Effectiveness of concentrated growth factors in regenerative endodontic treatment of immature permanent teeth - A systematic review and meta-analysis
Bibliographic record
Abstract
ABSTRACT Aim: The aim of this review was to study the effectiveness of concentrated growth factors (CGFs) for regenerative endodontic treatment (RET) in necrotic immature permanent teeth. Methods: Two independent reviewers were involved in a literature search across five databases to identify clinical trials published up until June 2024. The quality of included clinical trials was evaluated using the revised Cochrane risk of bias tool (RoB 2.0) for randomized controlled trials (RCTs) and the Newcastle–Ottawa scale for retrospective studies. The certainty of evidence was further assessed using the Grading of Recommendations, Assessment, Development, and Evaluation approach. A random-effect meta-analysis of standard mean difference was used to compute the summary risk ratio (and relative 95% confidence interval [CI]) between interventions. Results: In total, five studies were included, comprising two randomized clinical trials and three retrospective studies. Risk of bias assessment indicated that both RCTs had a low risk of bias, while two retrospective studies showed a low risk, and one had moderate concerns due to sample size limitations and nonrespondent factors. A combined hazard ratio of 1.00 with a 95% CI suggests no statistical difference between groups. The present meta-analysis revealed that CGF exhibits higher efficacy compared to platelet-rich fibrin (PRF) and blood clot with RET. Conclusion: This systematic review provides evidence that both CGF and PRF yielded positive results in terms of clinical and radiological outcomes. The choice between CGF and PRF may be influenced by factors such as the clinician’s preference, patient-specific considerations, and the intended therapeutic outcome. Moreover, conducting further high-quality clinical trials could yield a greater understanding of the advantages and disadvantages of CGF and PRF in different clinical situations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".