Prognostic Value of Echocardiographic Parameters Based on Machine Learning Approach

N/AUnknownNCT05772091

Pr. Nicolas GIRERD1,000 enrolled

Overview

Transthyretin cardiac amyloidosis is an increasingly recognized cause of heart failure with preserved ejection fraction. Its diagnosis is currently based on a non-invasive method including biology and imaging. Still currently incurable, the evolution of this pathology is burdened by numerous comorbidities, including iterative hospitalizations for heart failure leading to death. The Machine Learning approach has already shown its efficiency in terms of diagnosis but its prognostic approach has not yet been studied.

Study Type

OBSERVATIONAL

Enrollment

1,000

Conditions

Transthyretin Cardiac Amyloidosis

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Patients with suspicion of transthyretin cardiac amyloidosis * Age ≥18 years Exclusion Criteria: * Lack of data to confirm or overturn the transthyretin amyloidosis diagnostic * Echocardiographic data not allowing deep analysis (technical default, bad echogenicity of the patient) * Final diagnostic of AL or AA amyloidosis

Locations (4)

Hôpitaux Universitaires Henri Mondor

Créteil, France

NOT_YET_RECRUITING

CHRU de Nancy

Nancy, France

RECRUITING

CHU de Rennes Hôpital Pontchaillou

Rennes, France

NOT_YET_RECRUITING

Outcomes

Primary Outcomes

Rate of death from all causes

composite endpoint: rate of death from all causes and hospitalisation for acute heart failure following inclusion (with outcome 2