Coronary microvascular disease in women: epidemiology, mechanisms, evaluation, and treatment
Bibliographic record
Abstract
Coronary microvascular dysfunction (CMD) involves functional or structural abnormalities of the coronary microvasculature resulting in dysregulation of coronary blood flow (CBF) in response to myocardial oxygen demand. This perfusion mismatch causes myocardial ischemia, which manifests in patients as microvascular angina (MVA). CMD can be diagnosed non-invasively via multiple imaging techniques or invasively using coronary function testing (CFT), which assists in determining the specific mechanisms involving endothelium-independent and dependent epicardial and microcirculation domains. Unlike traditional coronary artery disease (CAD), CMD can often occur in patients without obstructive atherosclerotic epicardial disease, which can make the diagnosis of CMD difficult. Moreover, MVA due to CMD is more prevalent in women and carries increased risk of future cardiovascular events. Successful treatment of symptomatic CMD is often patient-specific risk factor and endotype targeted. This article aims to review newly identified mechanisms and novel treatment strategies for managing CMD, and outline sex-specific differences in the presentation and pathophysiology of the disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".