Efficacy of the application of leukocyte and platelet‐rich fibrin (<scp>L‐PRF</scp>) on alveolar ridge preservation. A randomized controlled clinical trial
Bibliographic record
Abstract
INTRODUCTION: Alveolar ridge preservation (ARP) is a well-defined treatment performed to reduce bone dimensional changes occurring during the healing of post-extraction sockets to allow for adequate implant placement. Leukocyte and platelet-rich fibrin (L-PRF) has been showing to potentially promote bone and tissue regeneration during wound healing. Therefore, the aim of this study is to evaluate its efficacy for ARP when applied to fresh extraction sockets, in comparison with spontaneous healing. MATERIALS AND METHODS: Twenty-seven patients with hopeless non-molar teeth were treated. After randomization, fresh extraction sockets were either filled with L-PRF or allowed to heal spontaneously. CBCTs and intraoral scans were obtained immediately after extraction and at 4 months. Through superimposition of the obtained images, changes in the horizontal ridge width, height, buccal volume, and ridge contour changes were measured, as well as patient-reported outcome measures (PROM's). RESULTS: The ridge dimensions changed similarly in both groups. Although less reduction occurred in the test group at 1 mm from the bone crest, differences were not statistically significant (p > 0.05). Application of L-PRF did not prevent reductions of ridge contours, neither in the linear vertical aspect nor in volumetric changes. There were no differences between groups in the need for bone regeneration when placing implants. Patients in both groups reported similar outcomes in terms of bleeding, pain, inflammation, and function at 1 and 4 weeks postoperatively. CONCLUSION: Alveolar preservation with L-PRF neither minimized bone resorption occurring after tooth extraction in non-molar sites nor reduced the need for bone regeneration when placing implants. Furthermore, its use did not improve PROM's.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".