Novel Applications for Invasive and Non-invasive Tools in the Era of ContemporaryPercutaneous Coronary Revascularisation
Bibliographic record
Abstract
: Percutaneous coronary intervention (PCI) is an expanding treatment option for patients with coronary artery disease (CAD). It is considered the default strategy for unstable presentation of CAD. PCI techniques have evolved over the last 4 decades with significant improvements in stent design, increase in functional assessment of coronary lesions, and the use of intra-vascular imaging. Nonetheless, the morbidity and mortality related to CAD remain significant. Advances in technology have allowed better understanding of the nature andprogression of CAD. New tools are now available that reflect the pathophysiological changes at the level of the myocardium and coronary atherosclerotic plaque. Certain changes within the plaque would render it more prone to rupture leading to acute vascular events. These changes are potentially detected using novel tools invasively, such near infra-red spectroscopy, or non-invasively using T2 mapping cardiovascular magnetic resonance imaging (CMR)and18F-Sodium Fluoride positron emission tomography/computed tomography. Similarly, changes at the level of the injured myocardium are feasibly assessed invasively using index microcirculatory resistance or non-invasively using T1 mapping CMR. Importantly, these changes could be detected immediately with the opportunity to tailor treatment to those considered at high risk. Concurrently, novel therapeutic options have demonstrated promising results in reducingfuture cardiovascular risks in patients with CAD. This Review article will discuss the role of these novel tools and their applicability in employing mechanical and pharmacological treatment to mitigate cardiovascular risk in patients with CAD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".