Evidence map›Paper›PMID 27844188›Full record

ArticleLa Radiologia medica2017

Correlation and predictive value of aortic root calcification markers with coronary artery calcification and obstructive coronary artery disease.

Christian Tesche, Carlo N De Cecco, Andrew Stubenrauch, Brian E Jacobs, Akos Varga-Szemes, Sheldon E Litwin, B Devon Ball, Moritz Baquet, David Jochheim, Ullrich Ebersberger and 4 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in La Radiologia medica, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 27% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Machine learning to predict hemodynamically significant CAD based on traditional risk factors, coronary artery calcium and epicardial fat volume.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Article
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  6. 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

14 authors at 3 institutions in 3 countries.

Christian TescheDivision of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA.
Carlo N De CeccoDivision of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA.
Andrew StubenrauchDivision of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA.
Brian E JacobsDivision of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA.
Akos Varga-SzemesDivision of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA.
Sheldon E LitwinDivision of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA.
B Devon BallDivision of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA.
Moritz BaquetDepartment of Cardiology, Hospital of the Ludwig-Maximilians-University, Marchioninistrasse 15, 81377, Munich, Germany.
David JochheimDepartment of Cardiology, Hospital of the Ludwig-Maximilians-University, Marchioninistrasse 15, 81377, Munich, Germany.
Ullrich EbersbergerDivision of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA.
Richard R BayerDivision of Cardiology, Department of Medicine, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA.
Ellen HoffmannDepartment of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Englschalkinger Strasse 77, 81925, Munich, Germany.
Daniel H SteinbergDivision of Cardiology, Department of Medicine, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA.
U Joseph SchoepfDivision of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, 29403, USA. schoepf@musc.edu.ORCID http://orcid.org/0000-0002-6164-5641
Medical University of South Carolina · USLudwig-Maximilians-Universität München · DEMünchen Klinik Bogenhausen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the correlation between aortic root calcification (ARC) markers and coronary artery calcification (CAC) derived from coronary artery calcium scoring (CACS) and their ability to predict obstructive coronary artery disease (CAD).

methodsWe retrospectively analyzed 189 patients (47% male, age 60.3 ± 11.1 years) with an intermediate probability of CAD who underwent clinically indicated CACS and coronary CT angiography (CCTA). ARC markers [aortic root calcium score (ARCS) and volume (ARCV)] were calculated and compared to CAC markers: coronary artery calcium score (CACS), volume (CACV), and mass (CACM). CCTA datasets were visually evaluated for significant CAD (stenosis ≥ 50%) and the ability of ARC markers to predict obstructive CAD was assessed.

resultsARCS (mean 67.7 ± 189.5) and ARCV (mean 67.3 ± 184.7) showed significant differences between patients with and without CAC (109.4 ± 238.6 vs 9.42 ± 31.4, p < 0.0001; 108.5 ± 232.4 vs 9.9 ± 30.5, p < 0.0001). A strong correlation was found for ARCS and ARCV with CACS, CACM, and CACV (all p < 0.0001). In a multivariate analysis, ARCS (OR 1.09, p = 0.033) and ARCV (OR 1.12, p = 0.046) were independent markers for CAC. Using a receiver-operating characteristics analysis, the AUC to detect severe CAC was 0.71 (p < 0.0001) and 0.71 (p < 0.0001) for ARCS and ARCV, respectively. ARCS (0.67, p < 0.0001) and ARCV (0.68, p < 0.0001) showed discriminatory power for predicting obstructive CAD, yielding sensitivities 61 and 78% and specificities of 62 and 80%, respectively.

conclusionARC markers are associated with and independently predict the presence of CAC and obstructive CAD. Further testing is required in patients with severe ARC and significant CAD in order to reliably obtain these markers from thoracic-CT or X-ray for proper risk classification.

Indexed as

Coronary AngiographyTomography, X-Ray ComputedAgedAortic Valve StenosisBody Mass IndexCoronary Artery DiseaseCoronary StenosisFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesSensitivity and SpecificitySeverity of Illness IndexVascular CalcificationAortic root calcificationCoronary artery calcium scoreCoronary artery diseaseCoronary computed tomographic angiography

Identifiers

PMID27844188
OpenAlexW2553504955

What OpenQuestion holds

Textmetadata
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.