A 1‐Year Prospective Clinical and Radiographic Study of Early‐Loaded Bone Level Implants in the Posterior Maxilla
Bibliographic record
Abstract
PURPOSES: The primary aim of the study was to investigate a 1-year success rate of early-loaded bone level implants with a chemically modified sand-blasted, large grit, acid-etched surface (SLActive®, Institut Straumann AG, Basel, Switzerland) in the posterior maxilla. Secondary objectives included stability of these implants and peri-implant bone level. MATERIALS AND METHODS: Bone level® implants (Institut Straumann AG) inserted into premolar and/or molar maxillary sites were loaded after 6 weeks of healing. The implants were monitored for 1 year using the following outcome measures: implant success, primary and secondary stability, and peri-implant bone level. RESULTS: Out of 37 implants placed in 13 patients, 36 reached sufficient stability and were early loaded, whereas one underwent a delayed loading protocol. One-year success rate of early-loaded implants was 100%. Implant stability at baseline was 71.7 ± 5. 6 to be steadily increased thereafter up to 1 year (80.3 ± 3.3), except at 2 weeks when a nonsignificant decrease was noticed (71.9 ± 3.9). Continuous and significant bone loss was observed, reaching 0.4 ± 0.1 mm in the first postoperative year. CONCLUSION: Bone level implants with the SLActive surface placed into low-density bone and loaded after 6 weeks of healing can predictably achieve and maintain a successful tissue integration.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".