New 3D technologies applied to assess the long‐term clinical effects of misfit of the full jaw fixed prosthesis on dental implants
Bibliographic record
Abstract
OBJECTIVES: To assess implant:suprastructure misfit in patients with an edentulous jaw restored by an implant-retained fixed dental prosthesis (FDP) and its association with biologic and mechanical adverse events over an extensive period. MATERIAL AND METHODS: Thirty patients with an edentulous mandible treated with implant-supported prosthetics before 2000 were examined clinically in 2012. Each patient had received 4 to 6 implants to retain a FDP made from acrylic and three different metal alloys, that is, Ag-Pd, Pd-Ag, and Au type IV. The implant intra-oral locations were recorded digitally by use of an intra-oral scanner, and the intaglio surface of the detached FDP was recorded using a desktop scanner. The fit was estimated by digital matching of the STL files using industrial metrological software. The average misfit was correlated with the average marginal bone loss and the prevalence of screw loosening or fractures, using the patient as the statistical unit. RESULTS: Over an average of 19 years (range 12 to 32), 5 implants had been lost in 4 participants (96.7% implant survival) and 8 eight prostheses (26.7%) had been remade. Anaverage misfit was 150 μm (SD 35, range 95-232, CI 138-163). An average marginal bone loss of 2.2 mm (SD = 0.7) had occurred (range 0.6 to 5.8 mm) for individual implants. The correlation between framework misfit and marginal bone loss was weak (R² = 0.04) (P = 0.29). The prostheses with a history of screw-related adverse events showed average misfit of 169 μm (SD = 32) vs. those with no history of screw-related adverse events, that is, 134 μm (SD = 30) (P = 0.005, Student's t-test). Fourteen of the 30 participants had experienced at least one incidence of screw loosening or fracture of prosthetic or abutment screw(s) over the period of follow-up. The occurrence among the frameworks fabricated with different metal alloys did not differ (P > 0.05, Fisher's exact test). CONCLUSIONS: Combining STL files with best-fit algorithms to appraise misfit is feasible using metrological software. The effect of misfit between the superstructures on its supporting implants up to ~230 μm on the long-term clinical outcomes appears to be minor, apart from a slightly higher risk of screw-related adverse events.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| 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) | 0.004 | 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".