Abstract 13939: Cardiac Resynchronization Improves Cardiac Sodium Channel mRNA Splicing Most in Patients With Severe Heart Failure
Bibliographic record
Abstract
Introduction: Heart failure (HF) downregulates full-length cardiac sodium channel (SCN5A) mRNA and upregulates the splicing variant D (VD), which encodes a prematurely truncated, nonfunctional channel. Recently, we have shown that the ratio of circulating VD to full-length mRNA can predict the risk of sudden death. Cardiac resynchronization therapy (CRT) improves heart function and decreases arrhythmic events. Nevertheless, the mechanisms are unclear. Hypothesis: We tested whether CRT altered circulating full-length SCN5A mRNA and VD and further investigated its correlation with clinical parameters in HF. Methods: HF patients with new implantable cardioverter-defibrillators (ICDs) for primary prevention were enrolled. Circulating SCN5A and VD levels at baseline and at a follow-up visit were measured and compared using the ratio of VD to total SCN5A transcripts. The change of VD was expressed as the difference between the proportion of VD levels at baseline and at a follow-up visit. Results: A total of 81 HF patients were enrolled. At enrollment, patients with lower ejection fraction (EF) (≤30%) had higher circulating VD levels (0.80±0.11 vs. 0.73±0.07, P<0.05). After a median follow-up of 235 days, the VD ratio significantly improved (0.84±0.08 vs. 0.74±0.10, P<0.01) in patients receiving CRT. In patients without CRT, the VD ratio had significantly increased (0.77±0.07 vs 0.84±0.05, P<0.05). In patients with CRT, the change of the VD ratio significantly correlated with left ventricular end systolic diameter (r=0.853, p<0.01), EF (r=-0.643, p<0.05) and ischemic cardiomyopathy (r=0.645, p<0.05). Conclusions: CRT decreased the proportion of nonfunctional sodium channels, which may explain the lower arrhythmic risk with CRT therapy. Furthermore, the improvement was more prominent in patients with left ventricular dilation, lower EF and ischemic cardiomyopathy.
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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) | 0.001 | 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) | 0.003 | 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".