Effect of Autologous Growth Factors in Maxillary Sinus Augmentation: A Systematic Review
Bibliographic record
Abstract
PURPOSE: The aim of the present study was to systematically evaluate the effect of autogenous platelet concentrates on the clinical and histomorphometric outcomes of maxillary sinus augmentation. MATERIALS AND METHODS: MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials were searched using a combination of specific search terms. Furthermore, a hand searching of the relevant journals and of the bibliographies of reviews was performed. Prospective comparative clinical studies were included. Implant survival and histomorphometric outcomes were evaluated. RESULTS: Twelve studies were included. Four hundred forty-five sinus floor augmentation procedures were considered. No difference in implant survival was reported between test and control groups. Six studies reported a beneficial effect of platelet concentrates based on histomorphometric outcomes, while another six studies found no significant effect. A large heterogeneity was found regarding study design, surgical techniques, graft materials, clinical and histomorphometric outcome variables, and methods for preparing platelet concentrates. Favorable effects on soft tissue healing and postoperative discomfort reduction were often reported but not quantified. CONCLUSIONS: A clear advantage of platelet concentrates could not be evidenced. Standardization in the experimental design is needed in order to detect the true effect of platelet concentrates in maxillary sinus augmentation procedure, especially regarding postoperative quality of life.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".