T-Peak to T-End Improvements After Beta-Blocker Administration in Peripartum Cardiomyopathy Patients
Bibliographic record
Abstract
Background: Many studies have shown that T-peak to T-end (TPTE) interval was associated with sudden cardiac events. Peripartum cardiomyopathy (PPCM) causes reversible left ventricle systolic dysfunction which may deteriorate into sudden cardiac death. This study aimed to evaluate beta-blocker as an antiarrhythmic agent to improve TPTE interval as a prognostic value of sudden cardiac death. Methods: A cohort experimental prospective study was performed. The PPCM was diagnosed from the emergency ward. A total of 54 cases were identified from 2014 to 2016. Thirty-four patients were followed up for further analysis. Electrocardiograms were conducted in all the patients, and TPTE interval was measured. After a follow-up of 6 months of beta-blocker treatment, the echocardiography and TPTE interval were measured again to obtain the repolarization heterogeneity. Results: The mean age of subjects was 32 ± 6.4 years. The mean left ventricular ejection fraction (LVEF) was 32.24±6.3%. The mean TPTE interval was 123.7 ± 28.2 ms. After 6 months of beta-blocker administration, the mean LVEF was 58.26±4.4% and the mean TPTE was 98.7 ± 39.5 ms. The paired t -test showed a significant difference between TPTE interval pre- and post-administration of beta-blocker (P value < 0.001). Conclusions: There is an improvement of TPTE in PPCM patients after 6 months of beta-blocker administration. Administration of beta-blocker in PPCM patients is expected to prevent sudden cardiac death in PPCM populations. Cardiol Res. 2020;11(3):185-191 doi: https://doi.org/10.14740/cr1053
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".