Periodontal Therapy Effects on Nitrite Related to Oral Bacteria: A 6‐Month Randomized Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Nitrite is a biologic factor relevant to oral and systemic homeostasis. Through an oral bacteria reduction process, it was suggested that periodontal therapy and chlorhexidine (CHX) rinse could affect nitrite levels, leading to negative effects, such as an increase in blood pressure. This 6-month randomized clinical trial evaluated the effects of periodontal therapeutic protocols on salivary nitrite and its relation to subgingival bacteria. METHODS: One hundred patients with periodontitis were allocated randomly to debridement procedures in four weekly sections (quadrant scaling [QS]) or within 24 hours (full-mouth scaling [FMS]) in conjunction with a 60-day CHX (QS + CHX and FMS + CHX), placebo (QS + placebo and FMS + placebo), or no mouthrinse (QS + none and FMS + none) use. Real-time polymerase chain reaction determined total bacterial, Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Streptococcus oralis, and Actinomyces naeslundii levels. Salivary nitrite concentration was determined with Griess reagent. Data were analyzed statistically at baseline and 3 and 6 months by analysis of variance, Kruskal-Wallis, Mann-Whitney U, and Spearman correlation tests (P <0.05). RESULTS: Nitrite concentrations did not tend to change over time. Regarding CHX use, there was a negative correlation between nitrite and total bacterial load at 6 months (FMS + CHX) and one positive correlation between P. gingivalis and nitrite at baseline (QS + CHX). Independently of rinse type, in the FMS group, nitrite correlated negatively with several microbial parameters and also with a higher percentage of deep periodontal pockets. CONCLUSIONS: The relationship between nitrite and bacterial levels appears weak. Short-term scaling exhibited a greater influence on nitrite concentrations then long-term CHX use.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".