Evidence map›Paper›PMID 36207164›Full record

ArticleThe Journal of thoracic and cardiovascular surgery2024

The predictive capability of aortic stiffness index for aortic dissection among dilated ascending aortas.

Ronald N Fortunato, Lauren V Huckaby, Leonid V Emerel, Virginia Schlosser, Fan Yang, Julie A Phillippi, David A Vorp, Spandan Maiti, Thomas G Gleason

Abstract read
In one paragraph

Article in The Journal of thoracic and cardiovascular surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Radiographic phenotyping of healthy and diseased aortas.Journal of cardiovascular imaging · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Ronald N FortunatoDepartment of Mechanical Engineering and Materials Science, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pa.
Lauren V HuckabyDepartment of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pa.
Leonid V EmerelDepartment of Cardiothoracic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pa.
Virginia SchlosserDepartment of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pa.
Fan YangDepartment of Statistics, University of Pittsburgh School of Public Health, Pittsburgh, Pa.
Julie A PhillippiDepartment of Cardiothoracic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pa; Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pa; McGowan Institute for Regenerative Medicine, Pittsburgh, Pa.
David A VorpDepartment of Mechanical Engineering and Materials Science, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pa; Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pa; Department of Cardiothoracic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pa; Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pa; McGowan Institute for Regenerative Medicine, Pittsburgh, Pa; Department of Chemical and Petroleum Engineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pa; Asheville Heart, Asheville, NC.
Spandan MaitiDepartment of Mechanical Engineering and Materials Science, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pa; Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pa; Department of Chemical and Petroleum Engineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pa.
Thomas G GleasonDepartment of Cardiothoracic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pa; Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pa; Asheville Heart, Asheville, NC. Electronic address: tgleason@ashevilleheart.com.

Funding

Vascular Surgery Research Training (VascTrain) ProgramT32HL098036 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Edith Tzeng · 2010 to 2026
$7.2M
Cardiovascular Bioengineering Training ProgramT32HL076124 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SANJEEV G SHROFF · 2005 to 2026
$7.0M
ROS Mechanisms in BAV AortopathyR01HL109132 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI GLEASON, THOMAS GILLETTE · 2012 to 2024
$6.2M
Matrix mediated vasa vasorum dysfunction in thoracic aortic diseaseR01HL131632 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI PHILLIPPI, JULIE A · 2017 to 2021
$1.9M
NHLBI NIH HHS R01 HL109132NHLBI NIH HHS R01 HL131632NHLBI NIH HHS T32 HL076124NHLBI NIH HHS T32 HL098036
6 · The paper itself

Abstract

objectiveWe created a finite element model to predict the probability of dissection based on imaging-derived aortic stiffness and investigated the link between stiffness and wall tensile stress using our model.

methodsTransthoracic echocardiogram measurements were used to calculate aortic diameter change over the cardiac cycle. Aortic stiffness index was subsequently calculated based on diameter change and blood pressure. A series of logistic models were developed to predict the binary outcome of aortic dissection using 1 or more series of predictor parameters such as aortic stiffness index or patient characteristics. Finite element analysis was performed on a subset of diameter-matched patients exhibiting patient-specific material properties.

resultsTransthoracic echocardiogram scans of patients with type A aortic dissection (n = 22) exhibited elevated baseline aortic stiffness index when compared with aneurysmal patients' scans with tricuspid aortic valve (n = 83, P < .001) and bicuspid aortic valve (n = 80, P < .001). Aortic stiffness index proved an excellent discriminator for a future dissection event (area under the curve, 0.9337, odds ratio, 2.896). From the parametric finite element study, we found a correlation between peak longitudinal wall tensile stress and stiffness index (ρ = .6268, P < .001, n = 28 pooled).

conclusionsNoninvasive transthoracic echocardiogram-derived aortic stiffness measurements may serve as an impactful metric toward predicting aortic dissection or quantifying dissection risk. A correlation between longitudinal stress and stiffness establishes an evidence-based link between a noninvasive stiffness parameter and stress state of the aorta with clinically apparent dissection events.

Indexed as

Aortic AneurysmAortic DissectionEchocardiographyFinite Element AnalysisVascular StiffnessAgedAortaDilatation, PathologicFemaleHumansMaleMiddle AgedModels, CardiovascularPredictive Value of TestsStress, Mechanicalaneurysm pathophysiologyaortic dissectionaortic wall stiffnessaortic wall tensile stresscomputational modelingdissection risk predictionstress analysis

Identifiers

PMID36207164
PMCPMC10225159

What OpenQuestion holds

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Registered trials

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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.