C-reactive protein modulates vagal heart rate control in patients with coronary artery disease
Bibliographic record
Abstract
Systemic inflammation is associated with sympathetic cardiac activation and decreased HRV (heart rate variability) in subjects at high risk of CAD (coronary artery disease). In the present study, we examined the influence of systemic inflammation, measured by CRP (C-reactive protein), on vagal HR (heart rate) control during behavioural relaxation in patients with CAD. It was hypothesized that CRP would be associated with decreased vagal HR modulation. Consecutive patients were screened 2 weeks prior to elective PTCA (percutaneous transluminal coronary angioplasty). The study was comprised of 29 subjects who represented the first and fourth quartiles of the CRP distribution: Low (0.47+/-0.07 microg/ml)- and High (8.19+/-1.95 microg/ml)-CRP groups respectively. Vagal HR control was quantified as RR high-frequency spectral power (0.15 to 0.40 Hz), and was assessed in log-transformed absolute units (logHF power). Near-IR particle immunoassay was used to determine high-sensitivity CRP concentration. Assessment entailed 5 min of silent reading and self-guided behavioural relaxation. RR logHF power was decreased in the High-CRP group across both assessment procedures (P=0.032). Behavioural relaxation increased RR logHF power for both the Low- and High-CRP groups (P=0.033). Hierarchical linear regression determined that CRP accounted for 18.9% of the variance in RR logHF power during behavioural relaxation (P=0.03), independent of baseline RR interval, cardiac medication, respiratory logHF power and body mass index. In conclusion, patients with CAD had augmented vagal HR control with behavioural relaxation, but this effect was moderated by the severity of CRP. Therefore it may be advisable to assess systemic inflammation in interventions aimed at improving neurocardiac regulation in patients with CAD.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".