Efficacy of Enamel Matrix Derivative in Vital Pulp Therapy: A Review of Literature.
Bibliographic record
Abstract
INTRODUCTION: Vital pulp therapy (VPT) aims to preserve the health and maintain life of the tooth pulp which has been compromised by caries, trauma or restorative procedures. Recently, enamel matrix derivative (EMD) has been introduced as a material for vital pulp therapy. The aim of this review is to critically analyze and summarize the available literature on EMD for VPT. METHODS AND MATERIALS: for the missing grey literature. All studies fulfilling the selection criteria were carefully reviewed for the focused question: "Does using EMD in VPT, compared with other materials, result in better clinical, radiographic and histological outcomes?". RESULTS: The primary search resulted in 18 articles of which, 14 articles (including 6 animal studies and 6 clinical trials and 2 case reports) met the inclusion criteria for this review and hence were included. The number of teeth tested in the animal studies ranged from 8 to 144 including pigs, rats and dogs teeth. A number of studies used EMD in the experimental group in comparison with calcium hydroxide, propylene glycol alginate (PGA) and MTA as a control. The observation period ranged from 1 to 2 months and 4 out of 6 animal trials reported more favorable outcomes with EMD while two studies reported comparable outcomes. CONCLUSION: Although EMD has potential for various applications in endodontics, studies conducted to date have failed to demonstrate any significant advantage of EMD over conventional VPT materials. Additionally, the 5-year and 10-year survival rate of EMD-treated teeth is not yet known. Hence, studies with a longer follow-up periods are required to deduce the long-term viability of teeth treated with EMD.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".