Correlation Between T Peak to End Interval and Left Ventricular Time to Peak Longitudinal Strain in Ischemic Cardiomyopathy Patients
Bibliographic record
Abstract
BACKGROUND: Ischemic cardiomyopathy is the most frequent etiology of heart failure with reduced ejection fraction (HFrEF) and a result of ventricular structural, functional and electrical remodeling. T peak to end (Tpe) interval is an electrocardiographic parameter that represents repolarization heterogeneity and had prognostic value for ventricular arrhythmia. Patients with ischemic cardiomyopathy face a significant burden of arrhythmias. Mechanical dispersion is a functional remodeling parameter that can be measured by time to peak longitudinal strain using speckle tracking echocardiography. This study aimed to assess the relationship between Tpe interval with time to peak longitudinal strain in ischemic cardiomyopathy patients. METHODS: This study was conducted with an observational analytical cross-sectional design. Ischemic cardiomyopathy subjects were included at Dr. Hasan Sadikin General Hospital, Bandung, from August to October 2019. Tpe interval was measured manually with the tangential method. Time to peak longitudinal strain was measured using speckle tracking echocardiography. The correlation between Tpe interval and time to peak longitudinal strain was analyzed using Pearson correlation. RESULTS: A total of 30 subjects were included in this study. The average age was 58 ± 8 years old, and the average left ventricular ejection fraction was 27±5.5%. The average of Tpe interval was 83.4 ± 7.62 ms, and the average time to peak longitudinal strain was 93.13 ± 34.51 ms. The Pearson correlation test showed a significant weak positive correlation (r = 0.386, 95% confidence interval: 0.029 - 0.743, P = 0.018) between Tpe interval and time to peak longitudinal strain in ischemic cardiomyopathy patients. CONLUCIONS: There was a significant weak positive correlation between Tpe interval and time to peak longitudinal strain in ischemic cardiomyopathy patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".