Evaluation by Dipirydamole MRI of the effects of cardiac rehabilitation after myocardial infarction
Bibliographic record
Abstract
Background: The effects of exercise training (ET) on myocardial perfusion after myocardial infarction have been well studied with scintigraphy whereas cardiac MRI seems a better technique which was not used yet in the literature in this indication. Methods: 11 patients after a first myocardial infarction were left again in 2 groups: a 20 session-ET program (T, n=6) and a control group (C, n=5). All patients underwent a dipirydamole MRI and a cardiopulmonary test at entry and after 3 months. Results At 3 months, improvements in work capacity (P < 0,05), peak VO2 (P < 0,05) were observed in T but not in C. Ejection fraction and left ventricular (LV) volumes were unchanged in T and C. Myocardial perfusion assessed by MRI was comparable at rest and after dipirydamole in each group. The recuperation of the segmentary kinetics was inversely proportional to the delayed enhancement given by MRI and was better for T than for C (P < 0,02). Conclusions: This is a preliminary study. Cardiac MRI makes it possible to apprehend perfusion in a reliable and reproducible way. ET has no detrimental effects on LV volumes and function; rather, it improves recovery of infarcted segments.
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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 | 0.001 |
| 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) | 0.001 | 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".