Increased beat-to-beat T-wave variability in myocardial infarction patients
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Bibliographic record
Abstract
The purpose of this study was to investigate the beat-to-beat variability of T-waves (TWV) and to assess the diagnostic capabilities of T-wave-based features for myocardial infarction (MI). A total of 148 recordings of standard 12-lead electrocardiograms (ECGs) from 79 MI patients (22 females, mean age 63±12 years; 57 males, mean age 57±10 years) and 69 recordings from healthy subjects (HS) (17 females, 42±18 years; 52 males, 40±13 years) were studied. For the quantification of beat-to-beat QT intervals in ECG signal, a template-matching algorithm was applied. To study the T-waves beat-to-beat, we measured the angle between T-wave max and T-wave end with respect to Q-wave (∠α) and T-wave amplitudes. We computed the standard deviation (SD) of beat-to-beat T-wave features and QT intervals as markers of variability in T-waves and QT intervals, respectively, for both patients and HS. Moreover, we investigated the differences in the studied features based on gender and age for both groups. Significantly increased TWV and QT interval variability (QTV) were found in MI patients compared to HS (p<0.05). No significant differences were observed based on gender or age. TWV may have some diagnostic attributes that may facilitate identifying patients with MI. In addition, the proposed beat-to-beat angle variability was found to be independent of heart rate variations. Moreover, the proposed feature seems to have higher sensitivity than previously reported feature (QT interval and T-wave amplitude) variability for identifying patients with MI.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 | 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 it