Enamel Matrix Derivative Versus Bioactive Ceramic Filler in the Treatment of Intrabony Defects: 12‐Month Results
Bibliographic record
Abstract
BACKGROUND: This study examined the clinical efficacy of enamel matrix derivative (EMD) and bioactive ceramic filler (BCF) in the treatment of intrabony periodontal defects and evaluated factors influencing the treatment outcome. METHODS: Thirteen chronic periodontitis patients, 41 to 74 years of age, who had two proximal intrabony defects in different jaw quadrants with > or =3 mm vertical radiographic bone loss were selected for this study. After initial therapy, the sites in each patient were randomly assigned to EMD or BCF treatment. Clinical attachment level (CAL), probing depth (PD), tooth mobility (TM), gingival recession (GR), bleeding on probing, and dental plaque were recorded at baseline and at 6 and 12 months. At surgery, the intrabony component was characterized by recording the number of bony walls, distance in millimeters from the buccal crest (BC) to the most apical point of the defect, distance from the cemento-enamel junction (CEJ) to the BC, and the mesio-distal width of the defect at the level of the bony crest. RESULTS: BCF treatment resulted in a significant gain in proximal CAL (P = 0.005) and a reduction in proximal PD at 6 months (P <0.001), but there was no further improvement from 6 to 12 months. Paired comparisons by time for the EMD group revealed a significant reduction in proximal PD at 12 months (P = 0.001), whereas the gain in proximal CAL approached significance (P = 0.056). Mean GR increased significantly from baseline to 6 months in both groups (P = 0.001). Regression analysis revealed that within the EMD group, smoking and TM negatively influenced the gain of attachment, whereas within the BCF group, gingival recession increased with age, increasing CEJ to BC distance, and increasing mesial-distal width of the defect. CONCLUSIONS: The gain in proximal attachment after treating intrabony defects by flap surgery with BCF was significant (P = 0.004) and twice that following treatment with EMD (P = 0.056). Patient and site variables affected the clinical outcome differently.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".