Clinical and Radiographic Comparison between Platform‐Shifted and Nonplatform‐Shifted Implant: A One‐Year Prospective Study
Bibliographic record
Abstract
BACKGROUND: Developments in implant hardware and biologic understanding improved treatment predictability in terms of implant survival. Current research focuses on accelerated loading protocols and crestal bone preservation. PURPOSE: This prospective, monocenter study analyzed the clinical and radiographic outcome of a novel parallel-walled implant, with and without platform shift. MATERIALS AND METHODS: Forty-eight consecutively treated patients (30 women, 18 men) with crowns/bridges supported by 115 implants were included. Eighty-three percent of implants were nonocclusal, immediately loaded, and 17% were subjected to one-stage surgery and delayed loading after 10 weeks; 39.1% were of diameter 5.0 mm, enabling platform shifting with a 4.0 mm-wide prosthetic component; 60.9% were of diameter 4.0 mm with a 4.0 mm component. Radiographic crestal bone levels were assessed at baseline and 1 year. A multivariate statistical analysis was performed to determine factors affecting crestal bone loss after 1 year. RESULTS: All implants survived and mean marginal bone loss was 0.73 mm (SD: 0.13; range: -0.60 to 5.0 mm). There was a statistically significant difference between platform-shifted (0.63 mm; SD: 0.18) and nonplatform-shifted (1.02 mm; SD: 0.14) implants. Implants in abundant bone volume lost significant less crestal bone (0.45 mm; SD: 0.14) compared with implants in small volume (1.20 mm; SD: 0.21). Implant diameter, loading time, anatomical position, smoking, and bone quality did not affect crestal bone loss. CONCLUSION: After 1 year of loading, both implant-prosthetic features yield a high survival and limited crestal bone loss. Crestal bone loss is minimized using platform-shifted implants placed in sufficiently voluminous bone. To limit the crestal bone loss, an adopted implant diameter with platform shifting should be considered.
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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 | 0.002 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".