Infarct-Related Artery Patency After Transmural Anterior Myocardial Infarction and Q Wave Regression + R Wave Development: Is there a Relationship?
Bibliographic record
Abstract
Material and Methods: Sixty patients with CHF in stable regime (NYHA II-III, age 64 4-10 years) were randomized to receive either carvedilol 25 mg b.i.d, or matched placebo (2:1) in addition to unchanged standard therapy.Measurement of EF was made in 4-and 2 chamber apical views according to Simpson's modified method.A mean from three measurements of EF at baseline and after 23 weeks therapy, were compared.Fifty-three patients (35 carvedilol/18 placebo) fulfilled the study period.Results: Coefficient of variation of EF was 5.9%.EF increased in the carvedilol group from 29.8 4-7.8 to 35.5 4-9.8% (P < 0.001 vs. baseline), and compared with placebo the improvement was significant (+5.7 vs. -0.9%,P = 0.001).Patients treated with carvedilol (n = 17) and a heart rate above the median (78 beats per minute) had a significant improvement of EF from 27.7 4-6.4 to 37.1 4-9.4 (P < 0.001 vs. baseline), whereas it was unchanged in the carvedilol group (n = 18) below the heart rate median (P = 0.13).The improvement of EF in the high heart rate group was significant compared with the low heart rate group (+9.4 vs. +2.0%,P < 0.01).Conclusion: Heart rate seems to be useful to point out a group of patient with CHF who will have a superior improvement of left ventricular systolic function during treatment with carvedilol.The finding needs to he investigated in a prospective design to elucidate the importance of heart rate in accordance to mortality and morbidity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".