Implant‐Supported Single Crowns Replacing Congenitally Missing Maxillary Lateral Incisors: A 5‐Year Follow‐Up
Bibliographic record
Abstract
BACKGROUND: Knowledge of the long-term survival of single implants in cases of congenitally missing lateral incisors in the maxilla is limited. PURPOSE: This retrospective study aimed to evaluate the 5-year survival of implants and implant-supported crowns (ISCs) and to assess the functional and aesthetic outcomes from the professional and patient perspectives. MATERIALS AND METHODS: From a total of 46 patients with congenitally missing upper lateral incisors, 36 patients treated with 54 Brånemark® (Nobel Biocare AB, Göteborg, Sweden) implants and ISCs participated in the study. A clinical examination, California Dental Association (CDA) evaluation, and patient questionnaire were used to rate and compare the objective and subjective evaluations of the ISCs. RESULTS: The survival of implants and ISCs was 100%. The CDA ratings were satisfactory for all ISCs, with 70% being rated excellent. The patient rating was also high for the overall satisfaction item, with 21 being completely satisfied and 14 fairly satisfied. However, 12 patients wished for the replacement of their ISCs. Logistic regression analysis indicated that a less optimal embrasure fill was the most discriminating factor though not statistically significant (p = .082). CONCLUSIONS: One-third of the patients wished for the replacement of their ISCs. Soft tissue adaptation seems to be an important factor for overall satisfaction.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".