The Contribution of Regenerative Endodontics in the Management and Healing of Pathological Root Resorptions: A Systematic Review
Bibliographic record
Abstract
Abstract Pathological root resorption is an irreversible condition that can compromise the tooth's prognosis. Despite the success of conventional root canal treatment, these methods have their limitations and cannot restore damaged dental tissue. Recently, regenerative techniques have been employed to treat pathological root resorption. The aim of this systematic review is to evaluate the role of regenerative endodontics in managing pathological internal and external root resorptions in permanent teeth. A literature search was conducted on the following databases: MEDLINE via PubMed, Web of Science, Cochrane, and Scopus, using the following Medical Subject Headings (MeSH) « root resorption », « regenerative endodontics », and keywords « tooth resorption » and « Platelet-Rich Fibrin ». A reading grid was established to extract data related to the research question. The methodological quality of each included study was assessed using Cochrane RoB and Newcastle–Ottawa scale. The review protocol was registered with PROSPERO (identification N° CRD420251023900). After applying inclusion and exclusion criteria, nine articles were included in our review. These studies examined clinical data related to the type and location of root resorption, as well as data related to the regenerative endodontic technique employed, and the type of repair. The risk of bias was low in one study and moderate in eight studies. The selected studies highlighted the effectiveness of regenerative endodontic techniques based on platelet-rich fibrin and revascularization in the treatment of internal and external resorptions, demonstrating their ability to repair resorption defects through the formation of newly calcified tissue.
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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 | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 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".