Frequency analysis of the signal-averaged ECG of postinfarction patients for prediction of cardiac death
Bibliographic record
Abstract
Frequency domain analyses based on the Fast Fourier Transform (FFT), Wavelet decomposition (WD) and Power law scaling (PLS) were performed on the signal-averaged ECG (SAECG) of 2461 postinfarction patients for the purpose of predicting cardiac death (CD) and compared to time domain (TD) analysis. During follow-up (2 years), 158 patients had CD. FFT was used to estimate the power area ratio from (20 to 50 Hz)/(0 to 20 Hz) and from (40 to 100 Hz)/(0 to 40 Hz). The relative energy (RE) of the SAECG was calculated in seven frequency bands ranging from 0 to 250 Hz using WD. PLS slope was estimated from the spectral log-log plot. Multivariate analysis (Cox) showed QRS duration as the best time domain parameter (risk=3.2, p<0.0005) with RE below 3.9 Hz (risk=2.2, p<0.0006) and RE from 7.8 to 15.6 Hz (risk=2.3, p<0.0006) as independent and significant predictors of CD. FFT and PLS parameters were excluded from the model. WD parameters of the SAECG used for predicting of CD after MI allowed a significant discrimination between CD patients and survivors. The statistical results obtained with the WD parameters were comparable with those obtained by TD parameters.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".