Regenerative Effect of Platelet Concentrates in Oral and Craniofacial Regeneration
Bibliographic record
Abstract
Platelet concentrates (PCs) are biological autologous products derived from the patient's whole blood and consist mainly of supraphysiologic concentration of platelets and growth factors (GFs). These GFs have anti-inflammatory and healing enhancing properties. Overall, PCs seem to enhance bone and soft tissue healing in alveolar ridge augmentation, periodontal surgery, socket preservation, implant surgery, endodontic regeneration, sinus augmentation, bisphosphonate related osteonecrosis of the jaw (BRONJ), osteoradionecrosis, closure of oroantral communication (OAC), and oral ulcers. On the other hand, no effect was reported for gingival recession and guided tissue regeneration (GTR) procedures. Also, PCs could reduce pain and inflammatory complications in temporomandibular disorders (TMDs), oral ulcers, and extraction sockets. However, these effects have been clinically inconsistent across the literature. Differences in study designs and types of PCs used with variable concentration of platelets, GFs, and leucocytes, as well as different application forms and techniques could explain these contradictory results. This study aims to review the clinical applications of PCs in oral and craniofacial tissue regeneration and the role of their molecular components in tissue healing.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".