A comparative study of encode protocol versus conventional protocol for restoring single implants: One‐year prospective randomized controlled clinical trial
Bibliographic record
Abstract
BACKGROUND: The Encode protocol (Biomet 3i, Palm Beach Gardens, Fla) has been proposed as a simplified implant restoration protocol. PURPOSE: To compare the 1-year clinical outcome of the Encode and conventional protocols for restoring single implants. MATERIALS AND METHODS: Forty-seven implants were inserted in 44 patients. After randomizing the implants, 24 implants were allocated to the Encode protocol and 23 implants were allocated to the conventional protocol. After 1 year, changes in esthetics, patient satisfaction, proximal contacts quality, occlusal contacts quality, marginal bone level (MBL), and probing pocket depth (PPD) were evaluated. Further, the prosthesis cleansability, mucosal health, bleeding on probing (BoP), metallic discoloration, and all forms complications were recorded. RESULTS: Forty patients with 41 implants (22 Encode and 19 conventional) were recalled. One conventional crown failed due to excessive looseness. Esthetics, patient satisfaction, and prosthesis cleansability were favorable for the two protocols. One Encode crown (4.5%) and six conventional crowns (33.3%) had slight mucosal redness. BoP was present around 8 Encode crowns (36.4%) and eight conventional crowns (45.4%). Only two conventional crowns showed metallic discoloration of the mucosa. The two protocols had similar PPD alteration (Encode = 0.04 mm, conventional = 0.13 mm), and MBL loss (Encode = 0.71 mm, conventional = 0.78 mm). Similar proximal contacts and occlusal contacts were observed for the two protocols. CONCLUSIONS: After 1 year, the Encode protocol for restoring single implants appears to be comparable to the conventional protocol from the biological, prosthetic, and esthetic perspectives.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".