Retrospective study on the clinical outcomes of small‐diameter implants supporting fixed prostheses without bone augmentation in the posterior region after 2 to 12 years
Bibliographic record
Abstract
BACKGROUND: Small-diameter implants (SDIs: diameter <3.5 mm) are often chosen as an alternative to bone augmentation in clinical practice, but the scientific evidence regarding SDI application in the posterior area remains deficient. PURPOSE: To evaluate the clinical and radiographic outcomes of SDIs supporting fixed prostheses without bone augmentation in the posterior region, and to analyze the potential influencing factors related to SDI failures. MATERIALS AND METHODS: Clinical and radiographic data of 243 SDIs in 156 patients were retrospectively assembled after 2 to 12 (mean 4.75) years of follow-up. Implant and prosthesis failures, mechanical and biological complications, and radiographic marginal bone loss (MBL) were evaluated. The influence of patient/implant characteristics and prosthetic design on SDI failures was investigated. RESULTS: Five implants in five patients failed, contributing to 10-year cumulative survival rates of 97.9% on an implant-based analysis and 96.8% on a patient-based analysis. Biological complications and mechanical complications were detected in 22 (9.1%) and 31 (12.8%) of implants, respectively. No implant fracture was detected. Peri-implant MBL during 10 years was 0.60 ± 0.90 mm on average. The implant type (bone-level or tissue-level) was the only factor that significantly influenced SDI failures. CONCLUSION: SDIs supporting fixed prostheses in the posterior region achieved predictable long-term clinical outcomes. However, tissue-level titanium SDIs should be avoided where possible.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".