Normal and Excessive Muscle Sympathetic Nerve Activity in Heart Failure: Implications for Future Trials of Therapeutic Autonomic Modulation
Bibliographic record
Abstract
Abstract Aims Patients with sympathetic excess are those most likely to benefit from novel interventions targeting the autonomic nervous system. To inform such personalized therapy, we identified determinants of augmented muscle sympathetic nerve activity (MSNA) in heart failure, versus healthy controls. Methods and results We compared data acquired in 177 conventionally-treated, stable non-diabetic patients in sinus rhythm, aged 18–79 years (149 males; 28 females; left ventricular ejection fraction [LVEF] 25 ± 11% [mean ± standard deviation]; range 5–60%), and, concurrently, under similar conditions, in 658 healthy, normotensive volunteers (398 males; aged 18–81 years). In heart failure, MSNA ranged between 7 and 90 bursts·min−1, proportionate to heart rate (p < 0.0001) and body mass index (BMI) (p = 0.03), but was unrelated to age, blood pressure, or drug therapy. Mean MSNA, adjusted for age, sex, BMI, and heart rate, was greater in heart failure (+14.2 bursts·min−1; 95% confidence interval [CI] 12.1–16.3; p < 0.0001), but lower in women (−5.0 bursts·min−1; 95% CI 3.4–6.6; p < 0.0001). With spline modeling, LVEF accounted for 9.8% of MSNA variance; MSNA related inversely to LVEF below an inflection point of ∼21% (p < 0.006), but not above. Burst incidence was greater in ischaemic than dilated cardiomyopathy (p = 0.01), and patients with sleep apnoea (p = 0.03). Burst frequency correlated inversely with stroke volume (p < 0.001), cardiac output (p < 0.001), and peak oxygen consumption (p = 0.002), and directly with norepinephrine (p < 0.0001) and peripheral resistance (p < 0.001). Conclusion Burst frequency and incidence exceeded normative values in only ∼53% and ∼33% of patients. Such diversity encourages selective deployment of sympatho-modulatory therapies. Clinical characteristics can highlight individuals who may benefit from future personalized interventions targeting pathological sympathetic activation.
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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 | 0.030 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".