Characterization of the Human Coronary Microvascular Response to Multiple Hyperaemic Agents
Bibliographic record
Abstract
Background It is unclear whether the coronary microvascular responses to multiple, mechanistically distinct hyperaemic agents exert similar dilatory responses or share common clinical predictors. This study therefore sought to characterize the index of microvascular resistance (IMR) response to multiple hyperaemic agents in the human coronary circulation. Methods Thermodilution-derived IMR was determined during intravenous adenosine, intracoronary acetylcholine, and intravenous dobutamine in patients with ischemic symptoms and nonobstructive coronary angiograms. A total of 128 patients were studied (44 with adenosine and acetylcholine, and 84 with all agents). Adenosine IMR >25, acetylcholine IMR >31, and dobutamine IMR >29 were used to define elevated responses. Results IMR responses demonstrated weak-to-moderate association (adenosine vs acetylcholine IMR: ρ = 0.33; adenosine vs dobutamine IMR: ρ = 0.51; acetylcholine vs dobutamine IMR: ρ = 0.28; all P < 0.01). Logistic regression analyses revealed that: (1) elevated adenosine IMR was associated with increasing age and left ventricle hypertrophy (odds ratio [OR] = 1.27 and 1.58; both P < 0.05, respectively), (2) elevated acetylcholine IMR was associated with increasing plasma uric acid (OR = 1.09; P < 0.05), and (3) elevated dobutamine IMR was associated with hypertension and left atrial volume index (OR = 3.99 and 1.07; both P < 0.05, respectively). Subset analyses to evaluate clinical utility of the acetylcholine and dobutamine IMR, independent of abnormal adenosine IMR, revealed that elevated acetylcholine and/or dobutamine IMR were associated with higher risk exercise stress tests, left atrial volumes, and burden of exertional chest pain. Conclusions Microvascular-specific IMR responses to different hyperaemic agents are only moderately associated, whereas the predictors for agent-specific IMR responses varied, suggesting that multiple pharmacologic agents interrogate different microvascular control mechanisms.
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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".