Immediate loading of multiple splinted implants via complete digital workflow: A pilot clinical study with 1‐year follow‐up
Bibliographic record
Abstract
BACKGROUND: Complete digital workflow attracts more attention in implant dentistry. OBJECTIVES: To explore the feasibility and short-term clinical results of immediate loading of multiple implants with fixed temporary bridges (2-4 teeth span) by complete digital workflow, and to evaluate the three-dimensional (3D) deviation of digital impression comparing with traditional impression method. MATERIAL AND METHODS: A total of 31 partial edentulous patients (16 females and 15 males) were recruited in this study. Digital impressions were taken immediately after implant placement, and implant-supported splinted temporary bridges were fabricated through a full digital approach (model free) and delivered within 24 hours. Final restorations were finished 4 months after surgery via traditional impression technique. Subjects were followed 1 year after treatment. 3D impression deviations were analyzed by comparing the digital and conventional impression methods. Time costs for the full digital approach were recorded. Implant survival rate, marginal bone levels were evaluated. RESULTS: All the recruited subjects finished this study. Seventy-four implants were surgically placed and immediately loaded with 34 temporary bridges fabricated through a full digital approach. Digital impression deviation compared with traditional impression method was 27.43 ± 13.47 μm. Time costs for chair side and laboratory were 32.55 ± 4.73 and 69.30 ± 10.87 minutes, respectively. Marginal bone alterations were -1.58 mm and -1.69 mm at the time of 4 and 12 months after surgery. The implants had a survival rate of 100% at the 1-year follow-up time. CONCLUSIONS: Immediate loading of multiple implants in partial edentulous (2-4 teeth span) patients with full digital approach is clinically applicable. The 3D discrepancy between digital and traditional impression is within clinical acceptable range.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".