evaluate the implant stability quotient (ISQ) of implants with similar designs, treated with 2 surfaces, sandblasted acid-etched (SAE) and hydrophilic SAE, within the initial 16 weeks of healing. MATERIAL AND METHODS: A total of 64 implants (32 SAE-control group and 32 modified SAE-test group) with the same design, length, and diameter (conical and compressive, 4.3 × 10 mm) were inserted into the posterior maxillae of 21 patients partially edentulous. The ISQ values were collected at post-surgery (T0), 1 week (T1), 2 weeks (T2), 3 weeks (T3), 5 weeks (T4), 8 weeks (T5), 12 weeks (T6), and 16 weeks (T7). RESULTS: None of the implants failed. Test group presented ISQ values higher than the control group (ANOVA-P < .01) from T5 to T7. When comparing groups regarding the amount of time required to achieve ISQ ≥ 70 as a reference, there was a statistically significant difference (cox regression-P < .01), and a hazard ratio of 2.24 (CI 1.62-3.11). At the 1-year follow-up, there was a drop out of 1 patient, and 2 implants were no longer evaluated. Survival rate for both groups was 100% at the 1-year follow-up. CONCLUSIONS: The current study suggests that implants with hydrophilic surface (modified SAE) integrate faster than implants with SAE surface. The stability gain of the test group was 2.24 times faster than the control group after 5 weeks of evaluation at the posterior region of the edentulous maxillae.
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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 | 0.001 |
| 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) | 0.005 | 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".