A Retrospective, Multicenter Study on a Novo Wide‐Body Implant for Posterior Regions
Bibliographic record
Abstract
BACKGROUND: Wide implants are recommended as "rescues" after failure to increase primary stability in extraction sockets or in poor quality bone. Consequently, inferior results compared with regular diameter implants have been reported. PURPOSE: The purpose of this study was to evaluate retrospectively the outcome of a novo wide-body implant (Max® implant, Southern Implants®, Irene, South Africa) designed for placement in the posterior regions. MATERIALS AND METHODS: In four private practices, patients with at least one Max implant were examined by two independent examiners to determine implant survival and marginal bone loss. Surgical, prosthetic, and patient-related parameters were evaluated to determine their influence on the treatment outcome. RESULTS: Seventy-five patients (31 male, 44 female), with a mean age of 58 years, received 93 Max implants (59 maxilla, 34 mandible) of 8 to 10 mm width. Twenty-seven implants in molar extraction sockets and two in mature bone were immediately loaded; 42 in extraction sockets and 22 in mature bone were delayed loaded. The mean follow-up was 14 months (6-34), and four implants failed (4.3%); mean bone loss after 1 year was 0.46 mm (SD 1.08; range -5.45-3.25). A total of 91.4% lost <1.5 mm of bone during the first year. The implant survival rate was 89.7% and 98.4%, respectively, for the immediate and delayed loaded implants and 95.8% and 95.7% for delayed and immediate placement. Time of placement, time of loading, surgical protocol, or prosthetic design did not affect the outcome. CONCLUSION: Within the limitations of the study, the Max implant demonstrated a survival rate of 95.7% and stable bone conditions after a year, irrespective of loading or surgical protocol. Future prospective studies are needed to evaluate the soft and hard tissue changes in time.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".