TY - JOUR
T1 - Exploring the EVolution in PrognOstic CapabiLity of MUltisequence Cardiac MagneTIc ResOnance in PatieNts Affected by Takotsubo Cardiomyopathy Based on Machine Learning Analysis
T2 - Design and Rationale of the EVOLUTION Study
AU - Cau, Riccardo
AU - Muscogiuri, Giuseppe
AU - Pisu, Francesco
AU - Gatti, Marco
AU - Velthuis, Birgitta
AU - Loewe, Christian
AU - Cademartiri, Filippo
AU - Pontone, Gianluca
AU - Montisci, Roberta
AU - Guglielmo, Marco
AU - Sironi, Sandro
AU - Esposito, Antonio
AU - Francone, Marco
AU - Dacher, Nicholas
AU - Peebles, Charles
AU - Bastarrika, Gorka
AU - Salgado, Rodrigo
AU - Saba, Luca
N1 - Publisher Copyright:
© 2023 Lippincott Williams and Wilkins. All rights reserved.
PY - 2023/11/1
Y1 - 2023/11/1
N2 - Purpose: Takotsubo cardiomyopathy (TTC) is a transient but severe acute myocardial dysfunction with a wide range of outcomes from favorable to life-threatening. The current risk stratification scores of TTC patients do not include cardiac magnetic resonance (CMR) parameters. To date, it is still unknown whether and how clinical, trans-thoracic echocardiography (TTE), and CMR data can be integrated to improve risk stratification. Methods: EVOLUTION (Exploring the eVolution in prognOstic capabiLity of mUlti-sequence cardiac magneTIc resOnance in patieNts affected by Takotsubo cardiomyopathy) is a multicenter, international registry of TTC patients who will undergo a clinical, TTE, and CMR evaluation. Clinical data including demographics, risk factors, comorbidities, laboratory values, ECG, and results from TTE and CMR analysis will be collected, and each patient will be followed-up for in-hospital and long-term outcomes. Clinical outcome measures during hospitalization will include cardiovascular death, pulmonary edema, arrhythmias, stroke, or transient ischemic attack. Clinical long-term outcome measures will include cardiovascular death, pulmonary edema, heart failure, arrhythmias, sudden cardiac death, and major adverse cardiac and cerebrovascular events defined as a composite endpoint of death from any cause, myocardial infarction, recurrence of TTC, transient ischemic attack, and stroke. We will develop a comprehensive clinical and imaging score that predicts TTC outcomes and test the value of machine learning models, incorporating clinical and imaging parameters to predict prognosis. Conclusions: The main goal of the study is to develop a comprehensive clinical and imaging score, that includes TTE and CMR data, in a large cohort of TTC patients for risk stratification and outcome prediction as a basis for possible changes in patient management.
AB - Purpose: Takotsubo cardiomyopathy (TTC) is a transient but severe acute myocardial dysfunction with a wide range of outcomes from favorable to life-threatening. The current risk stratification scores of TTC patients do not include cardiac magnetic resonance (CMR) parameters. To date, it is still unknown whether and how clinical, trans-thoracic echocardiography (TTE), and CMR data can be integrated to improve risk stratification. Methods: EVOLUTION (Exploring the eVolution in prognOstic capabiLity of mUlti-sequence cardiac magneTIc resOnance in patieNts affected by Takotsubo cardiomyopathy) is a multicenter, international registry of TTC patients who will undergo a clinical, TTE, and CMR evaluation. Clinical data including demographics, risk factors, comorbidities, laboratory values, ECG, and results from TTE and CMR analysis will be collected, and each patient will be followed-up for in-hospital and long-term outcomes. Clinical outcome measures during hospitalization will include cardiovascular death, pulmonary edema, arrhythmias, stroke, or transient ischemic attack. Clinical long-term outcome measures will include cardiovascular death, pulmonary edema, heart failure, arrhythmias, sudden cardiac death, and major adverse cardiac and cerebrovascular events defined as a composite endpoint of death from any cause, myocardial infarction, recurrence of TTC, transient ischemic attack, and stroke. We will develop a comprehensive clinical and imaging score that predicts TTC outcomes and test the value of machine learning models, incorporating clinical and imaging parameters to predict prognosis. Conclusions: The main goal of the study is to develop a comprehensive clinical and imaging score, that includes TTE and CMR data, in a large cohort of TTC patients for risk stratification and outcome prediction as a basis for possible changes in patient management.
KW - cardiac magnetic resonance
KW - machine learning
KW - prognosis
KW - risk stratification
KW - Takotsubo
UR - http://www.scopus.com/inward/record.url?scp=85163934114&partnerID=8YFLogxK
U2 - 10.1097/RTI.0000000000000709
DO - 10.1097/RTI.0000000000000709
M3 - Article
C2 - 37015834
AN - SCOPUS:85163934114
SN - 0883-5993
VL - 38
SP - 391
EP - 398
JO - Journal of thoracic imaging
JF - Journal of thoracic imaging
IS - 6
ER -