Electronic assessment of peri‐implant mucosal esthetics around three implant–abutment configurations: a randomized clinical trial
Bibliographic record
Abstract
OBJECTIVES: To objectively assess the influence that three different implant-abutment interface designs had on peri-implant mucosal esthetics at 1 year post-implant placement via the pink esthetic score (PES). Additionally, to demonstrate the novel employment of a tablet-based digital imaging format to reliably assess and score clinical images as part of a multicenter clinical trial according to PES criteria. MATERIALS AND METHODS: Adult subjects (n = 141) with healed tooth-bound edentulous sites in the anterior maxilla as well as first premolar region were randomized to receive one of three different implant-abutment interface designs (conical interface = CI; flat-to-flat interface = FI; or platform switch interface = PS). Immediate provisionalization was performed with prefabricated titanium abutments, with definitive custom CAD/CAM zirconia abutments and all-ceramic cement-based crowns being delivered 12-week post-implant placement. Bilateral (anterior sites) or unilateral (premolar sites) digital clinical photographs were made at 1, 3, 6, and 12 months post-implant placement. Five calibrated faculty evaluators of different clinical backgrounds scored images during a 4-week timeframe on a standardized, tablet-based, digital imaging format. RESULTS: Six hundred and forty-nine clinical photographs were evaluated resulting in a total of 3245 sum PES values and 22,715 individual PES values. Faculty evaluator intra- and inter-rater reliability was found to be "strong" (ICC = 0.84) and "substantial" (ICC = 0.64), respectively, demonstrating repeatability of both the PES, evaluator calibration, and standardization of tablet-based scoring. All implant-abutment interface groups demonstrated significant improvements in mean sum PESs up to 1 year, with the largest improvement between restoration delivery and 6 months. No significant differences were found between groups in mean sum PESs both for individual study visits as well as for changes between study visits. CONCLUSIONS: No significant differences in mean sum PESs were found between subjects randomized to three different implant-abutment interfaces. However, significant differences were found as a function of time for all three groups, with the largest improvement in mean sum PESs occurring between definitive abutment and restoration delivery and 6 months. Use of electronic, tablet-based digital imaging scoring formats represents a novel and repeatable methodology for scoring PES images in large, multicenter clinical trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.035 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".