2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes
2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes is a research paper published in European Heart Journal (2019). On theSindex it has a DataRank of 1.3. It has been cited 7,033 times.
Abstract
Coronary artery disease (CAD) is a pathological process characterized by atherosclerotic plaque accumulation in the epicardial arteries, \nwhether obstructive or non-obstructive. This process can be modified by lifestyle adjustments, pharmacological therapies, and invasive \ninterventions designed to achieve disease stabilization or regression. \nThe disease can have long, stable periods but can also become unstable at any time, typically due to an acute atherothrombotic event \ncaused by plaque rupture or erosion. However, the disease is \nchronic, most often progressive, and hence serious, even in clinically \napparently silent periods. The dynamic nature of the CAD process \nresults in various clinical presentations, which can be conveniently categorized as either acute coronary syndromes (ACS) or chronic \ncoronary syndromes (CCS). The Guidelines presented here refer to \nthe management of patients with CCS
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Open Access
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
DataRank Breakdown
Base Score Contribution
1.3
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.