P5647Temporal variability of T-wave morphology and risk of sudden cardiac death in patients with coronary artery disease
Bibliographic record
Abstract
Abstract Background The possible relationship between temporal variability of electrocardiographic spatial heterogeneity of repolarisation and the risk of sudden cardiac death (SCD) in patients with coronary artery disease (CAD) is not completely understood. Purpose To investigate the prognostic value of temporal variability of T-wave spatial heterogeneity in SCD in patients with CAD. Methods The Innovation to reduce Cardiovascular Complications of Diabetes at the Intersection (ARTEMIS) study population consisted of 1,946 patients with angiographically verified CAD. T-wave morphology dispersion (TMD), which estimates the average angle between all reconstruction vector pairs in T-wave loop based on leads I-II and V2-V6, was analysed on beat-to-beat basis from 10 minutes period of the baseline electrocardiographic recording in 1,678 study subjects. The temporal variability of TMD was evaluated by standard deviation of TMD (TMD-SD). Results After on average of 7.4±2.0 years of follow-up, a total of 47 of the 1,678 study subjects (2.8%) had experienced SCD or were resuscitated from sudden cardiac arrest (SCA). TMD-SD was significantly higher in patients who had experienced SCD/SCA compared with those who remained alive (3.64±2.57 vs. 2.65±2.54, p<0.01, respectively), but did not differ significantly between the patients who had experienced non-sudden cardiac death (n=40, 2.4%) and those who remained alive (2.98±2.43 vs. 2.67±2.55, p=0.45, respectively) or between the patients who succumbed to non-cardiac death (n=88, 5,2%) and those who stayed alive (2.74±2.44 vs. 2.67±2.55, p=0.81). After adjustments with relevant clinical risk indicators of SCD/SCA, such as left ventricular ejection fraction, diabetes, left bundle branch block and Canadian Cardiac Society class, TMD-SD still predicted SCD/SCA (HR 1.113, 95% CIs 1.028–1.206, p<0.01). The discrimination and reclassification accuracy increased significantly (p=0.02, p=0.033) and the C-index increased from 0.733 to 0.741 when TMD-SD was added to the clinical risk model of SCD/SCA. The Kaplan-Meier survival curves show proportional probabilities of event-free survival for different modes of death for patients classified according to the optimised TMD-SD cut-off point (Figure). Figure 1 Conclusions Temporal variability of electrocardiographic spatial heterogeneity of repolarisation represented by TMD-SD independently predicts long-term risk of SCD/SCA in patients with CAD. Acknowledgement/Funding Sigrid Juselius Foundation and Finnish Foundation for Cardiovascular Research
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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) | 0.000 | 0.000 |
| 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".