Early Loading of Fluoridated Implants Placed in Fresh Extraction Sockets and Healed Bone: A 3‐ to 5‐Year Clinical and Radiographic Follow‐Up Study of 39 Consecutive Patients
Bibliographic record
Abstract
BACKGROUND: Immediate placement of implants in extraction sockets for early loading is an attractive treatment modality due to reduced treatment time. However, the outcome of fluoridated implants in this situation with regard to bone levels and health of soft tissues is not well documented. PURPOSE: To evaluate the outcome of early loading of OsseoSpeed(™) dental implants placed into fresh extraction sockets and healed bone in consecutive patients treated in a private clinic. MATERIALS AND METHODS: A total of 182 OsseoSpeed(™) implants (Astra Tech Implant System, DENTSPLY Implants, Mölndal, Sweden), 72 in immediate extraction sockets and 110 in healed sites, were placed in 39 consecutive patients. The implants were loaded with permanent restorations within 60 days (average 31 days). Clinical and radiographic follow-up examinations were performed annually for at least 3 years (mean 55 months). An aesthetic index was used to evaluate the soft tissues adjacent to the prosthetic restorations. RESULTS: No implant was lost during the observation period, giving a survival rate of 100%. Bone level changes during the observation period were minimal, with a mean marginal bone loss of 0.3 ± 0.9 mm around the delayed implants and a mean marginal bone gain of 0.3 ± 1.4 mm around the immediate implants (p = .0036). The frequency distribution of bone level revealed that 85% of implants placed in fresh extraction sockets and 84% of implants in healed bone did not show any loss of bone level during follow-up (p = NS). Soft tissue complications were observed at two immediate implant sites in one patient. The remaining 180 implants received the highest aesthetic score. Moreover, no signs of peri-implant purulent infection or aggressive bone loss were found during the follow-up period. CONCLUSION: Early loading of fluoridated implants with permanent constructions appears to be a viable therapy for implants placed immediately in extraction sites and in healed bone.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".