A 10-Year Follow-Up Study of Titanium Dioxide–Blasted Implants
Bibliographic record
Abstract
BACKGROUND: Dental implants with moderately rough surfaces are commonly used in the treatment of edentulous patients. However, long-term data on survival rates and marginal bone conditions are lacking. PURPOSE: This prospective study evaluated the cumulative survival rate of the TiOblast implant (Astra Tech AB, Mölndal, Sweden) after 10 years of prosthetic loading. MATERIALS AND METHODS: A total of 199 TiOblast implants were placed in 36 consecutive edentulous patients (23 males and 13 females). All patients were treated at one clinic and by the same team. The patients were edentulous in either the maxilla (n = 16) or the mandible (n = 20). The average age of the patients at the start of the trial was 64 years (range, 59-82 years). Of the 199 implants inserted 108 were in the mandible and 91 were in the maxilla. Clinical evaluations were undertaken after completion of the prosthetic superstructure (baseline) and after 6 months, 1 year, 3 years, 5 years, 7 years, and 10 years. Mean marginal bone level was evaluated for the first 100 placed implants for up to 7 years. RESULTS: Six implants failed during the study (3 in the mandible and 3 in the maxilla). All failures occurred within the first year, giving a cumulative survival rate of 96.9% (96.6 % in the maxilla and 97.2 % in the mandible) after 10 years of follow-up. The survival rate for the superstructures was 100%. The mean marginal bone level in the measured sample was 0.2 mm (standard deviation [SD], 0.31) below the reference point at baseline, 0.28 mm (SD, 0.20) and 1.27 mm (SD, 1.15) below the same point 7 years later (mean, 0.15 mm per year). CONCLUSION: This study showed that titanium dioxide-blasted implants offer predictable long-term results as supports for fixed prostheses in both the maxilla and mandible.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".