Absence of Association Between Infectious Agents and Endothelial Function in Healthy Young Men
Bibliographic record
Abstract
BACKGROUND: Although several studies have reported correlations between infections and coronary artery disease, associations with endothelial dysfunction, its precursor, have not been established. This study assessed whether infection with Chlamydia pneumoniae (CP), cytomegalovirus (CMV), Epstein-Barr virus (EBV), or Helicobacter pylori (HP) is associated with decreased endothelial function. METHODS AND RESULTS: Sixty-five male subjects, aged 20 to 45 years, with no risk factors or known coronary artery disease were enrolled in a seroepidemiological cross-sectional study. Endothelial function was determined by flow-mediated brachial vasodilation. Serum antibodies consisting of anti-CP IgG and IgM, anti-CMV IgG, anti-EBV nuclear antigen, and anti-HP IgG and markers of inflammation including high-sensitivity C-reactive protein were measured. Average age was 29.3+/-5.5 years. Seroprevalence values were 65.1%, 34.9%, 88.9%, and 14.3% for CP, CMV, EBV, and HP, respectively. Average values for endothelium-dependent and -independent vasodilation were 9.4+/-4.5% and 12.6+/-5.0%. Despite adequate statistical power (82% for the primary end point), no association between endothelial function and seropositivity to individual infectious agents, infectious burden, or C-reactive protein was observed in regression analyses controlling for variables including age, blood pressure, and lipid parameters. Moreover, no dose-response trends between serum titers and endothelial function were found. CONCLUSIONS: Lack of association between chronic infection with CP, CMV, EBV, HP, or pathogen burden and endothelial function was observed, suggesting that these agents are not implicated as early etiologic triggers in the genesis of coronary artery disease. These results do not preclude active involvement at later stages of the pathophysiological process, such as acceleration of existing atherosclerosis and acute plaque rupture.
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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".