Effect of Induced LV Dyssynchrony by Right Ventricular Apical Pacing on All‐Cause Mortality and Heart Failure Hospitalization Rates at Long‐Term Follow‐Up
Bibliographic record
Abstract
BACKGROUND: Right ventricular apical (RVA) pacing may induce left ventricular (LV) dyssynchrony. The long-term prognostic implications of induction of LV dyssynchrony were retrospectively evaluated in a cohort of patients who underwent RVA pacing. METHODS: A total of 169 patients (62 ± 13 years, 69% male) with high RVA pacing burden were included. Echocardiographic evaluation of LV volumes, ejection fraction, and dyssynchrony were performed before and after device implantation. LV dyssynchrony was assessed by 2-dimensional radial strain speckle tracking echocardiography. Based on the median LV dyssynchrony value after RVA pacing, the patient population was dichotomized (induced and noninduced LV dyssynchrony groups) and was followed up for the occurrence of all-cause mortality and heart failure (HF) hospitalization. RESULTS: Baseline mean LV ejection fraction was 51 ± 11%. Median LV dyssynchrony value was 40 ms (12-85 ms) before RVA pacing and increased to 91 ms (81-138 ms) after a median of 13 months (3-26 months) after RVA pacing. Median follow-up duration was 70 months (interquartile range 42-96 months). Patients with induced LV dyssynchrony, defined as LV dyssynchrony value superior to the median at follow-up (≥91 ms), showed higher mortality rates (5% and 27% vs. 1% and 3% at 3 and 5 years follow-up; log-rank P = 0.003) and HF hospitalization rates (18% and 24% vs. 3% and 4% at 3 and 5 years follow-up; log-rank P < 0.001) than patients with LV dyssynchrony <91 ms after RVA pacing. A multivariate model was developed to identify independent associates of a combined endpoint of all-cause mortality or HF hospitalization. Induction of LV dyssynchrony was independently associated with increased risk of combined endpoint (HR [95% CI]: 3.369 [1.732-6.553], P < 0.001). CONCLUSION: Induction of LV dyssynchrony by RVA pacing is associated with worse long-term mortality and increased HF hospitalization rates.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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".