Atrial natriuretic peptide augments the variability of sympathetic nerve activity in human heart failure
Bibliographic record
Abstract
OBJECTIVES: Activation of the sympathetic nervous system, decreased heart rate variability (HRV), and loss of modulation of muscle sympathetic nerve activity (MSNA) within the low frequency (LF, 0.05-0.15 Hz) range are three adverse features of advanced congestive heart failure (CHF). In healthy men, atrial natriuretic peptide (ANP) infusion attenuates reflex increases in MSNA and reduces LF components of HRV spectral power. Sympathoinhibitory actions have also been documented in CHF, but effects on the variability of MSNA and HRV have not been described. DESIGN AND METHODS: Heart rate and MSNA were recorded in 10 men (aged 39 +/- 3 years, mean +/- SE) with dilated cardiomyopathy (mean EF 20 +/- 4%) treated with angiotensin converting enzyme (ACE) inhibitors. Subjects received i.v. ANP (50 microg bolus then 50 ng/kg/min) and nitroglycerin (NTG, 8 mg/min) as a hemodynamic control. Signals at baseline, and 13-20 min into each infusion were submitted to spectral analysis. RESULTS: ANP had no effect on HRV, but increased MSNA LF (from 7.9 +/- 1.5 to 12.1 +/- 2.6 U2; P< 0.02) and total spectral power (from 47.9 +/- 5.4 to 61.9 +/- 6.8 U2; P < 0.05). NTG had no effect on the variability of MSNA or HRV. CONCLUSIONS: In CHF patients receiving ACE inhibitors, ANP (i) does not suppress HRV and (ii) enhances the modulation of MSNA, particularly within the LF range. This latter action is not observed with NTG. These findings suggest beneficial actions of exogenous ANP on neurogenic circulatory control.
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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".