Immediate implant placement for a single anterior maxillary tooth with a facial bone wall defect: A prospective clinical study with a one‐year follow‐up period
Bibliographic record
Abstract
BACKGROUND: Clinical studies on immediate implant placement for a single anterior maxillary tooth with a facial bone wall defect are rarely reported. OBJECTIVE: To study the clinical outcomes of immediate implant placement combined with flap surgery, guided bone regeneration and non-submerged healing for a single anterior maxillary tooth with a facial bone wall defect. MATERIALS AND METHODS: Forty-five patients with a single failing tooth in the anterior maxillary region showing indications for extraction combined with a facial bone wall defect were treated by means of immediate implant placement combined with flap surgery, guided bone regeneration and non-submerged healing. During this study, the implant survival rate, soft and hard tissue dimension changes, pink aesthetic score (PAS), and patient aesthetic satisfaction were assessed at 1, 6, and 12 months post-operatively. RESULTS: At 12 months post-operatively, the survival rate of 45 implants was 100%. Mesial/distal papillary level reduction and midfacial soft tissue recession were measured as 0.53, 0.41, and 0.31 mm, respectively. The thickness of facial bone reduction measured by cone beam computed tomography was 0.94, 0.80, 0.85, 0.82, 0.45, and 0.41 mm at 6 different sites around the implant. The mean PAS and patient aesthetic satisfaction were determined to be 10.58% and 93%, respectively. CONCLUSIONS: The proposed surgical procedure is a valuable treatment strategy as assessed by preliminary clinical outcomes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".