<i>Porphyromonas endodontalis</i>in chronic periodontitis: a clinical and microbiological cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Although previous studies have shown the presence of Porphyromonas endodontalis in chronic periodontitis associated with periapical lesions, the occurrence of this pathogen in diseased periodontal sites without periapical lesions has been poorly investigated. OBJECTIVE: The aims of this study were to quantify P. endodontalis in patients with chronic periodontitis without periapical lesions, to evaluate the potential correlation of P. endodontalis with Porphyromonas gingivalis and Tannerella forsythia, and to evaluate the ability of periodontal treatment to reduce these pathogens. DESIGN: Patients with generalized chronic periodontitis were selected by recording clinical attachment level (CAL), probing depth (PD), and bleeding on probing (BOP). Subgingival samples from 30 diseased nonadjacent sites (CAL≥5 mm, PD between 5 and 7 mm and positive BOP) and 30 healthy nonadjacent sites (PD≤3 mm and negative BOP) were collected and subjected to microbial analysis by quantitative polymerase chain reaction (qPCR) The variables of age, PD, CAL and BOP of all individuals were analyzed using the paired t-test (GrapPad Prism5(®)). Data of bacteria quantification were subjected to a normality test (D'Agostino-Pearson Test). For bacterial correlation analysis, the Spearman correlation was used. RESULTS: Our results showed that diseased sites had significantly higher levels of P. endodontalis compared to healthy sites, similar to the results obtained for P. gingivalis and T. forsythia. The numbers of all bacterial species were reduced significantly after mechanical periodontal treatment. P. endodontalis was significantly correlated with the presence of T. forsythia and P. gingivalis in the diseased group. CONCLUSION: Our results suggest that there is a high prevalence of P. endodontalis, P. gingivalis and T. forsythia in periodontitis sites and that mechanical periodontal treatment is effective at reducing the pathogens studied.
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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 | 0.004 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".