Evidence map›Paper›PMID 34801452›Full record

ArticleJACC. Cardiovascular imaging2022

Mean Versus Peak Coronary Calcium Density on Non-Contrast CT: Calcium Scoring and ASCVD Risk Prediction.

Omar Dzaye, Alexander C Razavi, Zeina A Dardari, Daniel S Berman, Matthew J Budoff, Michael D Miedema, Olufunmilayo H Obisesan, Ellen Boakye, Khurram Nasir, Alan Rozanski and 5 more

Open access · goldAbstract read
In one paragraph

Article in JACC. Cardiovascular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 4% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

  1. Pooled it
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  7. Article
  8. Article
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  10. Observational
  11. Article
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  15. Article
  16. Coronary Artery Calcium Scoring in Asymptomatic Patients.HCA healthcare journal of medicine · 2023
    Review
  17. Article
  18. Article
  19. Relationship BetweenAnnals of nuclear cardiology · 2022
    Article
  20. Explainable Machine-Learning Model to Classify Culprit Calcified Carotid Plaque in Embolic Stroke of Undetermined Source.Journal of neuroimaging : official journal of the American Society of Neuroimaging
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 8 institutions in 2 countries.

Omar DzayeJohns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. Electronic address: odzaye@jhmi.edu.
Alexander C RazaviJohns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.
Zeina A DardariJohns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Daniel S BermanDepartment of Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Matthew J BudoffLundquist Institute, Harbor-UCLA Medical Center, Torrance, California, USA.
Michael D MiedemaMinneapolis Heart Institute and Foundation, Minneapolis, Minnesota, USA.
Olufunmilayo H ObisesanJohns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Ellen BoakyeJohns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Khurram NasirDivision of Cardiovascular Prevention and Wellness, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas, USA.
Alan RozanskiDivision of Cardiology, Mount Sinai, St. Luke's Hospital, New York, New York, USA.
John A RumbergerDepartment of Cardiac Imaging, Princeton Longevity Center, Princeton, New Jersey, USA.
Leslee J ShawDepartment of Radiology, Weill Cornell Medicine, New York, New York, USA.
Martin Bødtker MortensenJohns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark.
Seamus P WheltonJohns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Michael J BlahaJohns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Johns Hopkins University · USCedars-Sinai Medical Center · USCornell University · USHouston Methodist · USMinneapolis Heart Institute Foundation · USPrinceton University · USSt. Luke's Hospital · USUCLA Medical Center · US

Funding

PATHOPHYSIOLOGY OF MYOCARDIAL DISEASEST32HL007227 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Chulan Kwon, WENDY S POST · 1985 to 2026
$21.2M
NHLBI NIH HHS L30 HL110027NHLBI NIH HHS T32 HL007227
6 · The paper itself

Abstract

objectivesThis study sought to assess the relationship between mean vs peak calcified plaque density and their impact on calculating coronary artery calcium (CAC) scores and to compare the corresponding differential prediction of atherosclerotic cardiovascular disease (ASCVD) and coronary heart disease (CHD) mortality.

backgroundThe Agatston CAC score is quantified per lesion as the product of plaque area and a 4-level categorical peak calcium density factor. However, mean calcium density may more accurately measure the heterogenous mixture of lipid-rich, fibrous, and calcified plaque reflective of ASCVD risk.

methodsWe included 10,373 individuals from the CAC Consortium who had CAC >0 and per-vessel measurements of peak calcium density factor and mean calcium density. Area under the curve and continuous net reclassification improvement analyses were performed for CHD and ASCVD mortality to compare the predictive abilities of mean calcium density vs peak calcium density factor when calculating the Agatston CAC score.

resultsParticipants were on average 53.4 years of age, 24.4% were women, and the median CAC score was 68 Agatston units. The average values for mean calcium density and peak calcium density factor were 210 ± 50 HU and 3.1 ± 0.5, respectively. Individuals younger than 50 years of age and/or those with a total plaque area <100 mm

conclusionMean and peak calcium density may differentially describe plaque composition early in the atherosclerotic process. Mean calcium density performs better than peak calcium density factor when combined with plaque area for ASCVD mortality prediction among persons with Agatston CAC 1-99.

Indexed as

AtherosclerosisCoronary DiseasePlaque, AtheroscleroticVascular CalcificationAdultCalciumFemaleHumansMalePredictive Value of TestsTomography, X-Ray ComputedYoung AdultCalciumatherosclerotic plaquecalcium densitycardiovascular diseasecoronary artery calciummultidetector computed tomographyprimary preventionriskvascular calcification

Identifiers

PMID34801452
PMCPMC8917973
OpenAlexW3211668745

What OpenQuestion holds

Textmetadata
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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.