Remodelling of cardiac sympathetic re-innervation with thoracic spinal cord stimulation improves left ventricular function in a porcine model of heart failure
Bibliographic record
Abstract
AIMS: Thoracic spinal cord stimulation (SCS) has been shown to improve left ventricular ejection fraction (LVEF) in heart failure (HF). Nevertheless, the optimal duration (intermittent vs. continuous) of stimulation and the mechanisms of action remain unclear. METHODS AND RESULTS: We performed chronic thoracic SCS at the level of T1-T3 (50 Hz, pulse width 0.2 ms) in 30 adult pigs with HF induced by myocardial infarction and rapid ventricular pacing for 4 weeks. All the animals were treated with daily oral metoprolol succinate (25 mg) plus ramipril (2.5 mg), and randomized to a control group (n = 10), intermittent SCS (4 h ×3, n = 10) or continuous SCS (24 h, n = 10) for 10 weeks. Serial measurements of LVEF and +dP/dt and serum levels of norepinephrine and B-type natriuretic peptide (BNP) were measured. After sacrifice, immunohistological studies of myocardial sympathetic and parasympathetic nerve sprouting and innervation were performed. Echocardiogram revealed a significant increase in LVEF and +dP/dt at 10 weeks in both the intermittent and continuous SCS group compared with controls (P < 0.05). In both SCS groups, there was diffuse sympathetic nerve sprouting over the infarct, peri-infarct, and normal regions compared with only the peri-infarct and infarct regions in the control group. In addition, sympathetic innervation at the peri-infarct and infarct regions was increased following SCS, but decreased in the control group. Myocardium norepinephrine spillover and serum BNP at 10 weeks was significantly decreased only in the continuous SCS group (P < 0.05). CONCLUSIONS: In a porcine model of HF, SCS induces significant remodelling of cardiac sympathetic innervation over the peri-infarct and infarct regions and is associated with improved LV function and reduced myocardial norepinephrine spillover.
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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".