The role of <scp>rhFGF</scp>‐2 in periodontal defect bone fill: A systematic review of the literature
Bibliographic record
Abstract
BACKGROUND: Growth factors have been used with success in periodontal regeneration, especially in intrabony defects. Among those, the recombined form of fibroblast growth factor-2 (rhFGF-2) has been also examined. OBJECTIVE: To address the outcomes of periodontal regeneration using rhFGF-2 alone or in combination with bone substitutes primarily in terms of Radiographic Bone Fill (RBF%) and secondary Probing Pocket Depth (PPD), and Probing Attachment Levels (PAL). MATERIAL AND METHODS: A search in MEDLINE and EMBASE using the Ovid interface was conducted from 2000 up to and including the 12th of November 2022. Starting from the initially identified 1289 articles, 34 studies were selected for further analysis. Following the full-text screening, 7 of the 34 studies met the inclusion criteria and thus were included in the systematic review after assessing their quality according to the Newcastle-Ottawa scale (NOS). Clinical and radiographic results (bone gain, pocket depth, and clinical attachment level) after the application of FGF-2 alone or in combination with different carriers were studied in patients with intrabony defects of at least one wall and pocket depth greater than 4 mm. RESULTS: Primary outcomes: RBF% was higher in studies using a combination of rhFGF-2 and bone substitutes (74.6 ± 20.0%) compared to others using the specific growth factor alone or negative controls (22.7 ± 20.7%). In terms of secondary outcomes, the analysis failed to show an additional benefit from the use of the rhFGF-2 alone or in combination with bone substitutes. CONCLUSION: rhFGF-2 can improve RBF% in the treatment of periodontal defects, especially when it is used in combination with a bone substitute.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".