Plasma Rich in Growth Factors Improves Patients' Postoperative Quality of Life in Maxillary Sinus Floor Augmentation: Preliminary Results of a Randomized Clinical Study
Bibliographic record
Abstract
PURPOSE: The control of postoperative discomfort may improve the patient's quality of life as well as treatment acceptance. The aim of the present preliminary report was to assess if the use of autologous platelet concentrate during maxillary sinus augmentation may have a favorable impact on pain and other factors related to patient's quality of life in the first week after surgery. MATERIALS AND METHODS: This is an interim report of a randomized single-blind study. Fifteen patients with atrophic edentulous posterior maxilla underwent maxillary sinus augmentation using deproteinized bovine bone matrix (DBBM) as the grafting material (control group). In other 15 patients (test group), autologous plasma rich in growth factors (P-PRP) was added to DBBM, then a P-PRP clot was applied to covering the graft before suturing and finally P-PRP was placed over the suture in liquid form. During the first week postsurgery, all patients filled in a questionnaire for evaluation of main symptoms and daily activities. The outcomes of the questionnaires of the two groups were statistically compared. RESULTS: In the first days postsurgery, the group using P-PRP reported significantly less pain, swelling, and hematoma, and improved functional activities with respect to the control group. CONCLUSIONS: The adjunct of P-PRP to the maxillary sinus augmentation procedure produced a beneficial effect to patients' quality of life in the early postsurgical phase.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".