Evidence map›Paper›PMID 36619296›Full record

ReviewAmerican journal of preventive cardiology2023

Imaging subclinical coronary atherosclerosis to guide lipid management, are we there yet?

Pamela Piña, Daniel Lorenzatti, Rita Paula, Jonathan Daich, Aldo L Schenone, Carlos Gongora, Mario J Garcia, Michael J Blaha, Matthew J Budoff, Daniel S Berman and 2 more

Open access · goldAbstract readReview
In one paragraph

Review in American journal of preventive cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
  3. Utility of Cardiovascular CT in Ischemic Heart Disease.Echocardiography (Mount Kisco, N.Y.) · 2025
    Review
  4. Review
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 4 institutions in 2 countries.

Pamela PiñaCardiology Division, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA.
Daniel LorenzattiCardiology Division, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA.
Rita PaulaCardiology Division, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA.
Jonathan DaichCardiology Division, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA.
Aldo L SchenoneCardiology Division, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA.
Carlos GongoraCardiology Division, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA.
Mario J GarciaCardiology Division, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA.
Michael J BlahaJohns Hopkins Ciccarone Center for the Prevention of Heart Disease. Baltimore, MD, USA.
Matthew J BudoffDepartment of Medicine, Lundquist Institute at Harbor UCLA Medical Center, Torrance, CA, USA.
Daniel S BermanDepartment of Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Salim S ViraniSection of Cardiology, Department of Medicine. Baylor College of Medicine, and Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, USA.
Leandro SlipczukCardiology Division, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA.
Albert Einstein College of Medicine · USAga Khan University · PKCedars-Sinai Medical Center · USUCLA Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atherosclerotic cardiovascular disease risk (ASCVD) is an ongoing epidemic, and lipid abnormalities are its primordial cause. Most individuals suffering a first ASCVD event are previously asymptomatic and often do not receive preventative therapies. The cornerstone of primary prevention has been the identification of individuals at risk through risk calculators based on clinical and laboratory traditional risk factors plus risk enhancers. However, it is well accepted that a clinical risk calculator misclassifies a significant proportion of individuals leading to the prescription of a lipid-lowering medication with very little yield or a missed opportunity for lipid-lowering agents with a potentially preventable event. The development of coronary artery calcium scoring (CAC) and CT coronary angiography (CCTA) provide complementary tools to directly visualize coronary plaque and other risk-modifying imaging components that can potentially provide individualized lipid management. Understanding patient selection for CAC or potentially CCTA and the risk implications of the different parameters provided, such as CAC score, coronary stenosis, plaque characteristics and burden, epicardial adipose tissue, and pericoronary adipose tissue, have grown more complex as technologies evolve. These parameters directly affect the shared decision with patients to start or withhold lipid-lowering therapies, to adjust statin intensity or LDL cholesterol goals. Emerging lipid lowering studies with non-invasive imaging as a guide to patient selection and treatment efficacy, plus the evolution of lipid lowering therapies from statins to a diverse armament of newer high-cost agents have pushed these two fields forward with a complex interaction. This review will discuss existing risk estimators, and non-invasive imaging techniques for subclinical coronary atherosclerosis, traditionally studied using CAC and more recently CCTA with qualitative and quantitative measurements. We will also explore the current data, gaps of knowledge and future directions on the use of these techniques in the risk-stratification and guidance of lipid management.

Indexed as

CACCCTALipidsPlaque burdenPlaque characterization

Identifiers

PMID36619296
PMCPMC9813535
OpenAlexW4312054104

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.