Periodontal care may improve systemic inflammation
Bibliographic record
Abstract
BACKGROUND: Periodontitis is an infectious chronic insidious disease of the tooth supporting structures that causes a general inflammatory response. The aims of the study were to determine whether periodontitis is associated with markers of general inflammation high-sensitivity (hs) C-reactive protein (CRP) leading to cardiovascular disease, and whether proper management of the periodontal disease would improve inflammation and thus, may prevent cardiovascular disease in the future. METHODS: This was a prospective case-controlled pilot study. Nine patients (3 women, 6 men; 40+/-5 yr) took part. All had severe periodontitis, without systemic disorders, and were all treated conservatively without surgical intervention. All had a 2nd visit after 3 months of treatment at the Outpatient Dental Clinic of the Hospital. Periodontal status and hs-CRP were evaluated on entry to the study and 3 months after treatment. Nine age and sex-matched healthy volunteers without periodontal disease served as the control group. RESULTS: Periodontal clinical parameters were improved after 3 months' treatment: probing depth (PD) (mean) at baseline was 4.3 and after 3 months' treatment improved to 3.2 (P=0.001), clinical attachment level (CAL) (mean) was 4.6 and changed to 3.7 (P=0.01), bleeding on probing (BOP %) changed from 64% to 33% (P=0.001), and Plaque index (Pi) changed from 49% to 25% (P=0.001). hs-CRP level was different between the patients'group (pre treatment) and the healthy volunteers: 2.97+/-0.58 mg/L vs. 0.25+/-0.14 mg/L (P=0.00002). After completing 3 months' treatment, hs-CRP levels were decreased from 2.97+/-0.58 mg/L to 2.3+/-0.7 mg/L (P=0.009). CONCLUSIONS: Periodontitis is an infectious condition that may be an insidious cause of chronic inflammation and may be a risk factor for future cardiovascular disease. Treating periodontitis improved inflammation, and might be used as an important prevention tool for cardiovascular disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".