Five‐Year Survival Distributions of Short‐Length (10 mm or less) Machined‐Surfaced and Osseotite® Implants
Bibliographic record
Abstract
BACKGROUND: In cases of reduced alveolar bone height, implants of short length (10 mm or less) may be employed although there is a perceived risk that because of their small stature they will be unable to tolerate occlusal loads and will fail to osseointegrate. PURPOSE: This report describes an analysis of prospective multicenter clinical studies evaluating the risk for failure of short-length implants, comparing dual acid-etched (DAE) Osseotite implants (Implant Innovations, Inc., Palm Beach Gardens, FL, USA) to machined-surfaced implants. MATERIALS AND METHODS: Admission criteria were the same for both data sets. Baseline variables of demographics including age, gender and smoking status, bone quality, location, implant dimensions, and types of prostheses were compared to ensure balance among groups. Cumulative survival rates (CSRs) were calculated with the Kaplan-Meier estimator. RESULTS: The implant data included 2294 implants for the DAE series and 2597 implants for the machined-surfaced series. Patient demographics showed similar percentages of occurrence for all variables. The distributions of implants between short- and standard-length data sets for baseline variables including width, location, and restorative type were similar, qualifying these data sets for comparison of the independent variable of length. Overall, there was a 2.2% difference in 5-year CSRs between the machined-surfaced short- and the standard-length implants. For these implants a 7.1% difference was observed in the posterior maxilla and an 8.5% difference in the anterior maxilla. For DAE implants the overall difference between "standards" and "shorts" was 0.7%, which is not statistically significant. CONCLUSION: In this analysis the difference in CSRs between short- and standard-length implants was greater for machined-surfaced implants than for DAE implants.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".