Prognotic Role of CMR in Takotsubo Syndrome

NCT ID: NCT06277297

Last Updated: 2025-06-08

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

350 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-11-09

Study Completion Date

2032-11-30

Brief Summary

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The primary objective of this observational registry is to develop a comprehensive clinical and imaging score (incorporating echocardiography and cardiac magnetic resonance data) that enhances risk stratification for patients with Takotsubo syndrome.

The secondary objectives of this registry are as follows:

Investigate the diagnostic value of cardiac magnetic resonance parameters in predicting in-hospital and long-term outcomes in patients with Takotsubo syndrome.

Compare the proposed risk stratification score for patients with Takotsubo syndrome with previously existing scores.

Investigate the contribution of machine learning models in predicting in-hospital and long-term outcomes compared to standard clinical scores.

The design and rationale of this registry are available at 10.1097/RTI.0000000000000709

Detailed Description

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The prognosis of Takotsubo syndrome patients remains contentious, necessitating improved risk stratification for better management. While various clinical characteristics and parameters from transthoracic echocardiography have been associated with outcomes, none of the existing predictive scores incorporate cardiac magnetic resonance imaging (CMR) data, despite its ability to noninvasively assess tissue characterization. CMR offers a comprehensive evaluation of functional and structural changes, including an accurate assessment of right ventricular function. While CMR has been extensively studied for diagnostic purposes in Takotsubo syndrome, its role in prognosis is still debated. Emerging technologies like computed tomography show promise in myocardial characterization but lack robust investigation in prognostic roles. The EVOLUTION registry aims to address this gap by incorporating CMR parameters into a risk stratification score alongside clinical and transthoracic echocardiography data, with machine learning models also explored for enhanced outcome prediction. This initiative seeks to provide a more reliable predictive tool for the optimized management of Takotsubo syndrome patients. The main objective of this study is to enhance risk assessment in Takotsubo syndrome patients by incorporating CMR data alongside demographic, clinical, and transthoracic echocardiography parameters. Specifically, the aim is to analyze CMR data and their association with both short-term and long-term patient outcomes. Additionally, the effectiveness of the proposed risk stratification score for Takotsubo syndrome patients will be evaluated in comparison to existing scoring systems. Moreover, all available CMR, transthoracic echocardiography, and clinical variables will be utilized to develop machine learning models for predictive analysis

Conditions

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Takotsubo Cardiomyopathy Machine Learning Magnetic Resonance Imaging

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* Takotsubo syndrome diagnosis (according to Position Statement of the European Society of Cardiology Heart Failure Association)
* Adult patients ( \> 18y old)
* Availability at baseline of clinical variables, standard transthoracic echocardiography, and cardiovascular magnetic resonance acquisition

Exclusion Criteria

* \<18 y old
* Lack of transthoracic echocardiography and cardiovascular magnetic resonance examinations
* Preexisting cardiomyopathies
* Previous myocardial infarction
* Suspected or known prior irreversible myocardial damage
* Valvular heart disease
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Centro Cardiologico Monzino

OTHER

Sponsor Role collaborator

IRCCS San Raffaele

OTHER

Sponsor Role collaborator

University of Roma La Sapienza

OTHER

Sponsor Role collaborator

Fondazione C.N.R./Regione Toscana "G. Monasterio", Pisa, Italy

OTHER_GOV

Sponsor Role collaborator

University of Messina

OTHER

Sponsor Role collaborator

University of Udine

OTHER

Sponsor Role collaborator

Vannini Hospital Rome

UNKNOWN

Sponsor Role collaborator

A.O.U. Città della Salute e della Scienza - Molinette Hospital

OTHER

Sponsor Role collaborator

University Hospital, Bonn

OTHER

Sponsor Role collaborator

University Hospital, Rouen

OTHER

Sponsor Role collaborator

University of Cagliari

OTHER

Sponsor Role lead

Responsible Party

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Riccardo Cau

Principal investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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University of Cagliari

Cagliari, Italy, Italy

Site Status RECRUITING

Countries

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Italy

Central Contacts

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Riccardo Cau, MD

Role: CONTACT

+3393493317

Facility Contacts

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Riccardo Cau

Role: primary

+393393493317

References

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Cau R, Muscogiuri G, Pisu F, Gatti M, Velthuis B, Loewe C, Cademartiri F, Pontone G, Montisci R, Guglielmo M, Sironi S, Esposito A, Francone M, Dacher N, Peebles C, Bastarrika G, Salgado R, Saba L. Exploring the EVolution in PrognOstic CapabiLity of MUltisequence Cardiac MagneTIc ResOnance in PatieNts Affected by Takotsubo Cardiomyopathy Based on Machine Learning Analysis: Design and Rationale of the EVOLUTION Study. J Thorac Imaging. 2023 Nov 1;38(6):391-398. doi: 10.1097/RTI.0000000000000709. Epub 2023 Apr 4.

Reference Type BACKGROUND
PMID: 37015834 (View on PubMed)

Other Identifiers

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NP/2022/4583

Identifier Type: -

Identifier Source: org_study_id

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