Detection of cardiac allograft vasculopathy by multi-layer left ventricular longitudinal strain in heart transplant recipients.


Journal

The international journal of cardiovascular imaging
ISSN: 1875-8312
Titre abrégé: Int J Cardiovasc Imaging
Pays: United States
ID NLM: 100969716

Informations de publication

Date de publication:
May 2021
Historique:
received: 11 10 2020
accepted: 24 12 2020
pubmed: 15 1 2021
medline: 16 10 2021
entrez: 14 1 2021
Statut: ppublish

Résumé

Cardiac allograft vasculopathy (CAV) is an obliterative and diffuse type of coronaropathy that develops in the transplanted human heart, representing a major cause of graft failure and mortality. Nowadays the gold standard for the diagnosis of CAV is coronary angiography (CA). Non-invasive CAV detection, especially in the early stages of the disease, is still challenging. Our study aimed to investigate the role of speckle tracking echocardiography (STE), in particular three-layer STE, in predicting CAV at early stages, and if other traditional echocardiographic, clinical or biochemical parameters could relate to CAV. The study population was composed of a total of 33 heart transplanted patients, divided accordingly to the presence or absence of CAV (12 CAV+ , 22 CAV-). All subjects underwent a complete transthoracic echocardiographic examination on the same day of the CA, and all conventional parameters of myocardial function were obtained, including strain values assessed by STE. Strain values were significantly reduced in presence of CAV, at each myocardial layer but in particular the endocardial-epicardial gradient (- 4.15 ± 1.6 vs - 1.7 ± 0.4% < .0001) that was also highly predictive of CAV (AUC at ROC curve 0.97). Among diastolic parameters, the E wave deceleration time (DT) and the mean E/e' ratio were strongly positively associated with CAV. In our population, left ventricular global longitudinal strain (GLS), layer-specific GLS and the endocardial-epicardial LS gradient, E wave DT and E/e' ratio were the best independent non-invasive predictors of CAV.

Identifiants

pubmed: 33442856
doi: 10.1007/s10554-020-02147-2
pii: 10.1007/s10554-020-02147-2
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1621-1628

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Auteurs

C Sciaccaluga (C)

Department of Medical Biotechnologies, Section of Cardiology, University of Siena, Siena, Italy. carlotta.sciaccaluga@gmail.com.

G E Mandoli (GE)

Department of Medical Biotechnologies, Section of Cardiology, University of Siena, Siena, Italy.

N Sisti (N)

Department of Medical Biotechnologies, Section of Cardiology, University of Siena, Siena, Italy.

M B Natali (MB)

Department of Medical Biotechnologies, Section of Cardiology, University of Siena, Siena, Italy.

A Ibrahim (A)

Department of Medical Biotechnologies, Section of Cardiology, University of Siena, Siena, Italy.

D Menci (D)

Department of Medical Biotechnologies, Section of Cardiology, University of Siena, Siena, Italy.

A D'Errico (A)

Department of Internal Medicine, University of Siena, Siena, Italy.

G Donati (G)

Department of Internal Medicine, University of Siena, Siena, Italy.

G Benfari (G)

Division of Cardiology, Department of Medicine, University of Verona, Verona, Italy.

S Valente (S)

Department of Medical Biotechnologies, Section of Cardiology, University of Siena, Siena, Italy.

S Bernazzali (S)

Department of Cardiac Surgery, University Hospital of Siena, Siena, Italy.

M Maccherini (M)

Department of Cardiac Surgery, University Hospital of Siena, Siena, Italy.

S Mondillo (S)

Department of Medical Biotechnologies, Section of Cardiology, University of Siena, Siena, Italy.

M Cameli (M)

Department of Medical Biotechnologies, Section of Cardiology, University of Siena, Siena, Italy.

M Focardi (M)

Department of Medical Biotechnologies, Section of Cardiology, University of Siena, Siena, Italy.

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