Assessment of tissue oxygenation of periodontal inflammation in patients with coronary artery diseases using optical spectroscopy
Bibliographic record
Abstract
BACKGROUND: We have recently developed a non-invasive periodontal diagnostic tool that was validated in periodontitis patients without systemic disorders like coronary artery disease (CAD). The purpose of present study is to verify whether this optical instrument can also be used in periodontitis patients with CAD. METHODS: A total of 62 periodontitis patients with CAD were recruited along with a control group consisting of 59 age and gender matched periodontitis volunteers without systemic disorders. Using a portable optical near-infrared spectrometer, optical spectra were obtained, processed and evaluated from the two groups. A modified Beer-Lambert unmixing model that incorporates a nonparametric scattering loss function was used to determine the relative contribution of deoxygenated hemoglobin (Hb) and oxygenated hemoglobin (HbO2) to the overall spectrum. The balance between tissue oxygen delivery and utilization in periodontal tissues was then assessed. RESULTS: Tissue oxygen saturation was significantly decreased in the periodontitis sites (p < 0.01), compared to the healthy sites in those individuals with CAD. There was a trend towards increased concentration of Hb and decreased concentration of HbO2 from healthy to diseased sites, without statistical significance (p > 0.05). No statistical differences were found in tissue oxygen saturation between the CAD and control groups either in periodontal healthy or inflammatory sites. CONCLUSION: This study supports the hypothesis that optical spectroscopy can determine the periodontal inflammation in patients with certain systemic disorders like CAD. And the overall periodontal oxygenation profiles in CAD patients resemble those in non-CAD individuals either in healthy or inflammatory sites.
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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) | 0.000 | 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".