Comparison of the accuracy of implant placement using different drilling systems for static <scp>computer‐assisted</scp> implant surgery: A simulation‐based experimental study
Bibliographic record
Abstract
BACKGROUND: Different designs of surgical drilling systems have been developed for the purpose of static Computer-Assisted Implant Surgery (sCAIS), but there is at present little understanding of how design principles affect the accuracy of implant placement. PURPOSE: The aim of this in vitro study was to compare the accuracy of implant placement among five drilling systems of sCAIS in a controlled experimental setting. MATERIALS AND METHODS: Twenty-five 3D printed models with two edentulous bilateral premolar spaces were allocated to five different drilling systems: group A: sleeve-in-sleeve, group B: sleeve-in-sleeve with self-locking, group C: mounted sleeve-on-drill, group D: integrated sleeve-on-drill with metal sleeve in the guide, group E: integrated sleeve-on-drill without metal sleeve. Models were scanned with CBCT and optical scanner. All implants were digitally planned and 10 implants placed with sCAIS in each group. Postoperative 3D deviation of placed vs planned position was measured by means of platform, apex and angular deviation. Data was analyzed using Kruskal-Wallis test (P ≤ .05). Pairwise comparisons were tested with Dunn's test with adjusted P values. RESULTS: The overall platform deviation ranged from 0.42 ± 0.12 mm (group B) to 1.18 ± 0.19 mm (group C). The overall apex deviation ranged from 0.76 ± 0.22 mm (group B) to 1.95 ± 0.48 mm (group D). The overall angular deviation ranged from 2.50 ± 0.89 degree (group B) to 5.30 ± 1.04 degree (group E). Group A and B showed significantly less angular deviation than groups D and E (P < .05). There was no statistically significant differences in all parameters between group A and B, as well as between group D and E (P > .05). CONCLUSIONS: Significant differences were found with regards to accuracy among the five sCAIS systems tested, suggesting that the drilling protocol, the devices used and the design principles of the guides could influence the accuracy of implant placement.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".