Patterns of ectopy leading to increased risk of fatal or near-fatal cardiac arrhythmia in patients with depressed left ventricular function after an acute myocardial infarction
Bibliographic record
Abstract
AIMS: To identify potential new markers for assessing the risk of sudden arrhythmic events based on a method that captures features of premature ventricular complexes (PVCs) in relation to sinus RR intervals in Holter recordings (heartprint). METHODS AND RESULTS: Holter recordings obtained 6 weeks after acute myocardial infarction from 227 patients with reduced ventricular function (left ventricular ejection fraction ≤ 40%) were used to produce heartprints. Measured indices were: PVCs per hour, standard deviation of coupling interval (SDCI), and the number of occurrences of the most prevalent form of PVCs (SNIB). Predictive values, survival analysis, and Cox regression with adjustment for clinical variables were performed based on primary endpoint, defined as an electrocardiogram-documented fatal or near-fatal arrhythmic event, death from any cause, and cardiac death. High ectopy (PVCs per hour ≥10) was a predictor of all endpoints. Repeating forms of PVCs (SNIB ≥ 83) was a predictor of primary endpoint, hazard ratio = 3.5 (1.3-9.5), and all-cause death, hazard ratio = 2.8 (1.1-7.3), but not cardiac death. SDCI ≤ 80 ms was a predictor of all-cause death and cardiac death, but not of primary endpoint. CONCLUSION: High ectopy, prevalence of repeating forms of PVCs, and low coupling interval variability are potentially useful risk markers of fatal or near-fatal arrhythmias after myocardial infarction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".