Implant Treatment in the Edentulous Maxillae: A 15‐Year Follow‐Up Study on 76 Consecutive Patients Provided with Fixed Prostheses
Bibliographic record
Abstract
BACKGROUND: Few long-term follow-up studies are available on implant treatment based on patient level data related to time. PURPOSE: The aim of this study was to report 15-year patient-based data in relation to time of follow up after treatment with fixed prostheses supported by implants in the edentulous upper jaw. MATERIALS AND METHODS: Seventy-six edentulous consecutive patients, provided with 450 turned Brånemark implants, were followed up with regard to maintenance, complications, and radiographs taken during the follow-up period. RESULTS: Forty-four patients provided with 247 implants were lost to follow up. Patients followed up for 15 years showed as a group a trend of better implant survival than patients lost to follow up (p > .05). Altogether, 37 implants and 5 fixed prostheses failed during the follow-up period. Most implants were lost at abutment surgery (n- 15) and another nine during the first year of function. The 15-year implant and fixed prosthesis cumulative survival rate was 90.9 and 90.6%, respectively. Resin veneer fractures caused most problems, more frequent in the earlier stage while severe wear increased in the later stage of follow up. No implant fractures or loosening of abutment/bridge locking screws were noted. The mean marginal bone loss was 0.5 mm (SD 0.47) after 5 years, followed by only minimal average changes during the following years. No radiographic parameter showed any time-dependent relationship. The percentage of patients presenting at least one implant with more than 2.0-mm bone loss was 4.9% in the interval from 0 to 5 years and 4.0% between 10 and 15 years. Only 1.3% of implants showed >3.0 mm accumulated bone loss after 15 years. CONCLUSION: Implant treatment in the edentulous upper jaw functions well in a 15-year time perspective, but an insignificant trend of higher implant failures was observed for patients lost to follow up. Besides wear and fractures of veneers, no other parameter showed any time-related relationship, indicating an increased risk for more complications during later stages of follow up. However, accumulation of smaller amount of bone loss during the years resulted in an increasing number of implants and patients with bone levels below the third thread, which could be speculated to increase future maintenance after 15 years.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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 | 0.000 |
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".