A prospective cohort study of immediate implant placement into posterior compromised sockets with or without primary wound closure of reactive soft tissue
Bibliographic record
Abstract
BACKGROUND: Conventional wisdom states that reactive soft tissue consisting of granulation tissue and long junctional epithelium in compromised sites should be curetted completely, while others approve of its preservation in implant surgeries. PURPOSE: To evaluate the presence of reactive soft tissue as wound closure for immediate implantation in posterior compromised sockets. MATERIALS AND METHODS: Thirty-three implants were included in this study: (a) experimental group (EG), the reactive soft tissue was raised as the primary wound closure for the implant; (b) control group (CG), the reactive soft tissue was also elevated but failed to cover the site. Implants were inserted immediately after the tooth extraction. The bone dimensional changes were observed instantly after surgery (T1) and 6 months later (T2) by cone beam computed tomography. Soft tissue alterations were evaluated before tooth extraction (T0), at prosthesis delivery and at 1-year follow-up (T3). Measurements of marginal bone level (MBL) was obtained at the time of prosthesis placement and at T3. RESULTS: In all, 100% implant survival was reported during the study period. The buccal bone height and width of keratinized mucosa decreased less in the EG compared to the CG. At the 1-year follow-up, MBL and soft tissue changes were not significantly different between the two groups. CONCLUSIONS: Within the limitations of this study, the presence of reactive soft tissue as primary closure may contribute to hard-soft tissue augmentation during immediate implants into posterior compromised sockets.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".