Abstract 18770: Understanding Patients’ Characteristics and Coronary Microvasculature: Early Insights From First US Coronary Microvascular Dysfunction Registry
Bibliographic record
Abstract
Introduction: Coronary angiography falls short in accurately evaluating the coronary microcirculation. Fortunately, a new comprehensive invasive hemodynamic assessment method, which uses coronary flow reserve (CFR) and the index of microvascular resistance (IMR), provides enhanced diagnostic capabilities. Objective: We present our early real-world experience with invasive hemodynamic assessment of the coronary microvasculature in symptomatic patients with non-obstructive coronary artery disease (CAD) from the first US Coronary Microvascular Disease Registry (CMDR). Methods: The CMDR is a prospective, multi-center, standardized registry of patients with angina and non-obstructive CAD who underwent invasive hemodynamic assessment of the coronary microvasculature using the Coroventis CoroFlow Cardiovascular System (Abbott Laboratories, Chicago, Illinois). Comprehensive assessments, including resting full-cycle ratio (RFR), fractional flow reserve (FFR), CFR, and IMR, were performed on all patients. Results: The first 156 patients enrolled in the CMDR were analyzed; their mean age was 62.4 years and 65.6% were female. A substantial proportion (31.8%) of patients presented with a Canadian Cardiovascular Society Angina Score of 3 or 4. CMD was diagnosed in 39 of 154 patients (25.3%), with mean RFR of 0.89±0.43, mean FFR of 0.93±0.08, mean CFR of 1.8±0.9, and mean IMR of 36.26±19.23. None of the patients experienced in-hospital adverse events. Conclusions: Early results from CMDR patients show that invasive hemodynamic assessment of the coronary microvasculature is safe and effective for suspected CMD. Tailored medical therapy for microvascular angina was provided to diagnosed CMD patients. With ongoing patient enrollment, the CMDR aims to contribute valuable insights to the growing evidence base for CMD.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".