Coronary Flow Reserve of the Non-Ischemia Related Coronary Artery During Dobutamine Stress Echocardiography
Bibliographic record
Abstract
Background: Incorporation of analysis of coronary velocities in stress studies adds diagnostic value to both clinical variables and dobutamine echocardiography. Micorcirculatory abnormalities may precede obstructive corornary disease. Therefore the aim of this study was to assess Doppler derived coronary velocity and flow of the left anterior descending coronary artery (LAD) during dobutamine stress echocardiography (DSE) in patients without LAD-related ischemia. Methods: Sixty nine patients with chest pain underwent DSE studies to evaluate myocardial ischemia. All had trans-thoracic Doppler interrogation of the distal LAD before and just after termination of the DSE. Coronary velocity reserves (CFR) were calculated as the ratios of post-DSE/baseline diastolic velocities. Volumetric flow in the distal LAD was calculated from the diameter of LAD color jet and velocity integral. Volumetric flow reserve was calculated as the ratio of post-DSE baseline LAD flows. Results: At rest all subjects had left ventricular wall motion score index (WMSI) = 1, while in 28, wall motion abnormality appeared in non-LAD territory with WMSI = 1.17 ± 0.08. Peak diastolic velocity after DSE increased form 28.5 ± 13.6 to 52.4 ± 23.7 cm/sec, P = 9.5 × 10 -11 , and velocity-CFR was 2.08 ± 0.7. Diastolic LAD flow increased from 36.5 ± 23.8 to 75.75 ± 48.7 mL/min, P = 1.21 × 10 -7 and volumetric-CFR was 2.6 ± 2.8. Peak diastolic velocity-CFR in patients without LV wall motion abnormality was 2.4 ± 0.7 while in those with motion abnormality 1.77± 0.56, P = 0.00008. Flow-derived LAD-CFR was 3.3 ± 3.7 in those without compared to 1.88 ± 0.57 in patients with wall motion abnormality, P < 0.05. Conclusion: LAD velocity and flow reserves are reduced in patients with remote myocardial ischemia, which may indicate early atherosclerotic involvement. Â Â Cardiol Res. 2011;2(4):174-180 doi: https://doi.org/10.4021/cr57w
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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".