New electrocardiographic score for the prediction of atrial fibrillation: The MVP ECG risk score (morphology‐voltage‐P‐wave duration)
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia and has significant morbidity. A score composed of easily measured electrocardiographic variables to identify patients at risk of AF would be of great value in order to stratify patients for increased monitoring and surveillance. The purpose of this study was to develop an electrocardiographic risk score for new-onset AF. METHODS: A total of 676 patients without previous AF undergoing coronary angiography were retrospectively studied. Points were allocated based on P-wave morphology in inferior leads, voltage in lead 1, and P-wave duration (MVP). Patients were divided into three risk groups and followed until development of AF or last available clinical appointment. RESULTS: Mean age was 65 years, and 68% were male. The high- and intermediate-risk groups were more likely to develop AF than the low-risk group (odds ratio [OR] 2.4, 95% confidence interval [CI] 1.3-4.4; p = 0.006 and OR 2.1, 95% CI 1.4-3.27; p = 0.009, respectively). The high-risk group had a significantly shorter mean time to development of AF (258 weeks; 95% CI 205-310 weeks) compared to the intermediate- (278 weeks; 95% CI 252-303 weeks) and low-risk groups (322 weeks 95% CI 307-338 weeks), p = 0.005. CONCLUSIONS: A simple risk score composed of easy-to-measure electrocardiographic variables can help to predict new-onset AF. Further validation studies will be needed to assess the ability of this risk score to predict AF in other populations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".