Relationship Between Periodontitis and Nitric Oxide in Patients Undergoing Maintenance Hemodialysis
Bibliographic record
Abstract
BACKGROUND: The inflammatory processes associated with periodontitis have been implicated in the development and progression of systemic diseases, including chronic kidney disease (CKD). Notably, individuals with CKD frequently exhibit shared risk factors with those affected by periodontitis, such as hypertension, smoking, and diabetes mellitus. Nitric oxide (NO), a free radical with diverse physiological and pathological roles, exerts both anti-inflammatory (e.g., vasodilation, modulation of platelet function) and pro-inflammatory effects, the latter of which have been observed in patients with CKD. AIMS: This study aimed to investigate the relationship between nitric oxide levels in saliva and plasma and various periodontal parameters in patients with chronic kidney disease (CKD), in comparison to a control group without CKD. METHODS: This study enrolled 90 participants seeking dental treatment. The participants were divided into two groups: a CKD group (n = 40) consisting of patients undergoing dialysis or hemodialysis treatment at the Pró-Renal Foundation Dental Clinic, and a control group (n = 50) comprising individuals without CKD who were receiving treatment at the UFPR Dental Clinic. Two calibrated examiners conducted comprehensive periodontal examinations for all participants. Additionally, saliva samples were collected from each participant to assess pH, flow rate, and nitric oxide levels. Venous blood samples were also obtained to quantify plasma nitric oxide concentrations. RESULTS: Patients in the CKD group exhibited significantly poorer periodontal health compared to the control group (p < 0.05), characterized by a larger Periodontal Inflamed Surface Area, greater probing depth, increased clinical attachment level, and a higher visual plaque index (p < 0.05). Furthermore, the CKD group presented with significantly reduced salivary flow (p < 0.05). Notably, this group also showed elevated levels of both nitrate and nitrite in saliva and serum (p < 0.05) compared to the control group. Correlation analyzes revealed significant positive associations between nitrate and nitrite levels (in both plasma and saliva) and several periodontal variables: probing depth (r = 0.38 and 0.41, respectively), clinical attachment level (r = 0.40 and 0.38, respectively), and Periodontal Inflamed Surface Area (r = 0.27 and 0.48, respectively). Conversely, nitrate and nitrite levels in both fluids showed significant negative correlations with glomerular filtration rate (GFR) (r = -0.55 and -0.40, respectively). The visual plaque index demonstrated a significant positive correlation only with salivary nitrate and nitrite levels (r = 0.23), highlighting the potential influence of oral biofilm on nitric oxide metabolism. Interestingly, the comparable levels of nitrate and nitrite observed in saliva and plasma suggest that saliva may be a suitable non-invasive biofluid for biomarker analysis in this context. CONCLUSION: This study revealed a positive correlation between the visual plaque index and salivary nitric oxide levels in the studied population. However, further research involving specific analysis of the oral biofilm composition and its dynamic role within the nitric oxide entero-salivary cycle in these patients is warranted to elucidate this relationship fully.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".