The thickness of labial bone affects the esthetics of immediate implant placement and provisionalization in the esthetic zone: A prospective cohort study
Bibliographic record
Abstract
BACKGROUND: A 1-2 mm thick labial plate is generally advocated in immediate implant placement and provisionalization (IIPP). However, most of the human labial plates fail to meet this requirement. PURPOSE: This study aimed to investigate the effect of labial plate thickness on hard tissue, soft tissue, and esthetic outcomes in IIPP. MATERIALS AND METHODS: In this prospective cohort study, 40 patients received IIPP of 50 single-crown implants in the anterior maxilla. Patients were categorized into three groups according to their presurgical thickness of labial bone: 0-0.5, 0.5-1, and ≥ 1 mm. CBCT, mucosa recession and the papilla index were used to analyze labial hard and soft tissue alterations with a 1-year follow-up. RESULTS: At 1 year, OCI bone losses were 1.17 ± 0.73, 0.37 ± 0.39, 0.46 ± 0.35 mm; ICH bone losses were 2.23 ± 1.83, 0.74 ± 0.71, 0.72 ± 1.27 mm; TM recessions were 1.00 ± 0.51, -0.06 ± 0.37, -0.30 ± 0.88 mm; TL recessions were 0.61 ± 1.02, -0.18 ± 0.40, -0.26 ± 1.15 mm; TD recessions were 0.61 ± 1.02, -0.18 ± 0.40, -0.26 ± 1.15 mm; PIS scores were 1.63 ± 0.64, 2.20 ± 0.71, 2.71 ± 0.57 in group 0-0.5, 0.5-1 and ≥ 1 mm, respectively. No statistical significance was found between group 0.5-1 and ≥ 1 mm in bone resorption, gingival recession, and papilla index. The bone resorption and gingival recession were significantly the highest in group 0-0.5 mm at 6 months and 1 year. CONCLUSIONS: Group 0.5-1 mm had similar tissue dimensional alteration as group ≥1 mm, while group <0.5 mm suffered more massive bone resorption and gingival recession. Concerning the thickness of the labial plate, this study may suggest an expansion in the indication of IIPP.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".