Aesthetic Parameters and Patient-Perspective Assessment Tools for Maxillary Anterior Single Implants
Bibliographic record
Abstract
BACKGROUND: This review aimed to concisely describe the current aesthetic objective indices for a single-implant maxillary anterior crown. The secondary aim was to propose introducing a unified, standardized questionnaire for adequately collecting patient-reported outcome measures (PROMs) in implant dentistry. MATERIALS AND METHODS: A literature review was conducted using both EMBASE/Ovid and MEDLINE/PubMed databases by combining keywords and Emtree/Mesh terms related to "Esthetics," "Self-Assessment or Surveys and Questionnaires," and "Single-Tooth Dental Implants." RESULTS: The most meaningful aesthetic objective indices for single implants in the literature are the Pink Esthetic Score (PES), the Papilla Presence Index (PPI), Peri-Implant and Crown Index (PICI), PES/White Esthetic Score (PES/WES), the Implant Crown Aesthetic Index (ICAI), and a modified version of the ICAI (mod-ICAI) index. Clearly, PES/WES is still the most widely accepted tool. It is encouraging to observe that there is an increasing tendency in recent years to report PROMs more frequently in the implant dentistry literature. We proposed the implementation of a unified, standardized questionnaire using a self-administered visual analogue scale (VAS) scoring system, which evaluates overall satisfaction, comfort, tooth appearance, gingival appearance, function, and hygiene complexity. This tool should be validated in the oral implantology research context for its regular implementation or further development. CONCLUSIONS: Conducting qualitative studies among dental implant patients who received few implants or single-tooth implant reconstructions in the aesthetic zone may help dental researchers understand better how to efficiently develop and validate a quantitative instrument. This standard tool would reduce heterogeneity bias by providing comparable data between studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".