Platelet gel: applications in dental regenerative surgery.
Bibliographic record
Abstract
BACKGROUND: Platelet growth factors obtained from platelet-rich plasma (PRP) are used in prosthetic and periodontal regenerative therapy in dentistry. Increased microvascular proliferation in the first 20 days is followed by enhanced osteoblast activity and immature osteoid formation within 3-6 weeks, improving the quality and quantity of newly formed bone tissue. The aim of this study was to evaluate, through three-dimensional X-ray monitoring, the amount of bone obtained after bone regeneration treatment with platelet gel from autologous PRP. MATERIALS AND METHODS: Patients eligible for regenerative treatment of atrophic alveolar bone of the maxilla or mandible were studied. The patients' autologous whole blood was collected at the Department of Immunology and Transfusion of San Matteo Hospital for the preparation of platelet gel. The bone at the treated sites was analysed prior to and 4 months after the treatment using the three-dimensional X-ray system Galileos. RESULTS: Over a period of 6 years, 133 patients were treated: 304 implants were inserted and there were five cases of failure. The regenerated bone area consisted of histologically immature osteoid tissue composed of thin trabeculae of vital bone and nuclei of osteocytes, associated with fibro-connective tissue. DISCUSSION: This co-operative trial between the Transfusion Centre, for standardised production and validation of the platelet gel, and the Dental Surgery room for its application showed that the technique appears effective and safe. Although difficulties were encountered because of the small sample size and the inability to carry out long-term histological controls, the use of small amounts of PRP (5-10%) combined with autologous bone (15-20%) and alloplastic material appears to reduce the need for bone grafting.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".